Winter 2006
CONTENTS
JSMAM VOLUME 6, WINTER 2006
5
From the Editor
By Dan C. Weilbaker, Ph.D.
ACADEMIC ARTICLES
6
Delivering Integration, Value, and Satisfaction Through Key
Account Manager’s Communication
By Laurent Georges
Do You See what I See? A Comparison of “Ivory Tower” and “Real
World Perspectives Regarding the Contribution of Sales related
Courses in University Curricula
22
By Rajesh Gulati, Dennis Bristow, and Douglas Amyx
An Analysis of the Effect of Sales Force Automation on Salesperson
Perceptions of Performance
38
By James E. Stoddard, Stephen W. Clopton, and Ramon A. Avila
APPLICATION ARTICLES
Relationships: The 21st Century Asset
58
By Jerry Acuff and Lori Champion
Word of Mouth Process: Your Way to Sales Success
65
By Joe Cullinane
Mission Statement
The main objective of the journal is to provide a focus for collaboration between
practitioners and academics for the advancement of application, education and
research in the areas of selling and major account management. Our audience is
comprised of both practitioners in industry and academics researching in sales.
©2006 By Northern Illinois University. All Rights Reserved. ISSN: 1463-1431
Vol. 6, No. 1
Journal of Selling & Major Account Management
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UNIVERSITY OF TOLEDO
Winter 2006
Manuscripts
1. Articles for consideration should be sent to Editor: Dan C. Weilbaker, Department of Marketing Northern Illinois University,
DeKalb, IL 60115 USA or by fax: 001 815-753-6014 or by Email to dweilbak@niu.edu
2. Articles in excess of 6000 words will not normally be accepted. The Editor welcome shorter articles, case studies and reviews.
Contributors should specify the length of their articles.
3. A manuscript copy of the contribution along with four (4) copies should be submitted if possible with a copy on 3.5"
diskette in Microsoft Word format, author's name(s) and short title of the article. Alternatively, the contribution may be emailed to
the above address as a Microsoft Word document; however contributors are advised to check by telephone that submissions have
been received. Neither the editor nor Northern Illinois University, Department of Marketing accepts any responsibility for loss or
damage of any contributions submitted for publication in the Journal.
Biographical note - supply a short biographical note giving the author(s) full name, appointment, institutions or
organization / company and recent professional attainments.
Synopsis - an abstract not exceeding 100 words should be included.
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References - should be cited using the Harvard method. No footnotes should be used for references or literature citations.
Wherever possible, full bibliographic details (e.g., volume number issue number or date, page numbers publisher year of
publication) should be included.
Footnotes - for clarification or elaboration should be used very sparingly - they may be indicated in the text and at the
beginning of the footnote by the use of asterisks and / or daggers.
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Font style should be Times New Roman in 12 pitch. Footnotes should be typed at the bottom of the page and numbered
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7 An address for correspondence (including Email address) should be supplied as well as a telephone and fax number at which
the author(s) may be contacted. .
8. Authors undertake to check proofs and to return them within the specified date. They should be free from grammatical,
syntax or spelling errors. Failure to return proofs will result in the publication of the article at the editor’s discretion in which
event the editor does not accept liability for any changes made to grammar syntax, spelling or other changes deemed necessary.
The editor reserve the right not to accept any alterations or corrections made.
PERMISSIONS
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Subscriptions
To subscribe to Journal of Selling and Major Account Management, please go to www.cob.niu.edu/jsmam/subscription.asp or mail
the subscription form to The Journal of Selling and Major Account Management,. 128 Barsema Hall, Northern Illinois University,
DeKalb, IL 60115. Subscription prices are: U.S. Individual-$50; U.S. Corporation-$60; Foreign Individaul-$70; Foreign
Corporation $80.
EDITORIAL AND ADMINISTRATIVE STAFF
EDITOR—Dan C. Weilbaker, Ph.D.
McKesson Pharmaceutical Group
Professor of Sales
Department of Marketing
Northern Illinois University
dweilbak@niu.edu
EUROPEAN EDITOR—Kevin Wilson
Sales Research Trust
Peyrenegre
47350 Labretonie
France
Kevin@sales-research-trust.org
ASSISTANT—Ieva Engel
Professional Sales Program Secretary
Department of Marketing
Northern Illinois University
iengel@niu.edu
Vol. 6, No. 1
Journal of Selling & Major Account Management
EDITORIAL BOARD
Rolph E. Anderson
Drexel University
Mark C. Johlke
Bradley University
Ramon A. Avila
Ball State University
Eli Jones
University of Houston
Sonke Albers
Christian-Albrechts-University of Kiel
Buddy LaForge
University of Louisville
Terri Barr
Miami Unviersity—Ohio
Terry W. Loe
Kennesaw State University
Jim W. Blythe
University of Glamorgan
Daniel H. McQuiston
Butler University
Richard E. Buehrer
University of Toledo
Pete Naude
Manchester Business School
Steven Castleberry
University of Minnesota—Duluth
Stephen Newell
Western Michigan University
William L. Cron
Texas Christian University
Nigel f. Piercy
University of Warwick
Laura Cuddihy
Dublin Institute of Technology
Richard E. Plank
William Paterson University
René Y. Darmon
ESSEC Business School
Gregory A. Rich
Bowling Green State University
Dawn R. Deeter-Schmelz
Ohio University
Elizabeth Rogers
Portsmouth Business School
Sean Dwyer
Louisiana Tech University
Jeffrey K. Sager
University of North Texas
Paolo Guenzi
SDA Bocconi
Charles Schwepker, Jr.
Central Missouri State University
Jon M. Hawes
University of Akron
C. David Shepherd
Kennesaw State University
Earl D. Honeycutt
Elon University
William A. Weeks
Baylor University
Thomas N. Ingram
Colorado State University
Michael R. Williams
Illinois State University
Northern Illinois University
Winter 2006
From the Editor
As my first comments as the new editor, I want to thank Kevin and Enid Wilson at
the Sales Research Trust for passing the torch of ownership of the Journal of Selling &
Major Account Management to the Department of Marketing at Northern Illinois University. It is very important to have an outlet for academics and practitioners to publish actionable research that is focused on helping those in the sales field to improve.
The goal of the Journal was originally and will continue to be bringing the practitioner and academic together to advance the knowledge in professional selling and major account management. There are many things that the academic can learn by listening to the practitioner and many things that the practitioner can learn from the
academic researcher. The Journal of Selling & Major Account Management strives to make
it the premier place to find that knowledge.
The Journal of Selling & Major account Management will continue to be a quarterly publication and welcomes articles from both academics with original research that focuses
on application and practitioners with information to share with their peers.
Our thanks also goes to The MBA Program at Northern Illinois University and the
University Sales Center Alliance for their financial support to get the journal up and
running before any subscriptions were ever sold. Our thanks also go to the dedicated
members of the Editorial Review Board and our ad hoc reviewers.
In this first issue of the re-launching of the Journal of Selling & Major Account Management the three academic articles cover a wide range of topics from key account management to comparing academic and practitioner views on sales training in the university to sales force automation’s impact on performance. I think that academics
will find these articles interesting and stimulating while the practitioner will find at
least one “pearl” that can help in their jobs.
The two application articles offer much more for the practitioner in ways of things
that can be immediately introduced into daily working lives while the academic will
find several issues that may stimulate more study.
As a relatively new journal, I encourage any academic to submit an article for review.
In addition, I encourage any practitioner who would like to share some best practices
with others to contact me.
Dan C. Weilbaker, Ph.D.
Editor and
McKesson Pharmaceutical Group Professor of Sales
Northern Illinois University
Vol. 6, No. 1
6
Journal of Selling & Major Account Management
Delivering Integration, Value, And Satisfaction
through Key Account Manager’s Communication
By Laurent Georges
As an increasing number of supplying firms introduce key account management (KAM) systems to service their major
accounts, it becomes crucial to understand the impact of key account managers’ communication on collaborative
relationships. In this study, a model is advanced and tested that examines the nature and consequences of key account
manager’s communication behaviors. First, four different behaviors (i.e. offer adjustment, buying center consultation,
communication transparency and internal communication) are identified and defined thanks to a literature review and a
qualitative study among key account managers. Second, a model linking key account manager’s communication
behaviors and customer-perceived integration, customer-perceived value as well as satisfaction is empirically tested
against a sample of 102 purchasing managers. The findings suggest that key account manager’s offer adjustment
behavior mostly influences customer-perceived value, whereas internal communication has a significant impact on
customer’s satisfaction. Moreover, it appears that customer-perceived integration strongly depends on buying center
consultation and communication transparency. Managerial implications of the findings for key account managers as
well as top management are discussed, and several recommendations are formulated to improve communication
practices with key accounts.
INTRODUCTION
The management of collaborative relationships
with important customers has become a major
concern for marketing research and practice
alike. In business markets in particular, all
customers are not created equal (Hallberg 1995).
As a consequence, suppliers dedicate most of
their resources to their core portfolio made up
by clients who represent high stakes: the key
accounts (Pardo 1997). In the literature, many
denominations have been used: large accounts
(Miller and Heiman 1991), national accounts
(Stevenson and Page 1979), major accounts
(Barrett, 1986) and global accounts (Wilson and
Millman 2001). Considering the many terms
employed the present research uses “key
accounts” to subsume all of them.
Empirical researches have shown that key
accounts can be characterized along four basic
dimensions. Firstly, their volumes of purchases
are significant in terms of absolute value or in
percentage of the total supplier’s sales for the
concern product (Dishman and Nitse 1998).
Northern Illinois University
Secondly, their procurement decisions are
centralized but concern multiple actors (i.e. the
buying center) belonging to different
organizational positions (Stevenson 1980).
Thirdly, these large customers select a limited
number of suppliers to collaborate and build
partnerships (Wilson and Millman 2001). Finally,
many of these powerful customers ask for a
coordinated selling approach from their
suppliers (Homburg, Workman and Jensen
2002).
The paramount importance of these clients,
which are frequently geographically dispersed
and require specific procedures, raise complex
problems for suppliers. For instance, because
key accounts are usually located in many
countries it is almost impossible for a regular
salesperson to identify the buying center’s
members as well as their needs and wants. As a
consequence, the understanding and monitoring
of the relationship are far less evident compared
to a relationship with a regular customer. At the
same time, the set of demands from these
complex accounts (generally in the form of
Winter 2006
value-adding activities and worldwide
coordination) cannot be handled by a unique
salesperson. Often it requires the cooperation of
other functional entities. Thus, to manage the
complexity of these large-scale buyers, suppliers
have to rethink their internal sales organizations
and develop a key account management
structure (Weilbaker and Weeks 1997).
The cornerstone of these specific sales
organizations is a position called “key account
manager” (Millman 1994; Wotruba and
Castleberry 1993). As stated by Homburg,
Workman and Jensen (2002 p. 39) “key account
programs frequently involved special
(intraorganizational) actors who are dedicated to
key accounts.” Key account managers are driven
by different objectives than traditional
salespersons (Wotruba and Chastelberry 1993).
Instead of maximizing the volume of sales in the
short term, their overriding goal is to minimize
friction within the relationship and optimize fit
between the supplier’s value offer and
customer’s needs (Weitz and Bradford 1999).
Key account managers integrate customerrelated activities within their own company and
contribute to customer-perceived value (Georges
and Eggert 2003). To fulfill their role as an
enabler or promoter of an existing relationship
(Bacon 1999), key account managers’
communication is key. Effective communication
between the supplying and the buying firm is a
fundamental condition of collaborative
relationships. According to Bleeke and Ernst
(1993 p. 16), even the “most carefully designed
relationship will crumble without good, frequent
communication”. In a similar vein, Mohr and
Nevin (1990 p. 36) declare that communication
is the “glue” that holds relationships together.
Consequently, key account managers are
supposed to advance the level of communication
between the supplying and the buying firm
(Millman 1994; Schultz and Evans 2002).
To date, however, little empirical research has
been done to evaluate the impact of key account
managers’ communication efforts on
7
collaborative relationships. This paper
contributes to our understanding of
collaborative relationships by focusing on the
contribution of key account managers’
communication on customer-perceived
integration, customer-perceived value and
satisfaction. These three outcome variables were
chosen because they represent the “raison
d’être” of collaborative relationships (Anderson
1995).
In the remainder of this paper, in a first part, we
review the existing literature and provide
definition for the different constructs studied in
this research. In a second part, we develop a
conceptual framework and test our hypotheses
using structural equation modeling. Finally, we
discuss theoretical and managerial implications,
outline limitations of the study and highlight
future research opportunities.
LITERATURE REVIEW
The cornerstone of the key account management
organization is the position called “key account
manager” whose objective is not only to
maximize the volume of sales, but also to
increase the degree of perceived integration, the
value created as well as the customer satisfaction
(Wotruba and Castleberry 1993). To achieve
these outcomes, key account managers develop
specific communications behaviours.
Customer-Perceived Integration
As highlighted by Barrett (1986), key account
managers are usually supported by a team
composed of people from production, finance,
logistics, marketing or other functional groups.
These teams – large and small, permanent and ad
hoc – are considered as central elements of a key
account program (Jones et al. 2005). Therefore,
key account managers also act internally (i.e.
inside the supplier’s organization) to coordinate
the decisions and the pattern of contacts
between their team’s members and with the
customer’s organization. One of their main
objectives is to achieve a high degree of
integration between the supplier’s subsidiaries,
Vol. 6, No. 1
8
Journal of Selling & Major Account Management
functions and individuals interacting with the
customer firm. However, as achieving
integration is considered as an important
objective in a key account setting, there is no
uniform definition or accepted measure of this
construct. In a recent article, Rouziès et al. (2005)
reviewed the literature on interdepartmental
integration and identified two main forms of
conceptualization for this construct. A first
group of researchers (Clark and Fujimoto 1991;
Lawrence and Lorsh 1967) defines integration as
the extent of collaboration between the different
departments of a firm. A second group (Ruekert
and Walker 1987) adopts a multidimensional
approach and describes integration according to
the exchanges of resources, work, and technical
assistance and the amount and difficulty of
communication According to Rouziès et al.
(2005), it is necessary to distinguish integration
from other related constructs such as
interactions, communications, and involvement.
They argue that integration is a dynamic process
which could be defined as the extent to which
activities carried out by several functions or
individuals are supportive of each other. More
precisely, by supportive, they underline the fact
that the different activities carried out should
lead to the realization of each other’s goals and
objectives and that the timing must be
coordinated.
In the reminder of our research, we will adopt
this definition and consider that a key account
manager achieves a high degree of integration if
the activities of the supplier’s departments
involved in the relationship with the key account
are perceived as well coordinated and consistent.
Customer-Perceived Value
Although it did not attract much explicit
attention until it became a watchword in the
nineties, value has always been “the fundamental
basis for all marketing activity” (Holbrook 1994,
p. 22). The exchange view of marketing (Bagozzi
1975; Hunt 1991) is based on the concept of
value. Market exchanges take place because all
parties involved expect to be better off after the
Northern Illinois University
exchange. The higher the net-value expected or
received, the stronger the motivation to
commence and to sustain an exchange process
respectively. While the literature contains a
variety of definitions stressing different aspects
of the value concept, four recurring
characteristics can be identified: (1) Value is a
subjective concept, (2) it is conceptualized as a
trade-off between benefits and sacrifices, (3)
benefits and sacrifices can be multi-facetted, and
(4) value perceptions are relative to competition.
Value is a subjectively perceived construct
(Kortge et al. 1993). Different customer
segments perceive different values within the
same product. In addition, the various members
in the customer organization involved in the
purchasing process can have different
perceptions of a supplier's value delivery
(Perkins 1993). This is of particular importance
in business markets where the buying center
consists of several persons sharing different roles
and responsibilities (Robinson, Farris and Wind
1967; Webster and Wind 1972).
Most definitions present customer-perceived
value as a trade-off between benefits and
sacrifices perceived by the customer in a
supplier’s offering (Zeithaml 1988, p.14; Monroe
1990 p. 46). Among other conceptualizations,
benefits are conceived as a combination of
economic, technical, service, and social benefits
(Anderson et al. 1993) or economic, strategic,
and behavioral benefits. Sacrifices are sometimes
described in monetary terms (Anderson et al.
1993). Other definitions describe sacrifices more
broadly as a combination of price and
relationship related costs (Grönroos 1997).
Finally, value is relative to competition. The
value of a market offering is always assessed in
relation to a competing offer. This resembles the
notion of the Comparison Level (CL Alt) that is
fundamental to social exchange theory (Thibault
and Kelley 1959).
On a high level of abstraction, customerperceived value is defined as the trade-off
between the benefits (“what you get”) and the
9
Winter 2006
sacrifices (“what you give”) in a market exchange
(Zeithaml 1988 p. 14).
Customer Satisfaction with the Key Account
Manager
Customer satisfaction research is based on the
disconfirmation paradigm (Parasuraman et al.
1988). This paradigm states that the customer’s
feeling of satisfaction is a result of a comparison
process between perceived performance and one
or more comparison standards, such as
expectations. The customer is satisfied when he
feels that the supplier’s performance is equal to
what was expected (confirming). If the supplier’s
performance exceeds expectations, the customer
is very satisfied (positively disconfirming), if it
remains below expectations, the customer will be
dissatisfied (negatively disconfirming).
Though most scholars agree on the
disconfirmation paradigm, the nature of
satisfaction remains ambiguous. On the one
hand, satisfaction arises from a cognitive process
comparing perceived performance against some
comparison standards. On the other hand, the
feeling of satisfaction essentially represents an
affective state of mind. Consequently some
satisfaction scales tap the cognitive dimension of
satisfaction, while others capture its affective
nature.
In accordance with the majority of research
being done on the satisfaction construct, we
define customer satisfaction with the key
account manager as an affective state of mind
resulting from the appraisal of all relevant
aspects of the business relationship (Geyskens et
al. 1999 p. 223).
Key Account Manager’s Communication
Research on communication in a KAM setting is
virtually nonexistent (for a notable exception, see
Schultz and Evans 2002). Most of the research
on communication and its impact on business
relationships have been done within in a
marketing channel context or among traditional
salespersons. Table 1 provides an overview over
selected facets of communication that have
previously been studied.
A qualitative study was done to get a wellgrounded understanding of the different
communication activities performed by key
account managers. Consistent with standard
procedures for qualitative research (Glaser and
Strauss 1967; Yin 1984; Zaltman et al. 1982),
twenty in-depth interviews and one focus group
with key account managers were recorded and
transcribed. Content analysis was conducted by
three marketing scholars to develop a
classification scheme and to examine the
meaning of the different communication
activities. Four communication-related variables
were identified. They were labeled as buying
center consultation, internal communication,
offer adjustment, and transparency, respectively.
TABLE 1:
Selected research on communication
Auhors
Facet of communication studied
Sheth (1976)
content and style
Frazier an Summers (1984)
content
Soldow and Thomas (1984)
code and rules
Williams and Spiro (1985)
content, rules, and style
Mohr and Nevin (1990)
frequency, direction, richness, and content
Mohr and Spekman (1994)
quality of information and participation
Leuthesser and Kohli (1995)
frequency, richness, strategy to influence
Schultz and Evans (2002)
strategic content, frequency, bi-directionality, and informality
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10 Journal of Selling & Major Account Management
FIGURE 1
Conceptual Framework
Offer
Adjustment
H1 (+)
Customer-Perceived
Value
H2(+)
Communication
Transparency
H4 (+)
Customer-Perceived
Integration
H7 (+)
H5 (+)
Buying Center
Consultation
H3 (+)
Customer Satisfaction
with the Key
Account Manager
Internal
Communication
H6 (+)
CONCEPTUAL MODEL
Figure 1 depicts our conceptual framework of
communication and its impact on customerperceived value, customer-perceived integration
and satisfaction with the key account manager.
In the following, we elaborate on its underlying
hypotheses.
Key account managers acquire an in-depth
knowledge of customers and their needs
(Wotruba and Castleberry 1993). As part of their
boundary-spanning function, they communicate
their insights within their own organization to
foster innovative solutions to customer
problems, fuel customer orientation and
ultimately increase the fit between their
organization’s value offer and customer’s needs.
As a good fit will promote customer-perceived
value, hypothesis 1 reads as follows:
H1: Offer adjustment has a positive
impact on customer-perceived value.
Transparency has been defined as the perception
Northern Illinois University
of being informed about the relevant actions and
properties of the other party in the interaction
process (Eggert and Helm 2003). Key account
managers impact transparency by providing
useful information about the supplier’s strategy,
marketing programs and competitive status.
From the customer’s perspective, supplier
transparency reduces uncertainty and facilitates
the interaction process. It therefore appears
reasonable to hypothesize:
H2: Supplier transparency has a
positive impact on the customerperceived level of integration.
Buying center consultation captures a key
account manager’s efforts to understand the
needs and preferences of a buying center. The
more intensively a key account manager
communicates with the different members of the
buying center, the more likely he is to obtain
valuable information about their needs and
preferences (Leuthesser and Kohli 1995). As
valid information is regarded as an antecedent of
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coordinated action, we hypothesize:
H3: Buying center consultation has a
positive impact on the customerperceived level of integration.
Key account managers orchestrate customerrelated efforts within their own organization
(Pardo, Salle and Spencer 1995) in order to
increase the customer-perceived level of
integration. An increased level of integration
facilitates the interaction process, reduces
customer-perceived costs of handling that
relationship and enhances customer satisfaction
(Mohr and Spekman 1994). Stated more
formally, hypotheses 4 and 5 posit:
H4: Customer-perceived integration
has a positive impact on customerperceived value.
H5: Customer-perceived integration
has a positive impact on customer
satisfaction.
To make sure that their clients enjoy a preferred
status among their own organization’s
employees, key account managers engage in
internal communication. By means of internal
communication, they develop and strengthen a
set of shared values between the client’s and
their own organization’s personnel. As this
contributes to customer satisfaction (Helman
and Payne 1992), we hypothesize:
H6: Internal communication has a
positive impact on customer
satisfaction.
Finally, customer-perceived value has been
shown to be an antecedent of customer
satisfaction in business markets (Anderson and
Narus 1984; Eggert and Ulaga 2002). In
distribution channels, Frazier (1983) showed that
economic results or gratifications influence
customer satisfaction. Consequently, the seventh
hypothesis posits:
H7: Customer-perceived value has a
positive impact on customer
satisfaction.
11
QUANTITATIVE STUDY
Data Collection
To validate our conceptual framework, we
interviewed purchasing agents who are serviced
by a key account manager. This population is not
compiled in a complete list, preventing us from
drawing a straightforward probability sample.
Instead we first had to generate a list of
respondents. Potential respondents were
identified through a snowballing sampling
procedure which is particularly well suited for
special populations that are difficult to access
(Dawes and Lee 1996). An initial set of 52
purchasing agents was identified by the key
account managers interviewed during our
qualitative study. Overall, 335 questionnaires
were sent out with 127 (38 %) being returned.
Participants were asked to select a purchasing
relationship meeting the following three
conditions: (1) the relationship was served by a
key account manager, (2) the relationship with
the supplier was a collaborative one and (3) the
purchases were predominantly industrial goods
and not industrial services. As the key informant
methodology was applied to collect data, we also
assessed our informants’ competency in
accordance with Kumar, Stern and Anderson
(1993). From the 127 questionnaires returned, 25
contained missing data or did not meet the
screening requirements, leading to a net sample
size of 102.
Sample Characteristics
The final sample consists of purchasing agents
working in a large variety of industries, such as
automobiles (20%), chemicals (15%),
pharmaceuticals (7%), electronics (7%), steel
(6%), computer (6%), transportation (5%), food
(5%), industrial equipment (5%) and others
(24%). The product categories considered by
respondents in their buyer-seller relationships are
components (35%), equipment (24%), raw
materials (25%) and semi-finished products
(16%). More than two third of the respondents
firms (67%) had more than 10.000 employees
Vol. 6, No. 1
12 Journal of Selling & Major Account Management
and about one third of the sample is composed
of firms which had more than 30.000 employees.
74% of the selected relationships were qualified
as long term relationships by the respondents
and 26% as partnerships.
Measures
Regarding customer-perceived integration,
customer-perceived value and customer
satisfaction, we used multi-item scales from
measures adopted in relevant literature. As for
key account manager’s communication behaviors
(i.e. offer adjustment, transparency, internal
communication and buying center consultation),
new scales were developed based on literature
review and our qualitative research. The
questionnaire was pre-tested with 31 purchasing
managers. After some minor adjustments, the
resulting items were included in the final survey
(see Appendix for scale items). Our measures are
reflective as opposed to formative. In fact, in
keeping with the suggestions provided by Jarvis
et al. (2003), the constructs used in this research
relate to individual attitudes or behavioural
intentions, not to managerial aspects, and the
items are better interpreted as manifestations,
not characteristics of the underlying constructs.
ANALYSIS AND RESULTS
Scale Purification
As recommended by Churchill (1979) and
Nunnally (1978) several steps were taken to
ensure scale purification. In the first step, an
exploratory factor analysis and an examination of
the item intercorrelations, means, and standard
deviations were used. Two items measuring
transparency were dropped because of low
intercorrelations. We then assessed
unidimensionality by the presence of a first
factor in a principal components analysis that
accounted for a substantial portion of the total
variance. In addition, all items had a loading
greater than .80 with the theoretically correct
sign.
In the second step, internal consistency of the
scales was assessed by calculating the Cronbach
alpha, which for all constructs is well above .70.
In the third step, principal component analyses
with varimax and oblimin rotations were
conducted for the variables contained in each
hypothesis. High loadings on hypothesized
factors and low cross-loadings showed favorable
discriminant validity at the exploratory level.
Model Estimation
Structural Equation Modelling
The structural equation model, represented in
figure 1, was estimated using partial least square
(PLS) latent path model. PLS is a non-parametric
estimation procedure (Wold 1982). PLS can
accommodate small samples (Wold 1982) and it
provides measurement assessment which is
crucial to our study as we have a rather limited
sample size. With a sample size of 102, PLS was
better suited for our study because unlike
LISREL, PLS makes minimal demands about
sample size (Fornell and Bookstein 1982). Using
the resampling procedures (i.e. bootstrap), one
can calculate the standard deviation and generate
an approximate t-statistic. This overcomes nonparametric methods’ disadvantage of having no
formal significance tests for the estimated
parameters.
The PLS results are interpreted in two stages: (1)
by assessment of its measurement model, and (2)
by assessment of its structural model (Fornell
and Larcker 1981). The properties of the
measurement model are detailed in Table 2. All
factor loadings are higher than 0.73 and
Jöreskog’s Rho exceeded the 0.7 threshold
(Fornell and Larcker 1981). For each latent
variable, the average variance extracted is well
above 60 percent indicating favorable
convergent validity.
Northern Illinois University
In a second step, latent variables’ discriminant
validity was checked using the Fornell and
Larcker (1981) criterion. As shown in Table 3,
the square root of the average variance extracted
(AVE) exceeds the correlations between every
pair of latent variables. This indicates a
Winter 2006
13
TABLE 2
Scale properties of the measurement model
Customer
Satisfaction
Customer-Perceived
Value
Customer-Perceived Integration
Offer
Adjustment
Communication Transparency
Internal
Communication
Buying Center
Consultation
Item
Loading
Sati1
0.90
Sati2
0.86
Sati3
0.91
Sati4
0.87
Sati5
vale1
0.90
0.92
vale2
0.86
vale3
0.89
vale4
coor1
0.82
0.86
coor2
0.87
coor3
0.87
coor4
offr1
0.76
0.80
offr2
0.81
offr4
tran2
0.82
0.73
tran3
0.82
tran4
0.79
tran5
inte1
0.86
0.77
inte2
0.88
inte3
0.82
inte4
sult1
0.82
0.91
sult2
0.87
sult3
0.82
satisfactory level of discriminant validity.
Table 4 reports the standardized B1 parameter
which is based on the total sample, and the
standardized B2 parameter which is obtained
from bootstrap simulation. Differences between
both parameters are low, indicating stable
estimates. In accordance with our hypotheses, all
parameters were found to be positive.
Bootstrapped standard deviations and t-values
Rho de Jöreskog
Average Variance Extracted
0.94
0.79
0.93
0.76
0.91
0.68
0.85
0.66
0.88
0.65
0.89
0.71
0.91
0.75
(Guiot 2001) confirm the significance of all
seven hypotheses.
Parameter expansion (i.e. adding direct links e.g.
between transparency and value, and between
transparency and satisfaction) did not produce
any significant parameter estimates. This
provides empirical evidence for the validity of
the conceptual framework in general and the
moderating role of coordination in particular.
Vol. 6, No. 1
14 Journal of Selling & Major Account Management
TABLE 3
Discriminant validity
1
2
3
4
5
6
1. offer adjustment
0.81
2.transparency
0.54
0.81
3. buying center consultation
0.38
0.23
0.87
4. internal communication
0.53
0.33
0.29
0.84
5.customer-perceived integration
0.45
0.42
0.38
0.36
0.82
6. customer-perceived value
0.76
0.55
0.37
0.50
0.56
0.88
7. customer satisfaction
0.73
0.53
0.38
0.64
0.54
0.73
7
0.89
TABLE 4
Parameter estimates
Hypothesis
B1
parameter*
B2
parameter**
Standard
Deviation
t-value
Sig. at the
5% level
H1 offer adjustment à customer-perceived value
0.64
0.63
0.07
8.60
ü
H2 supplier transparency à customer-perceived
coordination
H3 buying center consultation à customer-perceived
coordination
H4 customer-perceived coordination à customerperceived value
H5 customer-perceived coordination à customer
satisfaction
H6 internal communication à customer satisfaction
0.35
0.36
0.06
5.63
ü
0.30
0.32
0.08
3.70
ü
0.27
0.28
0.08
3.56
ü
0.16
0.15
0.08
1.93
ü
0.35
0.35
0.06
5.50
ü
H7 customer-perceived value à customer satisfaction
0.46
0.46
0.09
5.16
ü
*B1 parameter is based on the total sample and the standardized
**B2 parameter is obtained from bootstrap simulation
DISCUSSION
This paper raises the research question whether
key account managers’ communication efforts
contribute to customer-perceived integration,
customer-perceived value and satisfaction in
business relationships with large-scale buyers.
Based on a quantitative study among 102
purchasing managers, our results show that key
account managers’ communication efforts have a
significant impact on the three outcome
variables. With a standardized path coefficient of
Northern Illinois University
0.64, offer adjustment has the strongest reported
impact on customer-perceived value. Key
account managers’ efforts to increase the
supplier’s transparency (standardized path
coefficient = 0.35) as well as their efforts to
understand the needs and preferences of the
buying center (standardized path coefficient =
0.30) increases the perceived level of integration.
Integration in turn impacts customer-perceived
value (standardized path coefficient = 0.27) as
well as customer satisfaction (standardized path
15
Winter 2006
coefficient = 0.16). Finally, key account
managers’ internal communication has a positive
impact on customer satisfaction (standardized
path coefficient = 0.35).
The theoretical contribution of our research to
current knowledge can be summarized as
follows. First, our findings fill a gap in the
literature on key account management. As
pointed out previously, there is a lack of
empirical research specifically investigating the
contribution of a key account manager’s
communication behaviors in fostering customer
perceived-value, satisfaction or perceivedintegration. Second, our findings fill a gap in
sales literature, where interpersonal relationships
mainly focused on traditional salespeople. On
the contrary, little attention has been devoted to
the contribution in the integration-building
process offered by key account managers. Since
key account managers play a different role in
nurturing relationships with customers than that
of traditional salespeople, their contribution in
developing customer perceived-outcomes
needed to be investigated. Third, we used
customers as respondents: this is relevant,
because many empirical studies on the topic used
salespeople as key informants, thus incurring in
the risk of biases in relying on self-reported
measures of customer-based outcomes.
MANAGERIAL IMPLICATIONS
From a managerial point of view, these results
underline the importance of communication for
the development and maintenance of
collaborative relationships within a KAM setting.
This research also provides empirical evidence to
the notion that key account managers “utilize
collaborative communication to establish longerterm customer satisfaction and value-added
selling” (Schultz and Evans 2002 p. 23). The
findings reported in this paper concern both key
account managers and the individuals
responsible for the management of a key
account sales force.
Implications for key account managers
Our findings provide some important starting
points for an effective management of
relationships with key accounts. More
specifically, several recommendations can be
formulated regarding the way key account
managers might shape their communication
practices with their customers.
Offer adjustment: Key account managers create
value for their customers by improving the fit
between their organization’s value offer and
customer’s needs. To enhance the adjustment of
their offering, we advice key account manager to
make a systematic analysis to determine the
causes of the problems their customer might
encounter at the different stages of the
relationship with their organisation. They should
also listen beyond product needs and suggest
ways in which the customer may reduce its costs
and increase its benefits thanks to the supplier’s
products and services. Identifying constraints
before recommending corrective action is also a
prerequisite. Finally, as one key account manager
said during our qualitative study: “If I want to
create value for a key account, I need ton
constantly adapt my strategy and offering.
Therefore, modifying proposals or plans to deal
with the customers’ specific concerns and
incorporating customers’ suggestions is all part
of my job”.
Transparency: At this level, the goal is to
demonstrate the supplier’s value to the
customers in terms of customers’ financial
strategies and measures. From the customer’s
perspective, supplier transparency reduces
uncertainty and facilitates the interaction
process. To effectively increase transparency, key
account managers should inform their clients
about the actions that were taken by the supplier
to resolve past failures. They also impact
transparency by providing useful information
about the supplier’s strategy, marketing
programs and competitive status. To do so
effectively, they provide reports and documents
which help their clients to evaluate more
Vol. 6, No. 1
16 Journal of Selling & Major Account Management
thoroughly the supplier and its competitiveness.
Finally, as underlined by several key account
managers during our qualitative study, cultivating
transparency also implies formulating a clear
vision of how the supplier will contribute to the
relationship and what the key account/supplier
relationship can be in the future.
Buying center consultation: This behavior
reflects the key account managers’ own attempt
to understand the needs of the buying center. It
is shown to have a positive impact on customerperceived integration. On a practical level,
consultation implies regularly visiting the client’s
production sites to better understand the
expectations and needs of all departments
involved in the buying process. As one key
account manager said during our qualitative
study: “One of my key missions is to gathers
information to understand customers’ business
strategies and their view of their market
opportunities. To obtain such strategic
information, I network inside the buying center
(and sometimes outside) to broaden my
knowledge of the customer’s business”.
Internal communication: As shown in our study,
key account managers also have an important
internal role to play inside their firm to develop a
true “key account” orientation among all the
functions, departments and divisions of their
organization involved in the relationship with
the key account. As noted by one key account
man ager interview ed, th rough thi s
communication behaviour, they also look:
“Thanks to internal communication through
regular meetings, memos and newsletters, I try to
mobilize and assemble a balanced, diverse team
of experts to provide high-quality solutions and
service to customers. What I to do is to build a
real team spirit. I have even created a dedicated
website for the team dedicated to my key
accounts. Lotus Note© also provides some
interesting solutions to facilitate internal
communication between people who are not
always located in the same geographical
location”.
Northern Illinois University
Implications for the management of a key
accounts sales force
At a managerial level, the adoption and
reinforcement of these four behaviors could be
conducted in several ways. First, individuals
responsible for managing a key account sales
force should carefully select candidates for key
account positions, investigating their inclinations
(e.g. consideration of future sales consequences:
see Schultz and Good 2000) and skills (e.g.
communication skills: see Weitz and Bradford
1999). This screening can be done via relevant
personal histories and through the use of
interpersonal role-playing situations within the
interview environment. Second, companies
should design training programs specifically
aimed at helping key account managers to
develop those behaviors. For instance, key
account managers might be taught to exhibit
transparency and offer adjustment. These
behaviors can be taught by means of formal
lectures or role-playing exercises. Regarding
internal communication, management might
facilitate the development of this behavior by
providing different supports such as newsletters,
dedicated websites and information
technologies. Job rotation and frequent meeting
between the different functions involved in a
relationship with a key account should also be
encouraged. Third, when designing reward and
compensation schemes for key account
managers, sales managers may, at least in part,
take into account their behavioral performance
as well as indicators of relational performance,
such as customer satisfaction, perceived-value or
integration. Fourth, companies may change the
sales department’s organizational structure, as
well as their sales force control systems. For
example, managers may decide to create two
separate sales forces (a traditional one opposed
to a key accounts one) with different
compensation plans. Similarly, firms may shift
from outcome-based to behavior-based sales
force control systems, in order to better control
the actual implementation of communication
behaviors on the part of their key account
Winter 2006
managers. To do so, managers might use the
scales developed in our study.
LIMITATIONS AND FUTURE
RESEARCH OPPORTUNITIES
As in any empirical research, the results of the
present study cannot be interpreted without
taking into account the study’s limitations. First,
the relatively small sample size can be regarded
as a limitation. By definition, however, key
account relationships are not numerous. In many
industries, some dozens or even less key
accounts exist, making large-number research
virtually impossible. Instead of neglecting
empirical research and relying on conceptual
frameworks only, we recommend the application
of statistical methods that are particularly well
suited for small samples (e.g. PLS and the
bootstrap method). This way, complex models
can still be stably estimated. Second, the
snowball sampling method may raise concerns
with respect to the generalizability of the results
(Churchill 1979). Strictly spoken, only a
straightforward probability sample ensures
generalizability. For pure probability sampling, a
complete list of the population were required – a
condition that cannot be fulfilled in our case.
Under these circumstances, snowball sampling
appears as a pragmatic solution. As long as the
initial set is heterogeneous and relatively large,
this should lead to a good approximation of pure
probability sampling. Against this background,
replication studies that evaluate the
generalizability of the findings are of foremost
priority.
Future research on the topic should broaden our
framework by including other classes of
behaviors, such as coordination or conflict
resolution behaviors. Similarly, different
measures of performance could also be
considered, e.g. by comparing the impact of
relational behaviors on long-term versus shortterm performance indicators. In fact, some key
account manager’s behaviors may pay off only
over the long run, while being even detrimental
to immediate sales. Moreover, there is a need to
17
better understand both the organizational factors
(e.g. sales force control systems and training
programs) and the personal variables (e.g.
personality traits and skills) supporting the
adoption of relational behaviors from key
account managers.
REFERENCES
Anderson, J.C., 1995. Relationships in Business
Markets: Exchange Episodes, Value
Creation, and Their Empirical
Assessment. Journal of the Academy of
Marketing Science, 23 (4), 346-350.
Anderson, J.C. and Gerbing, D.W., 1988.
Structural Equation Modeling in Practice:
A Review and Recommended Two-Step
Approach. Psychological Bulletin, Vol.103,
411-423
Anderson, J.C. and Narus, J.A., 1999. Business
Market Management: Understanding, Creating,
and Delivering Value. Prentice Hall, Upper
Saddle River, NJ.
Anderson, J.C. and Narus, J.A., 1984. A Model of
the Distributor’s Perspective of
Distributor-Manufacturer Working
Relationships. Journal of Marketing, 48,( 4),
62-74.
Anderson, J. C., Dipak, C. J. and Pradeep, K. C.,
1993. Customer Value Assessment in
Business Markets. Journal of Business-toBusiness Marketing, 1 (1), 3-29.
Bacon, T. R., 1999. Selling to Major Accounts: Tools,
Techniques and Practical Solutions for the Sales
Manager. New York, NY: American
Management Association.
Bagozzi, R. P., 1975. Marketing as exchange.
Journal of Marketing, 3 (October), 32-39.
Barrett, J., (1986). Why Major Account Selling
Works? Industrial Marketing Management, 15,
63-73
Bleeke, J. and Ernst, D., 1993. Collaborating to
Compete. New York.
Cespedes F.V., 1995. Concurrent Marketing. Boston,
MA, Harvard Business School Press.
Chin, W. W., 1998a. The Partial Least Squares
Approach for Structural Equation
Modeling. In: G.A. Marcoulides, Modern
Methods for Business Research. Ed. Laurence
Vol. 6, No. 1
18 Journal of Selling & Major Account Management
Erlbaum Associates London.
Chin, W. W., 1998b. Issues and Opinion on
Structural Equation Modeling. Management
Information Systems Quarterly, Vol. 22, No. 1.
Chin, W. W. and Todd, P. A., 1995. On the Use,
Usefulness, and Ease of Use of Structural
Equation Modeling in MIS Research: A
Note of Caution”, MIS Quarterly, Vol. 19,
No 2, pp. 237-246
Chonko, L.B. and Burnap, H.F., 1998. Strategic
account strategies. In: G.J. Bauer et al., ed.
Emerging trends in sales thought and practice.
Westport, Quorum Books.
Churchill, G. A., 1979. A Paradigm for
Developing Better Measures of Marketing
Constructs. Journal of Marketing Research, 16
(February), 64-73.
Clark, K.B. and Fujimoto, T., 2005. Product
Development Performance: Strategy, Organization
and Management in the World Auto Industry.
Boston, MA: Harvard Business School
Press.
Dawes, P.L., Lee, D.Y., 1996. Communication
Intensity in Large-Scale Organizational
High Technology Purchasing Decisions.
Journal of Business-to-Business Marketing, 3
(3), 3-34.
Dishman, P., and Nitse, P.S., 1998. National
Account Revisited – New Lessons from
Recent Investigations. Industrial Marketing
management, 27, 1-9.
Eggert, A. and Helm, S., 2003. Exploring the
Impact of Relationship Transparency on
Business Relationships: A Cross-Sectional
Study Among Purchasing Managers in
Germany. Industrial Marketing Management,
32 (2), 101-108.
Eggert, A. and Ulaga, W., 2002. CustomerPerceived Value: A Substitute for
Satisfaction in Business Markets? Journal of
Business and Industrial Marketing, 17 (2/3),
107-118..
Fornell, C. and D. F. Larcker, 1981. Evaluating
Structural Equation Models with
Unobservable Variables and Measurement
Errors. Journal of Marketing Research, 18 (2),
39-50.
Fornell, C. and F. L. Bookstein, 1982. A
Comparative Analysis of Two Structural
Equation Models: LISREL and PLS Applied
Northern Illinois University
to Market Data. Working Paper, Ann
Arbor, Michigan.
Fornell, C., Lorange, P. and Roos J., 1990. The
Cooperative Venture Formation Process:
A Latent Variable Structural Modeling
Approach. Management Science, Vol. 36
Issue 10, 1246-1256
Frazier, G.L., 1983. Interorganizational Exchange
Behavior in Marketing Channels: A
Broadened Perspective. Journal of
Marketing, 47, (4), 68-78.
Georges, L. and Eggert, A. 2003. Key Account
Managers’ Role within the Value Creation
Process of Collaborative Relationships.
Journal of Business-to-Business Marketing, 10
(4), 1-21.
Geyskens, I., Steenkamp, J.-B., Kumar, N. 1999. A
Meta-Analysis of Satisfaction in Marketing
Channel Relationships. Journal of Marketing
Research, 36, 223-238.
Glaser, B. G. and Anselm, L. S., 1967. The Discovery
of Grounded Theory, Chicago: Aldine.
Grönroos, C., 1997. Value-Driven Relationship
Marketing: From Products to Resources
and Competencies. Journal of Marketing
Management, 13 (5), 407-419.
Guiot, D., 2001. Antecedents of Subjective Age
among Senior Women. Psychology and
Marketing, 18 (10), 1049-1071.
Hallberg, G. 1995. All consumers are NOT created
equal, New York.
Helman, D., Payne, A., 1992. Internal Marketing:
Myth versus Reality, Research Paper,
Cranfield School of Management.
Holbrook, Morris, B., 1994. The Nature of
Customer Value. In: R.T. Rust and R.L.
Oliver, Service Quality: New Directions in
Theory and Practice, Thousand Oaks, CA:
Sage, 21-71.
Homburg, C., Workman, J.P. and Jensen, O.,
2000. Fundamental Changes in Marketing
Organization : The Movement Toward a
Customer-Focused Organizational
Structure. Journal of the Academy of Marketing
Science, 28, 4, 459-478.
Homburg, C, Workman, JP and Jensen, O., 2002
Configurational perspective on key
account management. Journal of Marketing,
66 (April): 38-60.
Hunt, S. D. 1991. Modern Marketing Theory: Critical
Winter 2006
Issues in the Philosophy of Marketing Science.
Cincinnati: Ohio.
Jarvis, C. B., Mackenzie, S. B., and Podsakoff, P.
M., 2003. A Critical Review of Construct
Indicators and Measurement Model
Misspecification in Marketing and
Consumer Research. Journal of Consumer
Research, 30, (2), 199-218
Jones, E., Dixon, A.L., Chonko, L.B, and Cannon, J.P.,
2005. Key Accounts and Team Selling: A
review, Framework, and Research Agenda.
Journal of Personal Selling & Sales
Management, 25(2), 181-198.
Kortge, G. D. and Okonkwo, P.A., 1993. Perceived
Value Approach to Pricing. Industrial
Marketing Management. 22 : 133-140.
Kumar, N., Stern L. W. and Anderson J. C., 1993.
Conducting Interorganizational Research
Using Key Informants. Academy of
Management Journal, 36 (December), 16331651.
Lawrence, P.R. and Lorsh, J.W., 1969. Organization
and Environment : Managing Differentiation
and Integration. Homewood: Richard D.
Irwin, Inc.
Léger, C., Politis, D. and Romano, J.P., 1992.
Bootstrap technology and Applications.
Technometrics, 34, 378-398
Leuthesser, L., Kohli, A.K., 1995. Relational
Behavior in Business Markets:
Implications for Relationship
Management. Journal of Business Research,
34, 221-233.
Lohmöller, J.B., 1989. Latent Variable Path Modeling
with Partial Least Squares. New York:
Springer-Verlag.
Miller, RB, Heiman, SE, Tuleja, T., 1991. Successful
Large Account Management. London: Kogan
Page.
Millman T. (1994), Relational Aspects of Key
Account Management. 4th Seminar of the
European Network for Project Marketing and
Systems Selling, Pise, Italy.
Mohr, J. and Spekman, R., 1994. Characteristics of
Partnerships Success : Partnership
Attributes, Communication Behavior, and
Conflict resolution Techniques. Strategic
Management Journal, 15, 2, 135-152.
Mohr, J. and Nevin, J., 1990. Communication
Strategies in Marketing Channels – A
19
Theoretical Perspective. Journal of
Marketing, 50 (October), 36-51.
Monroe, K.B., 1990. Pricing – Making Profitable
Decisions. New York: McGraw Hill.
Nunnally, J. C., 1978. Psychometric Theory. 2nd ed.,
New York: McGraw-Hill
O’Loughlin, C. and Coenders, G., 2004,
Estimation of the European Customer
satisfaction Index: Maximum Likelihood
versus Partial Least squares; Application
to Postal Services. Total Quality
Management, 15 (9-10), 1231-1255.
Parasuraman, A., Zeithaml, V.A., and Berry L.
1988. SERVQUAL: A Multiple-Item
Scale for Measuring Consumer
Perceptions of Service Quality. Journal of
Retailing, 64 (Spring),12-40.
Pardo, C., 1997. Key Account Management in the
Business to Business Field: The Key
Account’s Point of View. Journal of Personal
Selling and Sales Management. 17 (Fall), 1726.
Pardo, C., Salle, R., and Spencer, R., 1995. The
Key Accountization of the Firm: A Case
Study. Industrial Marketing Management, 22,
123-134.
Perkins, W.S., 1993. Measuring Customer
Satisfaction. Industrial Marketing
Management, 22, 247-254.
Robinson, P., Faris C., and Wind Y. 1967.
Industrial buying and creative marketing,
Boston: Allyn and Bacon.
Rouziès, D., Anderson, E., Kohli, A.K., Michaels,
R.E., Weitz, B.A. and Zoltners, A.A.,
2005. Sales and Marketing Integration.
Journal of Personal Selling & Sales
Management, 25(2), 113-122.
Ruekert, R.W. and Walker, Jr. O.C., 1987.
Marketing’s Interaction with other
Functional Units: A Conceptual
Framework and Empirical Evidence.
Journal of Marketing, 51, 1, 1-19.
Schultz, R.J. and Evans, K.R., 2002. Strategic
Collaborative Communication by Key
Account Representatives. Journal of Personal
Selling and Sales Management, 22(1), 23-31.
Shapiro, B.P. and Moriarty, R.T., 1982. National
Account Management: Emerging Insights.
MSI Report, 82-100.
Sheth, J.N. and Parvatiyar, A., 2002. Evolving
Vol. 6, No. 1
20 Journal of Selling & Major Account Management
Relationship Marketing into a Discipline.
Journal of Relationship Marketing, 1(1), 3-16.
Stevenson, T.H., 1980. Classifying a Customer as a
National Account. Industrial Marketing
Management, 9, 133-136.
Stevenson, T.H. and Page, A.L., 1979. The
Adoption of National Account Marketing
by Industrial Firms. Industrial Marketing
Management, 8, 94-100.
Thibaut, J.W. and Kelley, H.H., 1959. The social
psychology of groups. New York: John Wiley.
Webster, F. and Wind, Y., 1972. A General Model
for Understanding Organizational Buying
Behaviour. Journal of Marketing, 36, 12-19.
Weilbaker, D.C., Weeks, W.A., 1997. The
Evolution of National Account
Management: A Literature Perspective.
Journal of Personal Selling and Sales
Management,17(4), 49-59.
Weitz, B. A. and Bradford, K.D., 1999. Personal
Selling and Sales Management: A
Relationship Marketing Perspective.
Journal of the Academy of Marketing Science, 27
(2), 241-254.
Wilson, K. and Millman, T.F., 2003. The Global
Account Manager as Political
Entrepreneur. Industrial Marketing
Management, 32, 151-58.
Wilson, D. T. and Swati, J. 1995. Understanding
the Value of a Relationship. Asia-Australia
Marketing Journal, 2 (1): 55-66.
Wold, H., 1982. Soft Modeling: The Basic Design
and Some Extensions. In: K.J. Jöreskog,
Wold, H., Systems Under Indirect Observation:
Causality, Structure, Prediction. Amsterdam:
North Holland Publishing.
Wotruba, T.R., Castleberry, S.B., 1993. Job
Analysis and Hiring Practices for National
Account Marketing Position. Journal of
Personal Selling and Sales Management, 13 (3),
49-65.
Yin, R.K., 1984. Case Study Research-Design and
Methods. Newbury Park, CA: Sage.
Zaltman, G., LeMasters, K. and Heffring, M.,
1982. Theory Construction in Marketing: Some
Thoughts on Thinking. New York, NY: John
Wiley.
Zeithaml, V. A., 1988. Consumer Perceptions of
Price, Quality, and Value: A Means-End
Model and Synthesis of Evidence. Journal
Northern Illinois University
of Marketing 52 (July), 2-22.
APPENDIX:
Scale Items
Construct
Measure Description
CustomerPerceived
Value a
Compared to other KAMsb, how would you
rate the target KAM’s contribution to…your
company’s competitiveness (vale1).
Cost reduction within your company
(vale2).
the fulfillment of the relationship
objectives (vale3).
the fulfillment of your company’s needs
(vale4).
Customer With respect to the target KAM, it can be
Satisfaction said that…
the quality of his work reconfirms
us having chosen the right
suppliers (sati1).
he contributes significantly to our
overall satisfaction with the
supplier (sati2).
his efforts have a positive impact
on our assessment of the
supplying company (sati3).
we better would chosen a different
supplier, taken into consideration
his performance (sati4).
he make it a pleasure to deal with
the supplier (sati5).
Customer- With respect to the KAM’s company (i.e. the
perceived
supplier), it can be said that…
Integration
the decisions are well coordinated
c
between the different subsidiaries
(coor1).
the different departments work
together
to
ensure
your
satisfaction (coor2).
the actions of the different
departments
are
mutually
consistent (coor3).
a real team spirit prevails between
the different departments (coor4).
21
Winter 2006
Offer
Adjustment c
With respect to the target KAM, it can
be said that…
the KAM collaborates with you
to adapt the supplier’s offer
to your specific needs (offr1).
the KAM regularly suggests
new solutions and ideas to
improve the relationship
(offr2).
the KAM tries to impose
standardized solutions (offr3,
reverse scored).*
the KAM does not make any
effort to customize the
supplier’s offer (offr4, reverse
scored).
Internal
With respect to the target KAM, it can
Communication be said that…
he defends our best interest in
his own organization (inte1).
he makes sure that the different
departments of his own
organization treat us as a
preferred customer (inte2).
he
urges
the
different
departments of his own
organization to adapt to our
needs (inte3).
he makes sure that the different
departments of his own
organization behave in a
cooperative
and
helpful
manner (inte4).
Buying-Center
Consultation c
With respect to the target key account
Communication manager, it can be said that…
Transparency c
he tends to be secretive about
the supplier’s strategy (tran1,
reverse scored).*
he tends to sidestep talk about
the supplier’s weaknesses
(tran2, reverse scored).*
he informs you of the actions
undertaken by the supplier to
improve your competitiveness
(tran3).
he presents reports and
documents which help you to
evaluate the supplier more
thoroughly (tran4).
he gives you a clear picture of
the measures the supplier has
taken to resolve past failures
(tran5).
Laurent Georges is Associate Professor of
Marketing, Polytechnic Institute of Tarbes, University of
Toulouse III, as well as a member of the Research Center
in Management and Cognition (LGC-EA 2043). His
research has been published in the Journal of Business-toBusiness Marketing and Industrial Marketing
Management Laurent.georges@iut-tarbes.fr
With respect to the target KAM, it can
be said that…
he works hard to understand
the expectations of all
departments involved in the
buying process. (sult1).
he visits your production sites
in order to understand your
employees’ needs (sult2).
he is only in contact with the
procurement
department
(sult3, reverse scored).
Vol. 6, No. 1
22 Journal of Selling & Major Account Management
Do You See What I See? A Comparison of “Ivory Tower” and
“Real World” Perspectives Regarding the Contribution
of Sales Related Courses in University Curricula
By Rajesh Gulati, Dennis Bristow, and Douglas Amyx
As a majority of college graduates with marketing degrees begin their professional careers in the sales area, delivering
appropriate sales education becomes an important objective of business schools. This study advances research efforts
in this area by examining perceptual differences between sales educators and sales managers with respect to the structure, content, and outcomes of professional selling and sales management courses currently being offered at most universities. Findings in this study reveal some important differences between sales educators who constitute the marketers of sales related education and sales managers, who as representatives of sales firms that hire graduates in sales positions, represent an important consumer group for such education. Findings in this study reveal some important differences between sales educators who constitute the marketers of sales related education and sales managers, who as representatives of sales firms that hire graduates in sales position, represent an important consumer group for such education. While results showed that both sales managers and sales educators indicated a preference for curriculums that
incorporate one or more professional selling and one or more courses in sales management, about 10% of the sales
managers viewed current university teaching formats for sales related courses as inadequate in terms of meeting the
needs of students seeking related careers. Differences were also found in sales managers’ and sales educators’ perceptions of the level to which sales related courses contributed to students’ related skill sets.
INTRODUCTION
Experts estimate that up to 80 percent of college
students majoring in marketing begin their career
in a sales related job (Heckman, 1998; Weilbaker,
2001). Selling Power Magazine (2005) reports that
the top 500 firms belonging to various industries
rely on approximately 17.5 million salespeople to
achieve their revenue objectives. Further, the
same report shows that between 2004 and 2005,
those 500 companies added nearly 2 million new
hires to their salesforces. In addition, the U.S.
Department of Labor Bureau of Labor Statistics
(BLS) Occupational Outlook Handbook (2004)
reported continued growth expectations in the
number of employment opportunities in sales
related arenas and strong demand for entry level
sales people with college degrees. Such statistics
indicate that professional selling is an essential
component of the business world and as such
offers a variety of exciting and challenging career
opportunities for university students graduating
with degrees in marketing and related business
disciplines.
Northern Illinois University
In the last two decades, business schools in the
U.S. have responded to this reality by integrating
sales courses more concretely into the marketing
curriculum. The emergence of sales centers at
some universities (e.g., Savage & Associates Center for Advance Sales & Marketing at The university campus, therefore, is an important source
for firms desirous of recruiting entry-level salespeople, a fact long acknowledged by researchers
(see Muehling & Weeks, 1988). the University of
Toledo; Fisher Center for Professional Selling at
the University of Akron; The Center for Professional Selling at Baylor University; the Professional Sales Institute at Illinois State University;
the Center for Professional Selling at Kennesaw
State University; the Gregg Professional Selling
Institute at Ball State University; the Sales Excellence Institute at the University of Houston; the
Center for Sales Studies and Market Intelligence
at the University of Indiana; the Russ Berrie Institute of Professional Selling at William Patterson University) underscores the value some marketing departments ascribe to sales education.
The presence of sales centers in business schools
Winter 2006
is, however, still uncommon. Marketing curricula
at most business schools currently include either
distinct professional selling and sales management courses or a combined course which incorporates components of both professional selling
and sales management.
Realization of the relevance of sales related
courses to students’ careers has resulted in an
increased focus on research in sales education. In
the fall of 1995, for example, the Journal of Marketing Education devoted a special issue that
addressed research on selling and sales management education. Topics explored in this issue
included the development of writing skills
(Donoho, Swenson & Taylor, 1995; McNeilly &
Ranney, 1995), screening and selection process
for sales jobs (Lollar & Leigh, 1995), relational
selling and group dynamics (Macintosh, 1995);
relationship selling (Tanner & Castleberry, 1995),
and telemarketing (Milner, 1995). These and
other similar studies (e.g., Marshall and Michaels
2001; McNeilly & Ranney, 1998; Ingram and
LaForge 1992) have contributed to improving
the quality of sales education in a continuing effort to provide students, who comprise an important consumer group for sales education,
with necessary selling and sales management
skills.
A related stream of research has delved into exploring how this consumer group perceives sales
careers. Examples include studies that have investigated students’ attitudes toward selling careers (Amin, Hayajneh, & Nwakanma, 1995; Bellenger, Bernhardt, & Wayman, 1974; Dauner &
Johnson, 1979; Lagace & Longfellow, 1989; Lysonski & Durvasula, 1998; Swenson, Swinyard,
Langrehr, & Smith, 1993), as well as investigations into student expectations and perceptions
of selling careers and sales jobs (Bellizzi & Hite,
1985; DelVecchio, 2000; Dubinsky, 1981;
Harmon, 1999). In addition, recent studies have
attempted to explore student perceptions regarding sales education and sales related careers
(Bristow, Gulati, Amyx, & Slack, in press, Bristow, Gulati, & Amyx, in press)
23
Extant research, therefore, has addressed appropriately the interests and needs of students by
attempting to make sales education more relevant and by eliciting feedback from this consumer group regarding sales careers. However, a
second important consumer group, the marketing and sales organizations that hire students for
entry level sales and sales management positions,
have largely been ignored. These organizations
consume the outputs of sales education in the
shape of sales related knowledge and skills that
reside in the students they hire and, therefore,
comprise the consumer segment that is the ultimate recipient and beneficiary of the quality and
relevance of sales education provided by business schools. Consequently, there is a need to
conduct studies that explore perceptions and
opinions that representatives of organizations
have regarding current sales related education in
order that educators, in the role as marketers,
can improve further the product that is sales
education. Much like the work others have performed in the area of supplier delusion (e.g., Ryals and Rogers 2006; Greek 1997; Turnbull,
Ford, and Cunningham 1996), such studies may
serve to reduce potential gaps between stakeholder perceptions of the university sales education product.
The need to obtain such feedback from organizations becomes more relevant in light of priorities formulated by the American Assembly of
Collegiate Schools of Business (AACSB). The
AACSB has suggested that business education
should focus on building relevant skills and imparting active learning (see Lamont & Friedman,
1997; Steven & Morris, 1997) and the standards
laid down by AACSB emphasize that curriculum
changes should be customer-driven (Bailey &
Dangerfield, 2000). For sales education, this
mandate can be more appropriately fulfilled if
educators elicit feedback from representatives of
hiring organizations such as sales managers in
order to develop sales related courses that reflect
the needs of these organizations. Obtaining input from sales managers regarding the structure,
manner, and content of sales related courses beVol. 6, No. 1
24 Journal of Selling & Major Account Management
comes meaningful because these managers may
have been recipients of sales education as students. Enriched by their experiences as salespersons and/or sales managers, these individuals
can provide practical insights to academicians
who design and teach sales courses.
This study adopts the consumer-driven perspective AACSB advocates and attempts to develop
initial benchmarks with respect to sales related
courses. In order to accomplish this, the current
study attempts to determine if differences exist
between academicians who teach sales related
courses (the marketers of sales education) and
sales managers (the ultimate consumers of sales
education) with respect to the perceptions they
hold toward sales education. The classic works
of Egon Brunswik and his cognitive lens model
(1952) suggest that such perceptual differences
between educators and managers would indeed
be predictable. Brunswik’s model has been
adapted and expanded (Bristow, Mowen, &
Krieger, 1994) and the resultant Marketing Lens
Model (see Figure 1) has subsequently been applied in a variety of research settings (Bristow,
1998; Bristow & Amyx, 1998, 1999; Bristow &
Asquith, 1999).
Northern Illinois University
The Marketing Lens Model (MLM) was developed to facilitate the assessment and comparison
of stakeholder perceptions and ratings of the
importance of and satisfaction with product/
service attributes/components across diverse
stakeholder groups. The MLM is based upon the
predication that one’s perceptions of his/her
environment are strongly influenced by the individual’s experiences, knowledge, and expectations (Brunswik, 1952). That is, different individuals and/or groups, having unique and varied
experiences and knowledge, can be expected to
exhibit distinctly different perceptions of the
environment (or products) they share.
The MLM consists of three distinct components:
(1) individual product/service attributes/
components, (2) the cognitive lenses of relevant
stakeholder groups, and (3) the perceptions of
relevant stakeholder groups. As can be seen in
Figure 1, the left side of the MLM consists of
product or service attributes that are of primary
importance to the stakeholder groups of interest.
In any application, this component of the model
consists of product or service attributes that are
of primary importance to the stakeholder groups
of interest. For example, as part of their marketing research, a marketer of laptop computers
Winter 2006
might seek to determine the degree to which the
perceptions of its own sales force members are
consistent with or diverge from the perceptions
of the target market with regard to the product’s
processor speed, dependability, user-friendliness,
memory capacity, and software compatibility. In
such a study, those elements of the laptop computer would represent the left side of the MLM.
In the current study, the left side of the model is
comprised of individual classroom formats commonly used to teach college/university level sales
related courses.
The second component of the MLM consists of
stakeholder groups’ cognitive lenses that may
account for discrepancies between stakeholder
groups’ perceptions of those teaching formats.
This central component of the model consists of
individual or group experiences that affect attitudes, beliefs, viewpoints, expectations, interpretations and so forth. As Brunswik suggested,
those perceptual lenses account for distinctions
in how different groups may perceive the same
element of a shared environment. For example,
imagine a sales trainee with virtually no industrial
selling experience and limited knowledge of the
product or the competition who is shadowing a
senior manufacturer’s representative with twenty
years of field experience and in-depth product
knowledge. Those two individuals, given their
different experience and knowledge, might be
expected to react very differently to the client
who pounds his or her desk and shouts, “Are
you crazy? I can get a similar product from your
competitor for much less!” In the same way that
the trainee and the manufacturers rep will differ
in their perceptions of the same stimulus in their
environment, the underpinnings of the MLM
suggest that university educators and sales managers, groups comprised of individuals likely to
have very different experiences, expectations,
and/or objectives, could be predicted to exhibit
dissimilar perceptions regarding the effectiveness
of the various teaching formats.
The product attributes, as perceived and evaluated by each consumer group studied, are represented by the third element of the model (the
25
right side). Previous researchers using the MLM
have assessed this cognitive side of the model via
survey methods and analyzed the data via t-tests
and Chi-square analysis (i.e., Bristow, 1998; Bristow & Amyx, 1999; Bristow & Asquith, 1999).
Based upon the literatures reviewed and the underpinnings of the MLM, this study seeks answers to the following four research questions:
1.
What perceptual differences, if any, exist
between academicians who teach sales
courses and sales managers regarding the
most effective format for teaching sales
related courses?
2.
What perceptual differences, if any, exist
between sales managers and academicians who teach sales related courses as
regards the contribution such courses
make in developing professional selling
skills in students?
3.
What perceptual differences, if any, exist
between sales managers and academicians who teach sales related courses as
regards the contributions such courses
make in developing sales management
skills in students?
4.
What perceptual differences, if any, exist
between sales managers and academicians who teach sales courses as regards
the adequacy of professional selling and
sales management courses in preparing
students for sales careers?
Although not stated in the research questions,
such a study does allow for directional evaluation
of perceptual differences between sales educators and sales managers. Specifically, the data
allow for comparisons that reveal which group,
sales educators or sales managers, has a more
favorable perception on any of the issues evaluated. And, although not specifically stated in the
research question, the authors expect that, in
general, sales educators should have more favorable perceptions than sales managers. In seeking
answers to the stated research questions, then,
the current study aims to begin a process of
evaluation of sales related courses and identify
areas, if any, that need modification so that acaVol. 6, No. 1
26 Journal of Selling & Major Account Management
demicians are better able to meet the needs of
graduating students and their prospective employers. The next section details the method employed to collect data. Thereafter the results of
the study are presented and are followed by a
discussion of the implications that flow from the
results. Finally, the limitations and future research avenues are listed.
METHOD
Survey Instrument
The researchers consulted textbooks in professional selling (e.g., Futrell, 2002; Weitz,
Castleberry & Tanner, 2001) and sales management (e.g., Dalrymple, Cron, & DeCarlo, 2002)
in addition to using their sales related expertise
and experiences in order to develop a list of
statements that addressed the abovementioned
research questions. This led to the formulation
of (a) eleven statements that tapped perceptions
regarding the extent to which professional selling
courses contribute to developing necessary sales
skills, (b) eight statements that addressed the
extent to which sales management courses provide relevant managerial skills in students, and
(c) seven statements that required respondents to
evaluate the importance and adequacy of professional selling and sales management courses currently offered by colleges and universities. In
addition, the researchers identified teaching formats commonly used in business schools to
teach sales related courses and included them as
components of a question in the survey instrument (see Table 1). Two separate survey instruments were developed to obtain feedback from
academicians and sales managers. Each questionnaire contained the above noted 26 statements
written into 5-point Likert type scales with end
points of (1) disagree completely and (5) agree
completely. In addition, each survey instrument
contained questions and statements designed to
seek demographic and other relevant information from the two respondent groups. Finally,
each instrument included a list of the following
teaching formats:
Northern Illinois University
Format 1: One or more college/
university courses in professional selling,
no course in sales management.
Format 2: One or more college/
university courses in sales management,
no course in professional selling.
Format 3: At least one college/university
course in professional selling and at least
one course in sales management.
Format 4: One college/university course
that combines both professional selling
and sales management.
College/university sales related courses
do not meet the needs of students intending to pursue a career in sales.
Educators were asked to indicate which of the
formats would provide students with the best
preparation for a career in professional selling/
sales management. Sales managers were asked
to indicate which professional selling/sales management teaching format most adequately met
the needs of college students desiring a career in
sales.
The survey instrument that sought to elicit information from academicians was reviewed for face
validity and subsequently pilot tested with eight
marketing faculty with expertise in one or more
disciplines including professional selling and/or
sales management, marketing research, and consumer behavior at a large mid-western university.
This process led to the rewording of several
items. A second pilot test revealed no problems
with the clarity or comprehensibility of the
items. The second survey instrument designed
for sales managers was similarly examined for
face validity and reviewed by several research
analysts, industry-based sales managers, and the
managing editor of nationally distributed sales
magazine. In order to facilitate statistical comparisons, the researchers were careful to ensure
that both survey instruments contained identical
statements.
Winter 2006
The two survey instruments were initially administered using electronic formats. As the response
of sales managers to the electronically distributed
questionnaire was marginal, the researchers incorporated the survey questions into a paper and
pencil questionnaire which was then distributed
to a sample of sales managers via the U.S. Postal
service.
Participants
The survey instrument was distributed electronically using the e-mail addresses of a national
sample of 1000 educators that were selected at
random from the American Marketing Association member directory. Due to a variety of reasons (i.e., failure notice; returned mail; local configuration error; name-server error report; undeliverable message; etc.), a total of 669 out of the
1000 e-mailed surveys were delivered successfully. A total of 219 responses were received resulting in a response rate of approximately 33%.
In addition to the 219 responses, another 40 emails were received indicating that those academicians did not teach sales related courses.
The researchers were interested in the responses
of only those educators who were either currently teaching, or had in the recent past (i.e., in
the last two years) taught sales related courses.
As this information was not available in the
AMA directory, the survey instrument contained
a screening question to facilitate appropriate responses from the sample of educators. Out of
the 219 responses received, the researchers identified 93 respondents who met the screening criterion and had completed the questionnaire.
Hence, those 93 responses that were received
from academicians who currently or had recently
taught one or more sales related courses were
included in the analysis conducted here. Approximately 66% of these respondents had
taught courses in professional selling, about 60%
had taught sales management, and roughly 37%
of the respondents had taught both professional
selling and sales management courses. Most of
these respondents (approximately 81%) had professional selling experience and about 40% had
27
prior sales management experience.
As was true in the case of marketing academicians, the researchers were primarily interested in
the responses of those sales managers who currently or had in the recent past (i.e., in the last
two years) managed a sales force. Accordingly a
screening question was included in the paper and
pencil questionnaire to ensure that only responses that met the researchers’ criterion were
included for analysis. Survey instruments were
mailed to a national random sample of 1500
sales managers taken from the subscription list
of a nationally distributed sales magazine. A total
of 203 questionnaires were received; 168 from
managers who met the screening criterion and
35 from sales managers who did not. A total of
55 questionnaires were returned as being nondeliverable, thus resulting in a response rate of
approximately 14%. The early and late respondent comparison procedure (see Armstrong &
Overton, 1977) indicated no non-response bias.
On average, the sales managers who met the
screening criterion had approximately 15.6 years
of experience as professional sales people and
8.16 years of experience as sales managers. Approximately 30% of these respondents managed
consumer goods sales forces while the remaining
70% were employed in the industrial goods sector. A vast majority of the sales managers
(approximately 80%) had either a college or
graduate school degree.
ANALYSIS AND RESULTS
The two sets of data containing 93 responses
from academicians and 168 responses from sales
managers, respectively, were merged to facilitate
analysis. The data were subjected to chi-square
and t-test procedures in order to evaluate the
research questions this study posed.
The first research question this study sought to
explore dealt with evaluating potential perceptual
differences between sales educators and sales
managers as regards the format these two groups
deemed as most effective in meeting the needs
of students who desired a career in sales. A total
Vol. 6, No. 1
28 Journal of Selling & Major Account Management
TABLE 1
TABLE 2
Comparing the perspectives of sales managers and
academicians on the most preferred teaching
format of sales related courses for students
seeking a career in sales
Comparing the perspectives of sales managers and
academicians on the most preferred teaching
format of sales related courses for students seeking
a career in sales:
Identifying Differences
Participant Responses
Teaching Format
Selected
One or more courses in
professional selling, no
courses in sales
management
One or more courses in
sales management, no
courses in professional
selling management
Sales
Educator
Sales
Manager
n = 93
n = 168
5 (5.4%)
19 (11.4%)
2 (1.2%)
At least one professional
selling and at least one sales
management course
71 (76.3%)
89 (53.3%)
One course that combines
both professional selling
and sales management
16 (17.2%)
40 (24%)
College/University courses
do not meet the needs of
students pursuing a career
in sales
1 (1.1%)
17 (10.2%)
Chi-Square = 17.017; p
= .002
NOTE: Two cells have very low counts, one cell has no
count, hence the chi-square value should be interpreted with
caution.
of four teaching formats commonly used by
business schools (i.e., one or more personal selling course and one or more sales management
course, one personal selling course only, one
sales management course only, a combined personal selling and sales management course) were
identified. Data obtained from sales managers
were evaluated initially to determine if the education levels of sales managers was in anyway related to the teaching formats they preferred; no
statistically significant differences could be identified. The researchers subsequently merged
these data with those obtained from sales educators and subjected the merged data set to Chisquare analysis. Table 1 presents the results of
this analysis. Although the Chi-square is statistiNorthern Illinois University
Teaching Format Selected
One or more courses in
professional selling, no
courses in sales management
One or more courses in
sales management, no
courses in sales
management*
At least one professional
selling and at least one sales
management course
One course that combines
both professional selling and
sales management
College/University courses
do not meet the needs of
students pursuing a career in
sales**
ChiSquare
P-value
2.567
.109
13.779
.000
1.550
.213
7.625
.006
NOTE: (*) One of the format options, i.e., could not be
evaluated because one cell has no count.
(**) Chi-square value should be interpreted with caution as
one cell has very low count.
cally significant (χ2 = 17.017; p = .002) suggesting that sales managers and sales educators differ
as regards the format they perceive to be the
most beneficial for teaching sales related courses,
the presence of very low counts in some cells
and no count in one cell (see Table 1) makes any
interpretation suspect. Consequently, a series of
Chi-square tests were performed to more appropriately identify specific formats, if any, where
the two groups had differing perceptions (see
Table 2).
Table 2 reports a statistically significant Chisquare (χ2= 13.779; p = .000) against the format
which entails teaching at least one or more
courses in personal selling and at least one or
more courses in sales management. Taken to-
Winter 2006
29
were no differences between sales managers and
sales educators as regards their perceptions
about the usefulness of other formats used in
universities to teach sales related courses. Overall, then the results of Chi-Square analysis reveal
that both sales managers and sales educators
largely agree that offering (a) only a professional
selling course, (b) only a sales management
course, or even (c) a course that combines both
professional selling and sales management are
not appropriate formats for delivering sales related education. In order to answer the second
research question which asked if sales educators
and sales managers had different perceptions
regarding the contribution of professional selling
courses in developing professional selling skills
in students, a series of independent samples ttests were conducted. The results of these tests
are presented in Table 3. The mean scores of the
responses of both sales educators and sales managers to the various items listed in Table 3 indicates that on average, both these groups agree
that professional selling courses in universities
gether with the information Table 1 presents,
this indicates that among the individuals who
responded to the survey questions, a greater proportion of sales educators as compared to sales
managers feel that this format best meets the
needs of students seeking a sales career. Notwithstanding this statistically significant finding,
it is worth noting that a majority of both sales
managers (53.3%) and sales educators (76.3%)
preferred this teaching format to any other format included in the survey instruments.
The information reported in Tables 1 and 2 also
indicates that a greater proportion of sales managers, as compared to sales educators, feel that
college/university sales related courses do not
meet the needs of students intending to pursue a
career in sales (χ2= 17.625; p = .006).
However, this statistical difference has to be
tempered in light of a very low count in one of
the cells. Chi-square tests involving the other
formats were not statistically significant, indicating that for the responding individuals, there
TABLE 3
Results of t-tests evaluating potential differences between sales educators and sales managers with regard to
the contribution of professional selling courses
Survey Question: If all entry level sales people (no
prior sales experience) are compared, those salespeople
who completed at least one personal selling course are
likely to...
Sales Educator
Sales Manager
n = 93
n = 168
Mean
Mean
Difference
t-value
3.73
4.17
3.23
3.47
.50
.70
4.011*
6.433*
4.16
3.51
.65
5.852*
4.25
3.80
.45
4.152*
... be better prepared to deal with client objections
4.23
3.44
.79
6.663*
... be better prepared to close a sale
4.19
3.32
.88
6.920*
4.15
3.57
.59
4.829*
4.31
3.39
.92
9.148*
3.98
3.32
.66
5.049*
4.44
3.63
.81
8.586*
3.96
3.29
.67
5.329*
... possess superior oral communication skills
... be better prepared to prospect for new clients
... be better prepared to effectively qualify new
prospects
... make more effective sales presentations
... be better prepared for success in a professional
selling career
... better appreciate the importance of providing after
sales service
... be more effective listeners
... better recognize the importance of understanding
customer needs in professional selling
... be better prepared to deal with ethical dilemmas in
selling situations
NOTE: (*) indicates that the t statistic is significant at p = .00 (2-tailed)
Vol. 6, No. 1
30 Journal of Selling & Major Account Management
effective sales presentations (t = 4.25, p = .00),
dealing with client objections (t = 4.23, p = .00),
and closing a sale (t = 4.19, p = .00), (c) better
preparing an individual for a successful career in
sales (t = 4.15, p = .00), (d) fostering in individuals a better appreciation of the importance of
providing after sales service (t = 4.31, p = .00),
(e) improving individuals’ listening skills (t =
3.98, p = .00), (f) helping individuals better recognize the importance of customer needs in professional selling (t = 4.44, p = .00), and (f) preparing individuals to better deal with ethical dilemmas in selling situations (t = 3.96, p = .00).
provide and improve an entry level salesperson’s
selling skills. The proportion of sales managers
that indicated an agreement (either agree or
strongly agree) with the eleven items listed in
Table 3 ranged between 46% and 73%, while the
proportion of sales educators indicating agreement with these items ranged between 75% and
78%.
For all the eleven items included in the study to
address the abovementioned research question,
however, the t-values indicated that the differences between the perceptions of sales educators
and sales managers were statistically significant
(see Table 3). More specifically, Table 3 reports
that the sampled sales educators perceived more
favorably than did the sampled sales managers
the contribution of professional selling courses
in (a) developing superior communication skills
in individuals (t = 4.011, p = .00), (b) preparing
individuals to prospect for new clients (t = 4.17,
p = .00), teaching individuals how to effectively
qualify new prospects (t = 4.16, p = .00), making
Table 4 presents the results of independent samples t-tests conducted to evaluate the third research question that was of interest in this study.
Similar in tone to the second research question,
this question sought to explore whether sales
educators and sales managers differed in their
perceptions as regards the contributions that
sales management courses taught in universities
and colleges made in developing sales manage-
TABLE 4
Results of t-tests evaluating potential differences between sales educators and sales managers with regard to
the contribution of sales management courses
Survey Question: If all entry level sales managers (no
previous sales management experience) are compared,
those sales managers who completed at least one sales
management course in college are likely to ...I
Sales Educator
Sales Manager
n = 93
n = 168
Mean
Mean
Difference
t-value
... be better at developing sales forecasts
3.92
3.46
.46
3.693*
... be better prepared to develop equitable sales quotas
4.01
3.27
.74
6.378*
... be better prepared to make the transition into sales
management
4.20
3.57
.63
5.564*
... be better prepared to make appropriate hiring
decisions
3.91
2.94
.97
7.889*
... be better at analyzing sales force performance
4.10
3.32
.78
6.795*
... be better prepared to determine territory allocations
3.95
3.07
.87
7.088*
4.01
3.10
.91
7.520*
4.00
3.29
.71
5.916*
... be better prepared to make salesforce compensation
decisions
... be better prepared to handle ethical dilemmas
involving salespeople
NOTE: (*) indicates that the t statistic is significant at p = .00 (2-tailed)
Northern Illinois University
Winter 2006
31
forecasts (t = 3.693, p = .00), (b) allocate equitable sales quotas (t = 6.378, p = .00), (c) make a
transition into sales management (t = 5.564, p
= .00), (d) make appropriate hiring decisions (t =
7.889, p = .00), (e) analyze sales force performance (t = 6.795, p = .00), (f) determine territory
allocations (t = 7.088, p = .00), (g) make sales
force compensation decisions (t = 7.520, p
= .00), and (h) handle ethical dilemmas involving
salespeople (t = 5.916, p = .00). Descriptive
analysis also suggested that the perceptual differences between sales educators and sales managers were greater in case of sales management
courses than they were in case of professional
selling courses.
ment skills in students. As indicated by the average response scores of the sampled sales managers and sales educators to the eight statements
listed in Table 4, both these groups on average
agreed that sales management courses at universities did indeed build sales management skills in
students. Preliminary descriptive analysis revealed that between 40% and 63% of responding
sales managers tended to agree with the statements listed in Table 4, whereas an overwhelming majority of sales educators (85% - 90%)
agreed with such statements.
For all the eight items listed in Table 4, t-values
indicated that the responding sales educators and
sales managers differed in their perceptions. Specifically, sales educators believed to a greater extent than did sales managers that, as compared
to other individuals, students who took sales
management courses currently offered in universities were better equipped to (a) develop sales
The last research question this study sought to
answer related closely to the previous two questions evaluated above. Specifically, the fourth
research question was formulated to evaluate the
extent to which sales educators and sales manag-
TABLE 5
Results of t-tests evaluating potential differences between sales educators and sales managers with regard to
impact of sales related courses on students’ preparation for a sales related career
Sales Educator
Sales Manager
n = 93
n = 168
Mean
Mean
Difference
t-value
It is important for entry level salespeople (no prior
sales experience) to have completed a professional
selling course while in college
4.00
3.51
.49
3.300*
It is important for entry level salespeople to have
completed a sales management course while in college
3.44
3.08
.36
2.342**
It is important for entry level salespeople to have a
business degree from a well respected college or
university
3.27
2.71
.56
3.633*
Sales courses at universities prepare graduates
adequately for a professional selling career
3.30
2.45
.85
6.307*
Sales management courses at universities prepare
graduates adequately for a sales management career
2.96
2.55
.41
2.956*
After completing a professional selling course, a
graduate is better prepared for a career in sales
4.52
3.66
.86
7.506*
After completing a sales management course, a
graduate is better prepared for a career in sales
management
4.24
3.43
.80
6.754*
Items
NOTE: (*) indicates that the t statistic is significant at p = .00 (2-tailed); (**) indicates that the t statistic is significant at p = .02 (2tailed)
Vol. 6, No. 1
32 Journal of Selling & Major Account Management
ers perceived that sales related courses taught
currently at universities were important, relevant,
and adequately prepared students to enter sales
related careers. A series of independent samples
t-tests were conducted to evaluate the seven
statements that addressed this research question
(see Table 5). For this set of statements, like the
previously examined items, sales educators and
sales managers differed in their perceptions. Specifically, the responding sales educators believed
to a greater extent than did sales managers that it
was important for entry level salespeople to have
completed professional selling (t = 3.300, p
= .00) and sales management courses (t = 2.342,
p = .00). Further, sales educators, as compared
to sales managers, thought that it was more important for an entry level salesperson to have a
business degree (t = 3.633, p = .00). In addition,
sales educators felt to a greater extent than did
sales managers that sales courses and sales management courses prepared graduates adequately
for professional selling (t = 6.307, p = .00) and
sales management careers (t = 2.956, p = .00).
Finally, sales educators agreed to a greater extent
than did sales manager that after completing professional selling and sales management courses, a
graduate was better prepared for a career in sales
and sales management respectively (t-values were
7.506 and 6.754 for these two statements, see
Table 5).
Descriptive analysis of the responses of sales
educators and sales managers to this set of seven
items yielded some interesting insights. As is evident from mean response scores of sales educators and sales managers to these items in Table
5, both these groups agreed in general that professional selling and sales management courses
were relevant for entry level salespeople, and
that completion of these courses better prepared
a graduate for sales and sales management careers. However, these two groups had different
opinions regarding the adequacy of sales and
sales management courses currently being offered at universities. While 50% of sales educators believed that sales courses adequately prepared students for sales careers (mean score =
Northern Illinois University
3.30), only 17% of sales managers held this belief
(mean = 2.45). Further, approximately 37% of
sales educators felt that sales management
courses being offered in universities adequately
prepared students for a career in sales management (mean score = 2.96) whereas only 24% of
sales managers agreed with this statement (mean
score = 2.55).
The potential implications of the findings reported against the four research questions that
were evaluated in the above paragraphs are discussed next.
DISCUSSION AND IMPLICATIONS
Of the four teaching formats that were evaluated
in this study, both sales managers and sales educators who responded to the survey instruments
largely preferred a university curriculum that incorporated at least one or more courses in professional selling and at least one or more courses
in sales management. This agreement indicates
that marketers of sales education (i.e., the academicians) as well as the final consumers of this
education (i.e., the sales managers) have similar
views regarding which of the included formats
best meets the needs of students seeking a career
in sales. A direct implication that flows from this
finding is that universities with curriculums that
incorporate any of the other formats mentioned
in this study would be more responsive to market needs if they revisited their curriculums and
considered the possibility of offering both professional selling and sales management courses
to students majoring in marketing. An extension
of this implication is the proposition that more
universities should investigate the feasibility of
offering relevant and comprehensive sales programs, similar to those provided by sales centers
that have been formed at some universities.
Given the importance of sales and sales management to a marketing student’s career, it may be
worthwhile for universities to add more sales
related courses to their curriculum, and thereby,
better meet the needs of hiring organizations
that are looking for entry-level salespeople (and
sales managers) as well as students that want a
Winter 2006
sales related career.
Although there was general agreement regarding
the most preferred format, sales educators
viewed the abovementioned format more favorably (76.3%) than did sales managers (53.3%).
This difference is especially relevant in light of
the finding that approximately 10% of the responding sales managers felt that none of the
teaching formats currently adopted by most universities met the needs of students seeking a career in sales and/or sales management. These
two findings taken together, when generalized
across the populations of sales educators and
sales managers, reveal that from the perspective
of sales managers, the current curriculums at
most universities may not be adequate when it
comes to delivering sales related courses.
So what should an adequate curriculum comprise? The potential answer to this question becomes complicated, given that in addition to
general skills taught at universities, entry-level
salespeople need and develop industry-specific
and firm-specific sales related skills only after
they join a sales organization through in-house
and on-the-job training. However, as suppliers
of sales related education, some of the steps we
can take include (a) a more adequately assessment of the needs of organizations that hire
graduates for sales positions, (a) development of
more practical and comprehensive approaches to
impart sales related skills through offering sales
related courses and seminars that require students opportunities to practice and hone the
skills they learn, (c) establishment of partnerships with firms so that sales education can be
more “real life”, and (d) an investigation of the
feasibility of offering sales related elective
courses that are industry-specific in some circumstances.
Findings that addressed the second and third
research questions revealed that although sales
educators and sales managers largely agreed that
professional selling and sales management
courses contributed to the development of selling and sales management related skills and
33
knowledge, sales educators had more favorable
opinions regarding the usefulness of such
courses currently being taught at universities and
colleges. The good news for academicians delivering sales related education is that the final consumers (i.e., the sales managers) perceive that
such education adds value. However, the difference in perceptions between sales educators and
sales managers reveals that the final consumers
of professional sales education do not perceive
the product (i.e., sales and sales management
knowledge and skills) to provide the same value
as do the marketers of this education. Some possible reasons for this divergence in perceptions
between these two groups are: (1) sales educators
have a biased view of the value they provide, (2)
sales managers have a biased view of the value
they receive, or (3) both groups are somewhat
biased but in opposite directions. Drawing on
the adage that “the customer is always right”, it
seems reasonable to imply that sales educators
need to make an in-depth assessment of the
value they currently provide through sales related
education and attempt to do a better job to increase this value. Such an objective might be
achieved via additional research, utilizing both
qualitative and quantitative methods, including
focus groups, in-depth interviews, and survey
research to gain additional insights and understanding of the skills, knowledge and training
sales managers look for in the sales forces of
today and tomorrow.
Findings pertaining to the last research question
underscore and further refine some of the implications resulting from the evaluation of the first
three research questions. Although both sales
educators and sales managers generally agree as
to the importance and value of sales related education, the marketers of sales education are more
favorably disposed than are final consumers.
More remarkable is the implication that despite
having favorable opinions regarding the usefulness of sales related education, some sales educators and most sales managers believe that currently dispensed sales education may not adequately meet the needs of students seeking sales
Vol. 6, No. 1
34 Journal of Selling & Major Account Management
related careers. This opinion may be based, to an
extent, on the fact that work experiences provide
much needed exposure and training to entry
level salespeople and sales managers, and education delivered in universities cannot duplicate
such exposure. Notwithstanding this fact, this
finding sends an important message to sales educators, i.e., there may be wisdom in revisiting the
content and delivery of sales related education so
that a better and more comprehensive product is
offered to the market. Those universities that
have established sales centers and are providing
in-depth sales training and education may be
ahead of the curve in terms of meeting the current needs of the market.
While sales practitioners and academicians appear to differ on a number of pedagogical issues,
the recent growth of sales centers at universities
may be the best opportunity to bridge the gap
between educators and sales managers. Sales
centers are designed to immerse students into
the field of selling by providing a more in depth
and practical learning environment. For example, sales centers offer multiple courses in selling
and sales management and are designed to foster
long term relationships with enriched practical
learning experiences between students and salespeople through shadowing, mentoring and other
programs. As such programs continue to take
root, then so will the likelihood of an ideological
convergence between how and what sales students learn, and what sales practitioners want
from students. In sum, the success of university
sales centers may be measured not only by the
preparedness of those students trained through
sales centers, but also by the lessening of perceived gaps between sales academicians and sales
practitioners who hire those students.
LIMITATIONS AND FUTURE RSEARCH
The findings of this study and the implications
drawn from those findings shed light on some
important issues concerning the structure, content, and delivery of sales related education in
universities. However, because the response
rates for the sampled sales educators and sales
Northern Illinois University
managers were relatively low, the above-noted
findings should be generalized with caution. A
replication of this study with a better response
rate will increase the generalizability of its findings. Further, although this study sought the
opinions of sales educators and sales managers,
it did not evaluate the perceptions of students,
an important consumer group that directly
“consumes” sales related education. A study that
incorporates the views of students and compares
them to the views of sales educators and sales
managers is likely to yield useful additional insights.
This study was an initial investigation into the
perceptions of sales managers and sales educators regarding current common offerings in sales
related education. Further research is needed to
identify avenues for improving professional selling and sales management education to make it
more relevant and adequate. A specific field of
inquiry in this regard would pertain to obtaining
feedback from important stakeholders (e.g., sales
organizations) regarding their priorities and requirements for entry level salespeople and sales
managers through an in-depth evaluation of requisite professional selling and sales management
skills and knowledge for those entry level employees. Such a study would facilitate better
structured and more comprehensive sales related
courses.
CONCLUSION
This study compared the perceptions of sales
educators and sales managers with regard to the
salience, validity, and usefulness of sales related
courses being currently taught at most universities by seeking to answer four related research
questions. These comparisons between sales
educators as marketers of a product (sales and
sales management knowledge and skills residing
in students) and sales managers as final consumers who hire these students yielded some constructive insights and indicated several areas
where improvements may be in order. Further
research on this topic should help educators better structure and deliver sales related curriculums
Winter 2006
in colleges and universities and improve sales
related education to more appropriately and adequately address the needs of employers.
REFERENCES
Amin, Sammy G., Abdalla F. Hayajneh, and Hudson Nwakanma. 1995. College students’
views of sales jobs as a career: An empirical investigation. American Business Review
13 (2): 54-60.
Anonymous. 2005. America’s 500 largest sales
forces. Selling Power Magazine (October):
58-60.
Armstrong, S. J., and T.S. Overton. 1977. Estimating non-response bias in mail surveys.
Journal of Marketing Research 14 (August):
396-402.
Bailey, Jeffrey J. and Byron Dangerfield. 2000. Applying the distinction between marketoriented and customer-led strategic perspectives to business school strategy. Journal of Education for Business 75 (3): 183-.
Bellenger, Danny N., Kenneth L. Bernhardt, and
Wilbur Wayman. 1974. Student attitudes
toward selling as a career: Implications for
marketing education. In 1974 American
Marketing Association Proceedings, edited by
R. Curhan. 580-84. Chicago: American
Marketing Association.
Bellizzi, Joseph A., and Robert E. Hite. 1985. Expectations of prospective salespeople with
regard to professional selling positions. In
Proceedings of the 1985 Southwestern Marketing
Association Conference, edited by J. Crawford
and B. Garland, 153-58. Southwestern
Marketing Association.
Bristow, Dennis N. 1998. Do you see what I see?
The marketing lens model in an academic
setting. Journal of Marketing for Higher Education 8(4): 1-16.
______ , and Douglas Amyx. 1999. Consumer
primacy on campus: A look at the perceptions of Navajo and Anglo consumers.
Journal of Non-Profit and Public Sector Marketing 7(2): 31–51.
_______ , ________ 1998. Do you see what I
see? A cross-cultural investigation of consumer perceceptions of the educational
35
product. Journal of International Consumer
Marketing 10(3): 3-20.
_______, and Jo Ann Asquith 1999. What’s in a
name? An intra-cultural investigation of
Hispanic and Anglo consumer preferences and importance of brand name.
Journal of Product and Brand Management 8(3):
185-203.
_______ , Rajesh Gulati, Douglas Amyx, and Jennifer Slack. (forthcoming). Do you see
what I see? An empirical look at professional selling from a student perspective.
Journal of Business for Higher Education.
_______ , _______, and _______. (forthcoming).
Do you see what I see? An empirical look
at professional selling from a student perspective: A replication and extension.
Marketing Management Journal.
Dalrymple, Douglas J., William L. Cron, and Thomas E. DeCarlo 2001. Sales Management.
John Wiley and Sons, New York, NY.
Dauner, Jack R. and Eugene Johnson. 1979. Attitudes of college students toward selling:
An exploratory study. Proceedings Southern
Marketing Association, 161-164. Southern
Marketing Association.
DelVecchio, Susan. 2000. An investigation of Afri
can-American perceptions of sales jobs.
Journal of Personal Selling and Sales Management 20 (1): 43-52.
Greek, Dinah. 1997. Delusion in good supply.
Professional Engineering 10, 19: 1.
Donoho, Casey L., Michael J. Swenson, and Garry
R. Taylor. 1995. Journal writing in the
personal selling curriculum. Journal of Mar
keting Education 17 (fall): 5-16.
Dubinsky, Alan J. 1981. Perceptions of the sales
job: How students compare with industrial salespeople. Academy of Marketing Science 9 (4): 352-67.
Futrell, Charles M. 2002. Fundamentals of Selling:
Customers for Life. Irwin McGraw-Hill,
New York, NY.
Harmon, Harry A. 1999. An examination of students’ perceptions of a situationally described career in personal selling. Journal of
Professional Services Marketing 19 (1): 119136.
Vol. 6, No. 1
36 Journal of Selling & Major Account Management
Heckman, James. 1998. Internet, sales focus to
affect higher ed. Marketing News
(December 7): 9.
Ingram, Tom and Buddy LaForge. 1992. Agenda
for improving personal selling and sales
management research. Journal of Personal Selling & Sales Management 12
(fall): 7-8.
Lagace, Rosemary R., and Timothy A. Longfellow.
1989. The impact of classroom style on
student attitudes toward sales careers: A
comparative approach. Journal of marketing
Education 11 (summer): 72-77.
Lamont, Lawrence M. and Ken Friedman. 1997.
Meeting the callenges of undergraduate
marketing education. Journal of Marketing
Education 19 (fall): 17-30.
Lollar, James G. and Thomas W. Leigh. 1995. An
experiential exercise for enlightening sales
students about the screening and selection
process for sales jobs. Journal of Marketing
Education 17 (fall): 35-50.
Lysonski, Steven, and Srinivas Durvasula. 1998. A
cross-national investigation of student
attitudes toward personal selling: implications for marketing education. Journal of
Marketing Education 20 (August): 161-173.
Macintosh, Gerrard. 1995. Using negotiations to
teach relational selling and group dy
namics. Journal of Marketing Education 17
(fall): 63-72.
Marshall, Greg W. and Ronald E. Michaels. 2001.
Research in selling and sales management in the next millennium: An
agenda from
the AMA faculty consortium. Journal of Personal Selling & Sales
Management 21 (winter): 15-17.
McNeilly, Kevin M. and Frances J. Ranney. 1995.
Improving writing skills in sales management courses: The use of memo-writing
exercises. Journal of Marketing Education 17
(fall): 17-24.
______ and Frances J. Ranney. 1998. Combining
writing and electronic media in sales management courses. Journal of Marketing
Education 20 (fall): 226-235.
Milner, Laura M. 1995. Telemarketing for the business school as a sales course project. JourNorthern Illinois University
nal of Marketing Education 17 (fall): 73-80.
Muehling, Darrel D., and William A. Weeks. 1988.
Women’s perceptions of personal selling:
Some positive results. Journal of Personal
Selling and Sales Management 8 (May): 11-20.
Pharr, Steven and Linda Morris. 1997. The fourthgeneration marketing curriculum: Meeting
AACSB guidelines. Journal of Marketing
Education 19 (fall): 31-43.
Ryals, Lynette J. and Beth Rogers. 2006. Holding
up the mirror: The impact of strategic
procurement practices on account management. Business Horizons 49, 1 (JanuaryFebruary): 41-50.
Swenson, Michael J., William Swinyard, Frederick
Langrehr, and Scott Smith. 1993. The appeal of personal selling as a career: A decade later. Journal of Personal Selling and Sales
Management 13 (1): 51-64.
Tanner Jr., John F. and Stephen B. Castleberry.
1995. Professional selling and relationship
marketing: Moving from transactional
role-playing to partnering. Journal of Marketing Education 17 (fall): 51-62.
Turnbull, Peter, David Ford and Malcolm Cunningham. 1996. The Journal of Business
and Industrial Marketing 11 (3/4): 44-62.
Weilbaker, Dan C. (2001), “Why a Career in
Sales,” in Careers in Professional Selling.
Center for Professional Selling, Hankamer
School of Business, Baylor University,
Waco, Texas, pp. 4-5.
Weitz, Barton A., Stephen B. Castleberry, and
John F. Tanner, Jr. 2002. Selling: Building
Relationships. Irwin-McGraw Hill, New
York, NY.
Winter 2006
37
Rajesh Gulati is an Associate Professor of
Marketing in the G.R. Herberger College of Business
at St. Cloud State University. He completed his MBA
in Marketing in 1986. He received his Ph.D. in
Marketing from University of North Texas in 1999.
rgulati@stcloudstate.edu
Dennis N. Bristow is a Distinguished Professor of
Marketing and the Associate Dean, G.R. Herberger
College of Business, at St. Cloud State University. He
received his B.S. degree in Psychology in 1989, and
M.A. in Industrial/Organizational Psychology in
1991.
He received his Ph.D. in Business
Administration and Marketing from Oklahoma State
University in 1995. He works in the areas of
consumer behavior, cross-cultural marketing, and
personal marketing. dbristow@stcloudstate.edu
Douglas A. Amyx is an Assistant Professor of
Marketing, Department of Management and
Marketing, at Louisiana Tech University. He
received his B.B.A. degree in Marketing in 1986, and
M.B.A. in Marketing in 1990. He received his
Ph.D. in Business Administration and Marketing
from Oklahoma State University in 1995. His work
is in the areas of consumer behavior, cross-cultural
marketing, and health care marketing.
damyx@cab.tech.edu
Vol. 6, No. 1
38 Journal of Selling & Major Account Management
An Analysis of the Effects of Sales Force Automation on
Salesperson Perceptions of Performance
By James E. Stoddard, Stephen W. Clopton, and Ramon A. Avila
Investments in sales force automation (SFA) are huge, yet the effects of SFA on salesperson performance are not well
established. This study investigates SFA’s effect on salesperson performance through its effect on two intervening variables: account management outcomes and sales process effectiveness. Sales force automation comprehensiveness of
use was found to positively influence salespeople’s account management and sales process effectiveness, leading to an
increased ability to work smarter while making work effort more efficient. In turn, improved account management and
sales process effectiveness resulting from the use of SFA led to increased job performance and job satisfaction. Results
suggest that sales managers should focus on adopting technologies that improve sales people’s account management
abilities such as those that support pricing and order placement, and technologies that help sales people to handle more
accounts and enhance their ability to assess their customer’s needs. Additional focus should be on technologies that
have the capability to analyze reasons for won and lost opportunities and provide the communications capabilities to
enhance teamwork with other people in the sales organization.
U.S. Companies have invested over $3 trillion
dollars into information technology (i.e.,
computer hardware and software and
telecommunications equipment) in the last
twenty years (Stiroh 2002).
Customer
relationship management (CRM) technology is
an important form of IT that assists sales
organizations in managing sales processes with
the objective of developing and maintaining
long-term customer relationships (Ingram,
LaForge, and Leigh, 2002). Worldwide, the
CRM industry is forecasted to reach $45.5 billion
in 2006, a compound annual growth rate of 18.6
percent. The U.S. CRM market is expected to
exceed $18 billion that same year (McCausland
2002). Sales force automation (SFA) is the most
widely used subset of customer relationship
management technology. Sales force automation
(SFA) is broadly defined as the conversion of
manual sales activities into electronic processes
via the use of software and/or hardware (Rivers
and Dart 1999).
These rapidly emerging
technologies are having a major impact on the
nature of the sales job. For example, one
computer software company was able to show
their sales force that three complaints (or
problems) in less than six months typically lead
to a lost customer. This directly led to lost
Northern Illinois University
commissions for the salesperson. Their sales
force automation software was set so that after
two complaints from an account, the salesperson
was alerted about the unhappy account. The
salesperson could then be proactive and take
care of the problems. This system reduced lost
accounts by 53% during the first year.
The potential benefits deriving from SFA are
many. As the example above highlights, SFA
can be an important tool for managing account
relationships, and improving customer retention
and overall sales performance. The possibility of
increasing customer retention is important, since
the cost of finding new customers is estimated to
be five times the cost of keeping existing
customers (Kotler 1997), and a customer’s
lifetime value (the net present value of the future
stream of profits from an individual customer)
increases markedly with customer retention
(Peppers and Rogers, 1997).
Evidence in the business press also indicates that
a sales force’s use of SFA can facilitate
communication with sales people, reduce manual
error rates, enhance time and territory
management (e.g., a reduction in time preparing
for customer presentations and follow-up when
more information is requested), give sales people
39
Winter 2006
faster access to timely information, and provide
enhanced customer service (e.g., Lorge 1999,
Orenstein and Leung 1997, Gentilcore 1996,
Schottmiller 1996, Hanover 2000, Thetgyi 2000).
However, other research indicates that not all
companies experience positive gains, in part due
to resistance to adopting the technology on the
part of the sales force (Rivers and Dart 1999;
Speier and Venkatesh 2002). The question of
the impact of SFA on sales performance is an
important one. Intuitively, successful adoption
and continued usage ultimately depends on sales
performance gains. Moreover, huge investments
have been, and are being made in SFA, and as
many as 75% of SFA projects fail (Blodgett
1995).
While scholarly research has focused on aspects
of SFA adoption, there has been surprisingly
little academic research focused on explaining
Figure 1
how SFA affects sales performance. In a recent
article (Tanner, Ahearne, Leigh, Mason and
Moncrief 2005), the authors argue that future
research needs to address the mechanisms
through which sales technologies like SFA
influence salesperson performance. The present
study seeks to contribute to our knowledge in
this area by developing and testing a conceptual
model of the effects of SFA on select sales task
outcomes that are viewed as key mechanisms
through which SFA affects salesperson
performance and job satisfaction. The study also
examines SFA-specific measures of working
smarter and harder and salesperson satisfaction
with SFA. The issues addressed should provide
important insights to both managers and sales
researchers regarding the mechanisms though
which SFA usage impacts performance.
Hypothetical SFA Model
Sales
Experience
H7
Task Outcomes
SFA
Training
H2
H2
H1
H4
H4
Account
Management
H8c
H5a
SFA
Comprehensivenes
H5
H1
H3
SFA
Experience
Sales Process
Effectiveness
Working
Smarter – Post
SFA
H8
H6a
H6
H3
SFA
Satisfaction
Working
Harder –
Post SFA
H8
Job
Performance
H9
Job
Satisfaction
Vol. 6, No. 1
40 Journal of Selling & Major Account Management
The Model
The conceptual model is presented in Figure 1.
As the model indicates, a salesperson’s
performance and job satisfaction are posited to
be a function of the salesperson’s ability to work
smarter instead of harder using SFA. In turn,
the ability to work smarter and the salesperson’s
level of work effort are posited to be reliant on
how well the salesperson can accomplish two
key sales tasks associated with the job – account
management and sales process effectiveness,
which depend on their training and experience
with SFA and the comprehensiveness of the
SFA implementation. The model also postulates
that a salesperson’s satisfaction with SFA is
dependent on improvements in account
management and increased sales process
effectiveness. Finally, a salesperson’s ability to
work smarter is anticipated to be related to the
person’s level of sales experience. The following
sections will describe these relationships in
further detail. Since the basic premise of this
research is that SFA’s effect on job performance
is through improved sales task outcomes, we
first discuss the task outcome constructs. Next,
we develop the logic and hypotheses for the
antecedent variables, then the expected
consequences of improved task outcomes.
Sales Task Outcomes
This research proposes that SFA usage affects
sales performance through its ability to enhance
the outcomes of key sales tasks. This is
consistent with recent research calling for studies
that investigate intervening variables in the sales
technology – sales performance relationship
(Tanner et al. 2005).
Walker, Churchill and Ford (1977) developed
one of the first conceptual frameworks to
recognize that sales performance was contingent
on the amount and quality of effort the
salesperson exerted on the various tasks
associated with the job. Weitz (1981) also
emphasized the importance of salesperson tasks
by proposing that salesperson performance was
contingent on how efficiently and effectively
Northern Illinois University
tasks are carried out. Salesperson activities and
behaviors include those tasks required in the
sales process and tasks related to the
development of ongoing relationships with
customers and buyers (Boles, Brashear,
Bellenger, and Barksdale (2000).
Moncrief
(1986) identified over 120 salesperson tasks,
which he empirically associated with selling,
working with orders, servicing the product,
information management, servicing the account,
attending conferences and meetings, training and
recruiting, entertaining, travel, and working with
resellers. Obviously, not all of these tasks are
directly related to sales performance, nor are
they all facilitated by SFA. This research focuses
on a reduced set of tasks that previous research
indicates should be facilitated by SFA and
should relate to improved sales performance.
SFA and Salesperson Tasks
The sales force automation literature suggests
that some salesperson tasks are facilitated by
SFA (Lorge 1999, Orenstein and Leung 1997,
Gentilcore 1996, Schottmiller 1996).
With
respect to information technologies such as SFA,
research suggests that task-technology fit is
important. Task-technology fit is the ability of a
technology to facilitate an individual's job
activities, and is the correspondence between the
job requirements and the functionality of the
technology (e.g., Goodhue and Thompson
1995). This research focuses on those sales job
tasks that the literature indicates and we believe
to be facilitated by SFA (i.e., activities that
should have a high task-technology fit). While
there are potentially many sales tasks facilitated
by SFA, and many different ways to think about
and organize those tasks, our focus is on two
higher-order task outcome constructs we believe
are facilitated by SFA: Account Management and
Sales Process Effectiveness. While SFA can
facilitate internal administrative tasks, time
management, contact management, and the like,
it seems intuitive that ultimately SFA must
improve customer relationships and boost the
effectiveness of the selling process for it to truly
be worthwhile.
Winter 2006
Account Management
The account management construct includes
task outcomes that deal with the salesperson’s
ability to accurately and effectively manage
account relationships.
For example, Lorge (1999) reported that SFA
helps sales reps sell more consultatively by being
better able to assess customer needs. Orenstein
and Leung (1997) found that SFA facilitates
providing the customer with more accurate
pricing information and results in more accurate
ordering processes. Gentilcore (1996) also
reported that SFA assists with order processing.
Schottmiller (1996) reported that SFA enabled
the salesperson to commit fewer costly mistakes
based on incorrect information, and to handle
more accounts, and improve call productivity.
These various issues all represent specific task
outcomes that together constitute improved
account management.
Sales Process Effectiveness
In addition to improved account management,
SFA should also enable salespeople to be more
effective in terms of specific short-term
outcomes of the sales process. For example,
users of SFA appear to be able to do a better job
of analyzing reasons for won and lost account
opportunities (Gentilcore 1996). Schottmiller
(1996) reported that SFA helps salespeople to
improve their closing rates.
A report by
Microsoft Corporation (1998) claims that SFA
usage can lead to improved customer retention
rates. That report also indicates that SFA usage
can facilitate teamwork, a claim also supported
by Gentilcore (1996). Erffmeyer and Johnson
(2001) reported that salespeople in their study
felt that SFA increased their effectiveness, and
that SFA allowed for faster revenue generation.
Dellecave (1996) found that the vast majority of
sales executives surveyed reported that their
companies were generating more revenue
because of sales technologies.
Given the premise that these salesperson task
outcomes are indeed facilitated by SFA, a logical
41
issue would be to determine which antecedent
variables lead to these improved task outcomes,
as well as the effects these improved task
outcomes have on important overall measures
such as salesperson job performance and
satisfaction. The following sections seek to
address these issues.
Antecedents to Salesperson Task Outcomes
Models of salesperson performance (Walker,
Churchill and Ford 1977, Churchill, Ford,
Walker, Johnston, and Tanner 2000, Weitz,
Sujan and Sujan 1986) posit salesperson
performance to be a function of a salesperson's
personal characteristics as well as organizational
variables. Weitz, Sujan and Sujan's (1986) model
suggests that one factor affecting salesperson
performance consists of the capabilities of the
salesperson, which are a function of the
salesperson's knowledge and information
acquisition skills. Sales force automation should
both enhance salespeople's' knowledge and
increase their ability to acquire timely
information. However, the ability of a sales
force automation system to enhance knowledge
and increase information acquisition should be
contingent on the comprehensiveness of the
SFA components used by the salesperson.
Comprehensiveness of SFA Use
Sales force automation systems can vary from
the simple (e.g., electronic organizers and other
personal information management systems) to
more extensive systems (e.g., computer systems
and software that integrates with corporate
systems). For purposes of this research, sales
force automation comprehensiveness is the
breadth of SFA use, both hardware and
software.
The more comprehensive the
technology use, the more the SFA system may
assist salespeople with their selling tasks. As
more components of a SFA system are
employed by the salesperson the more the
salesperson's tasks should be assisted, since the
technology has a better capability to overcome
inherent human weaknesses such as information
Vol. 6, No. 1
42 Journal of Selling & Major Account Management
processing limitations and bounded rationality
(Simon 1955, 1974).
This increased tasktechnology fit should result in increased
efficiency for the salesperson (DeSanctis and
Poole, 1994).
For example, more
comprehensive use might be expected to help
salespeople complete their selling tasks faster
(e.g., a decreased sales cycle), cheaper (e.g.,
improved order accuracy) or better (e.g., the
ability to better assess customer needs).
Moreover, new tasks (e.g., greater synergy
between inside and outside sales through
improved communication) might be
accomplished that were not previously possible
without a more comprehensive use of the
technology (Erffmeyer and Johnson 2001,
Taylor 1994, Verity 1993), thereby increasing
both information accuracy and ease of
information management.
Finally, more comprehensive sales automation
system use may also increase sales process
effectiveness. For example, Thetgyi (2000)
reported that Dow Chemical closed its sales
offices, cut administration costs by 50%, and
boosted sales force productivity by 32.5% with
reduced order cycle time. Dellecave (1996)
found that SFA increased the efficiency of the
sales force by more than 85 percent for the 300
respondents reporting. In that study, sixty-two
percent of respondents said that their companies
were generating more revenue because of sales
technologies.
ways. Adaptive structuration theory proposes
that salespeople choose which features of a sales
force automation system to use based, in part,
on their degree of knowledge and experience
with the technology (e.g., DeSanctis and Poole
1994). As salespeople spend more time training
and using their sales force automation systems,
they should become more proficient with the
system, and have a better understanding of the
benefits and pitfalls of the system. Therefore,
salespeople that are better trained and more
experienced with SFA should be more skillful
with its use, which should result in improved
account management and increased sales process
effectiveness.
Previous sales technology research shows a
positive relationship between company training
and SFA use (Jones, Sundaram and Chin 2002).
Evidence to support the positive value of
experience comes from Czaja and Sharit (1993)
who found that computer experience was
negatively related to the time it took to perform
data entry, file modification, and inventory
management tasks. They also found that more
computer experience resulted in fewer data entry
and inventory management errors. Research
also suggests that lack of adequate training is one
factor related to negative SFA outcomes
(Erffmeyer and Johnson 2001). Therefore, the
expectation is:
H2:
Therefore, the first hypothesis is:
H1:
Increased sales force automation
comprehensiveness of use improves
a salesperson’s
a.
b.
account management.
sales process effectiveness.
Training and Experience With SFA
Any given information technology, such as sales
force automation, can be thought of as a set of
capabilities.
These capabilities can be
implemented by salespeople in many different
Northern Illinois University
Increased salesperson training in
sales force automation should
result in improved
a.
b.
H3:
account management.
sales process effectiveness.
Increased salesperson experience
with sales force automation
should result in improved
a.
b.
account management.
sales process effectiveness.
43
Winter 2006
Consequences of Improved Salesperson
Task Outcomes
Sales Task Outcomes and SFA Satisfaction
Improved account management and sales
process effectiveness are expected to be related
to the salesperson’s satisfaction with SFA.
Consistent with models of technology
acceptance and use (e.g., Davis 1989, Venkatesh,
Morris, Davis, and Davis 2003), it logically
follows that this improvement in task
accomplishment should result in higher levels of
satisfaction with the SFA system.
H4:
selling. The purported benefits of SFA also
should increase the efficiency of the
salesperson’s time use. Thus, for any given level
of task accomplishment, the time required for
effective task completion should be reduced.
Dellacave (1996) found that about 80 percent of
the sales professionals surveyed reported that
technology was making their jobs easier; and
more than 90 percent expected technology to
make their jobs easier in the future.
H5:
Increased salesperson satisfaction
with SFA should result from
improved
a.
b.
account management.
sales process effectiveness.
Sales Task Outcomes and Post-SFA
Working Smarter and Harder
Better task outcomes are proposed to have a
positive impact on the salesperson’s ability to
work smarter while simultaneously reducing their
necessity to work harder as a result of SFA use.
As Weitz (1981) has proposed, working smarter
is the altering of sales behaviors based on
differences between selling situations. Following
Sujan, Weitz, and Kumar (1994), working smart
is defined as behaviors directed toward
developing knowledge about sales situations and
utilizing this knowledge in sales presentations.
A salesperson's use of “smart-selling” has been
postulated to be related to its associated benefits
and costs. The benefits of smart-selling behavior
accrue through large potential orders or when
information gained to engage in smart-selling
can be used in future sales interactions. The
costs of smart-selling primarily stem from the
cost of information collection (e.g., market
research on the customer), which should be
facilitated by more comprehensive use of SFA.
Finally, a salesperson’s information acquisition
skills (which may be enhanced through SFA)
should facilitate their ability to practice smart-
A salesperson’s ability to work
smarter is positively related to
improved
a.
b.
H6:
account management.
sales process effectiveness.
A salesperson's reduced necessity to
work harder should result from
improved
a.
b.
account management.
sales process effectiveness.
Sales Experience and Smart Selling
A salesperson’s overall job experience is
expected to affect his/her ability to work
smarter. As Szymanski (1988) points out,
salespeople must process much information to
sell effectively. To aid in the processing of this
information, salespeople rely on selling
categories stored in long-term memory.
Associated with these categories are attributes or
characteristics of the category. Salespeople can
then use these attributes to classify customers in
order to quickly identify their requirements.
Accordingly, experienced salespeople might be
expected to have (1) developed a greater number
of selling-related categories and (2) learned the
attributes that describe sales categories to a
greater extent than their less experienced
counterparts. As a result, salespeople with more
experience may have a higher propensity to
correctly classify a selling situation and then use
the correct selling strategy for that selling
situation. Therefore,
Vol. 6, No. 1
44 Journal of Selling & Major Account Management
H7:
Increased sales experience should
result in an increased ability to
work smarter.
Sales Performance, Smart Selling, Working
Harder, and SFA Satisfaction
In a series of studies including over 2000
salespeople and incorporating over 200
companies, Weitz Sujan, and Sujan (1986) have
found that salespeople's performance is more
strongly related to what they do rather than to
how hard they work. Salespeople with a greater
ability to engage in smart-selling should execute
sales presentations that are more effective and
persuasive, resulting in increased sales
performance (Boorom, Goolsby and Ramsey,
1998). Spiro and Weitz (1990) found that smartselling was positively related to salespeople’s selfassessment of performance. Sujan, Weitz and
Kumar (1994) found that smart-selling led to
increased sales performance. Finally, Boorom,
Goolsby and Ramsey (1998) found that smartselling was positively associated with percent of
quota achieved. While previous research has
found that both selling smarter and selling
harder are positively related to increased sales
performance (Sujan, Weitz and Kumar 1994),
much of the focus of this stream of research is
on the trade-off between working harder or
working smarter, with working smarter the more
efficient choice.
As hypothesized above
(H6a&b), SFA usage that improves account
management and sales process effectiveness will
cause salespeople to feel less need to work
harder. In the context of SFA usage, we
postulate a negative relationship between job
performance and working harder. In other
words, through SFA use, salespeople will more
efficiently generate a given level of job
performance, i.e., they will generate better
performance for a given level effort.
H8a:
H8b:
Working smarter is positively related
to sales performance.
Required job effort is negatively
related to sales performance.
Northern Illinois University
Based on the same logic as hypothesis 4 above
and based on models of technology acceptance
and use (e.g., Davis 1989, Venkatesh, Morris,
Davis, and Davis 2003), it logically follows that
the ability to work smarter through SFA should
have a positive effect on salespeople’s reported
satisfaction with SFA.
Therefore, it is
hypothesized that
H8c:
Working smarter leads to increased
levels of salesperson satisfaction
with SFA.
Job Satisfaction
The logic behind the notion that a salesperson’s
Table 1
Descriptive Statistics of Salespeople Included
in the Sample
Descriptor
Mean
N
(Percent)
11.10 years
91 (100%)
Sales
Experience
Age
36.64 years
91 (100%)
Education
High School
Some College
Bachelor's
Degree
Some Graduate
Graduate
Degree
3 (3.3%)
11 (12.1%)
66 (72.5%)
Mining
Health Care
Manufacturing
Wholesale Trade
Transportation
Retail Trade
Information
Finance and
Insurance
Real Estate
Professional
Services
Other Services
1 (1.1%)
12 (13.2%)
24 (26.4%)
7 (7.7%)
1 (1.1%)
2 (2.2%)
2 (2.2%)
27 (29.7%)
Industry
6 (6.6%)
5 (5.5%)
1 (1.1%)
12 (13.2%)
2 (2.2%)
Winter 2006
job performance leads to satisfaction with the
job is that the salesperson is able to compare
his/her actual job performance with expected
job performance when estimating rewards.
Then the salesperson is able to form positive or
negative feelings based on this discrepancy.
Bagozzi (1980) was the first in marketing to
apply the causal modeling technique to delineate
the positive directional relationship between a
salesperson’s performance and job satisfaction.
This result has been supported by other sales
research (e.g., Behrman and Perreault 1984).
H9:
Salespeople’s performance is
positively
related to their job
satisfaction.
Research Method
These hypothesized relationships were tested on
a cross-sectional sample of salespeople. The
following sections will discuss the questionnaire
and the data collection procedure.
Survey Questionnaire
Questions included in the survey were drawn
from previous studies or developed specifically
for this study. The questionnaire first asked
respondents whether or not they used SFA. If
not, respondents were asked to indicate their
reasons for not using SFA. Users were then
asked to indicate how long they had used SFA,
what type of hardware and software they used,
the degree of training they received, and their
level of satisfaction with SFA. Users were also
asked to evaluate whether certain aspects of their
job (e.g., hours worked, the ways they approach
their customers) had improved as a result of
using SFA.
Additional items queried
respondents as to how helpful SFA has been in
performing the selling function. The following
discussion explains the measures used in the
study.
Measures
Comprehensiveness of SFA use was measured as the
breadth of SFA implementation summing all of
the software and hardware components used by
45
the respondent (see the Appendix).
This
formative measure, adapted from Hunter,
Perreault and Armstrong (1998), consisted of 23
SFA software and hardware tools, for which the
salesperson simply checked those he/she
currently used.
A sales professional’s experience with SFA and
SFA training were assessed via two questions,
one asking how long (years, months) the sales
professional had used SFA., and the other asking
how much training (months, days, hours) s/he
had with SFA.
Account management and sales process effectiveness were
composite measures. These items were measured
by asking respondents to indicate the degree to
which SFA helped them with each sales task
using a seven point Likert scale anchored by
“Very Helpful” (7) and “Not Very Helpful
(1)” (see the Appendix).
Job experience was measured by asking salespeople
directly how long they have been in professional
sales (years and months).
A salesperson’s satisfaction with SFA was
measured with one seven point Likert scale that
read “How satisfied are you with your sales
automation tools?” anchored by “Very
Satisfied” (7) and “Not Very Satisfied” (1).
Salespeople’s ability to work smart and necessity
to work hard were assessed using a scale
developed by Sujan (1986) in which working
smarter consisted of two components: a sales
professional’s adaptations to customers, and
their repertoire of selling techniques. The
working harder components related to
persistence and intensity of selling behavior (see
the Appendix). Both measures tapped the
salesperson’s perceptions that (s)he worked
smarter or less hard after SFA usage than before.
Finally, sales performance was assessed using several
self-report measures. Each of these measures
asked the respondent to compare their
performance after using SFA to their pre-SFA
performance. Seven-point categorical scales
Vol. 6, No. 1
46 Journal of Selling & Major Account Management
first the researchers’ telephone calls alerted the
participants to the survey and allowed them to
answer the managers’ questions. Second, the
issues surrounding SFA are clearly timely and
relevant to both sales managers and salespeople.
were used to measure sales volume increases
(decreases), selling time gained (lost), and
productivity increases (decreases). For example,
on a scale that read “On average what best
describes what happened to your sales volume?”
the mid-point of the sales volume scale was “no
change,” and the end-points were “decreased
more than 20%” and “increased more than
20%.” The ease (difficulty) of the selling job was
measured on a seven point Likert scale where 1
= much more difficult and 7 = much easier (see
the Appendix).
To test for possible non-response bias,
respondents were compared with nonrespondents with respect to company sales
revenue and number of employees. The results
of this comparison suggest no differences
between the two groups on sales revenue (t
= .224, df = 195, p = .823) or on number of
employees (t = .246, df = 197, p = ,806). These
results provide some evidence that non-response
bias was not a concern in this study.
An
analysis of early versus late responders also was
conducted. Two exogenous variables (SFA
comprehensiveness of use and sales experience)
and the task outcome variables were included in
the analysis. No significant differences were
found between early and late responders. These
results provide further support that non-
Data Collection Procedure
The survey was sent to the sales managers of 200
companies in the Midwestern United States. All
200 companies were contacted by telephone and
informed that the survey was on the way and
asked for their cooperation. Each of the
managers was asked to distribute a questionnaire
to one of their salespeople. One hundred and
one salesperson surveys were returned. The
high response rate is attributed to two factors:
Table 2
Confirmatory Factor Analysis Results for Account Management, Sales Process Effectiveness and Job
Performance
Constructs & Indicators
Standardized
Loading
Account Management
Pricing
Placement
Mistakes
More Accounts
Productivity
Assess Cust. Needs
.7126
.7531
.7994
.8819
.8744
.6908
Sales Process
Opportunity
Close Rates
Cust. Retention
Teamwork
Composite
Reliability
.9074
Indicator
Reliability
Error
Variance
.5078
.5672
.6390
.7777
.7646
.4772
.4922
.4384
.3610
.2222
.2354
.5228
.8224
.7090
.8485
.7846
.5722
Job Performance
.5373
.5027
.7199
.6156
.3274
.4973
.2800
.3844
.6726
.8755
.6411
Sales Volume
Selling Time
.6613
.7391
.4373
.5462
.5469
.4466
Productivity
.9171
.8410
.1651
Ease of Job
.8600
.7396
.2523
Northern Illinois University
Variance
Extracted
.6252
Winter 2006
response bias was not a concern.
Analysis
Only 7 salespeople indicated that they did not
use sales force automation. Of those, 4 reported
that the reason for not using SFA was that the
benefits of using SFA were unclear.
Descriptive Statistics
Thirty-one percent of the responding
salespeople reported that they were in the
manufacturing industry, 27% in finance and
insurance, and 12% in health care and social
assistance and professional, scientific, and
technical services respectively.
Structural
Variables
Equations
With
Manifest
The analysis followed a two-step procedure.
First, measurement models were specified for
factors measured by reflective indicators, and
convergent and discriminant validity were then
47
assessed.
Next, the structural model was
estimated to test the hypotheses. The structural
relationships were tested by using structural
equations with manifest variables, where the
manifest variables included single-item measures,
a formative measure, or composites of multiple
measures (MacKenzie, Podsakoff and Ahearne
1998).
Structural equations with manifest
variables was preferred over other approaches
(e.g., latent variables) since one of the measures
used in the study was formative, several of the
other measures were single-item, and the large
number of theoretical constructs compared to
the sample size would make confidence in the
results of a latent variable analysis tenuous
(Behrman and Perreault 1984).
For those constructs having multiple measures,
composite scales were constructed.
For
example, working smarter was a composite of
two items, which were significantly correlated (r
= .571, p < .01). Similarly, working harder was a
composite of two items, which also were
Figure 2
Final SFA Model Standardized Coefficients
and Explained Variance
Task Outcomes
SFA
Training
.3698
SFA
Comprehensiveness
Account Management
R2 = .1368
.4278
.3157
Sales Process
Effectiveness
R2 = .3826
SFA
Experience
SFA
Satisfaction
R2 = .5178
.5019
.2758
.5135
Working
Smarter – Post
SFA R2 = .5407
.3163
-.2425
.4062
Working
Harder –Post
SFA R2 = .212
.3769
Sales
Experience
-.3334
.3706
Job
Performance
R2 = .7381
.3044
Job
Satisfaction
R2 = .0927
Vol. 6, No. 1
48 Journal of Selling & Major Account Management
Table 3
Correlations, Means and Standard Deviations for Variables in the Model
SFA
Comprehen
siveness
SFA
Comprehensi
veness
Account
Management
Sales Process
Effectiveness
SFA
Satisfaction
Working
Smart
Working
Hard
Sales
Experience
Job
Performance
Job
Satisfaction
Mean
Standard
Account
Management
Sales
Process
Effective
ness
SFA
Satisfactio
n
Workin
g
Working
Hard
Smart
Sales
Experienc
e
Job
Job
Performanc
e
Satisfactio
n
.384**
.488**
.554**
.189
.697**
.483**
.440**
.685**
.595**
.619**
-.063
-.316**
-.172
-.136
-.177
-.158
-.157
-.038
.027
-.184
.403**
.421**
.768**1
.572**
.593**
.684**
-.518**
-.228**
.067
.238*
.080
.153
.170
-.181
-.067
.308**
11.39
4.54
3.54
4.2
4.66
4.46
11.10
4.61
5.35
1.31
1.30
1.32
0.80
0.86
8.08
1.02
1.24
1–7
1–7
1–7
1–7
1–7
Years
1–7
1-7
3.51
Deviation
Scale
1 – 23
*p < .05 (two-tailed)
** p< .01 (two-tailed)
The discrininant validity between the account management, sales process effectiveness, and job performance constructs was assessed using the
chi-square difference test and the variance extracted test. In order to establish discriminant validity, the constructs were entered into a series of
confirmatory factory analyses. The first analysis estimated the fit of a model where the three factors were allowed to covary freely. The second,
third and fourth analyses fixed one of the covariances to be 1.0. All analyses suggested that model fit significantly deteriorated when the
covariances were fixed at 1.0 (∆c2 = 64.68, df = 1, p < .001 for account management and sales process effectiveness, ∆c2 = 22.35, df = 1, p
< .001 for account management and sales performance, and ∆c2 = 65.67, df = 1, p < .001 for sales process effectiveness and sales performance)
providing evidence of discriminant validity. The second test involved comparing the variance extracted by the three factors to the correlations
between the three factors. The average variance extracted by account management was .6252 and the average variance extracted for sales
performance was .6411 while the squared correlation between the two factors was .5898. Similarly, the average variance extracted by sales process
effectiveness was .5373 where the squared correlation between sales process effectiveness and sales performance was .3272. The results of these
tests suggest discriminant validity between account management, sales process effectiveness and sales performance.
1
significantly correlated (r = .683, p < .01).
The account management outcomes and sales
process effectiveness measures were subjected to
a confirmatory factor analysis. Results from the
confirmatory factor analysis are presented in
Table 2. The confirmatory factor analysis
substantiated the two factor solution (c2 = 46.49,
df = 34, p = .075, GFI = .9076, CFI = .9743,
NNFI = .9659, NFI = .9124, RMSEA =
0.0676). Convergent validity was established as
Northern Illinois University
all remaining factor loadings were significant (T
> 2.0) (Anderson and Gerbing 1988).
Discriminant validity between the two factors
was established in three ways, through the chisquare difference test (Bagozzi and Phillips
1982), the confidence interval test (Anderson
and Gerbing 1988), and the variance extracted
test (Fornell and Larcker 1981).
Sales performance was measured using a
composite of four measures which asked
Winter 2006
salespeople to compare their productivity, sales
volume, ease of the selling job and amount of
selling time after implementing sales force
automation, compared to before they had sales
force automation.
A confirmatory factor
analysis was conducted to determine the extent
to which these items loaded on a single construct
(c2 = 9.09, df = 2, p = .0106, GFI = .9495, CFI
= .9634, NNFI = .8902, NFI = .9545, RMSEA
= 0.1744) (Table 2). Convergent validity was
established since all factor loadings were
significant (T > 2.0). Composite reliability for
the job performance factor was .8755. The
average percentage of variance extracted by the
factor was 64.11%. The discriminant validity
among the two task outcome constructs and the
sales performance construct is presented in
Table 3.
Finally, SFA comprehensiveness was a formative
composite of the 23 possible SFA software and
hardware tools (Hunter, Perreault and
Armstrong 1998) (please see the Appendix).
Results
Model Fit
The initial model provided a poor fit to the data
(c2 = 94.58, df = 31, p < .001, GFI= .8528, CFI
= .8242, NNFI = .6880, RMSEA = .1518).
Therefore, model modifications were necessary.
Model modification began by first eliminating
non-significant paths up to the point where
model fit significantly deteriorated (i.e., c2 would
have become significantly larger). This resulted
in a more parsimonious model with about the
same explanatory power as the initial conceptual
model. Next, constraints were relaxed between
some factors by adding three paths when
appropriate.
The final model provided a
reasonable fit to the data (c2 = 49.22, df = 36, p
= .14, GFI = .9124, CFI = .9634, NNFI
= .9442, RMSEA = .0706). Figure 2 shows the
significant paths remaining in the modified
model. Table 3 shows the correlations between
the variables in the model.
Since the final model provided a reasonable fit to
49
the data, results for the hypothesis tests are
based on the final model. Several criteria were
used to test the hypotheses. First, the absolute
value of the T-values associated with the path
coefficients had to be greater than 2.0 to be
considered significantly different from zero (p
< .05). Second, the standard errors could not be
abnormally small (i.e., close to zero). Third, the
standardized path coefficients’ absolute values
had to exceed .05. Finally, the amount of
variance of the endogeneous variables explained
by the independent variables (i.e., R2) had to be
relatively large (Hatcher 1994). Overall, the R2
values in Figure 2 indicate that the model did a
good job of explaining the variance in the
endogenous variables.
Hypothesis Tests
H1a and H1b proposed that the
comprehensiveness of use of SFA would be
positively related to salespeople’s account
management and sales process task outcomes.
These hypotheses were supported by the data.
Increased SFA comprehensiveness of use was
found to be related to improved account
management and sales process effectiveness.
H2a and H2b proposed that increased
salesperson training on sales force automation
would be related to improved account
management and sales process effectiveness.
H3a and H3b proposed that increased
experience with sales force automation would be
related to improved account management and
sales process effectiveness task outcomes. These
hypotheses were not supported.
H4a and H4b proposed that a salesperson’s
improved account management and sales
process effectiveness would be related to
increased satisfaction with sales force
automation. While H4a was supported for
account management, H4b was not supported
for sales process effectiveness.
H5a and H5b proposed that a salesperson’s task
outcomes would be positively related to working
smarter. Both improved account management
Vol. 6, No. 1
50 Journal of Selling & Major Account Management
and sales process effectiveness were found to be
positively related to working smarter. Therefore,
the relationships were supported.
H6a and H6b posited that a salesperson's
necessity to work harder – post SFA should be
negatively related to account management and
sales process effectiveness task outcomes. H6a
was supported for account management, but was
not supported for sales process effectiveness
(H6b).
H7 proposed that a salesperson’s sales
experience would be positively related to their
ability to work smarter. This hypothesis was not
supported.
H8a proposed that a salesperson’s ability to
work smarter – post SFA would be positively
related to sales performance. H8b proposed that
a salesperson’s necessity to work harder – post
SFA would be negatively related to sales
performance. Both relationships were supported
by the data.
H8c proposed that working smarter would lead
to a salesperson’s increased satisfaction with
SFA. This hypothesis was supported.
H9, which proposed that a salesperson’s
performance would be positively related to their
job satisfaction, was supported. Salespeople in
this sample reported that increased job
performance led to increased job satisfaction.
Post Hoc Results
As a result of modifying the initial conceptual
model to achieve acceptable model fit, three
significant paths were added. These paths
represent significant relationships between
variables in the model which were not
anticipated in the initial conceptual development,
but which have logical bases for inclusion.
Therefore, they are considered post hoc results.
The first additional path indicates a significant
effect of improved account management on
sales process effectiveness. Our focus was on
the separate effects of these task outcome
Northern Illinois University
measures.
However, in retrospect, this
relationship is logical since improved account
management should be positively related to sales
process effectiveness.
Second, the final model contains a path for the
direct effect of improved account management
on job performance. Initially, we thought that
the effects of SFA comprehensiveness on
performance would only be mediated by a
salesperson’s ability to work smarter with SFA,
however, this additional direct effect makes
sense since a salesperson's improved account
management capabilities should result in
increased job performance.
Last, the final model indicates that sales
experience is positively related to working harder
with SFA. While somewhat surprising on its
face, this path makes sense in the context of
SFA comprehensiveness of use. It is possible
that older, more experienced salespeople worked
harder when integrating automation into their
jobs. Previous work on age differences in the
performance of computer-based work suggests
that age (which was highly correlated with sales
experience in this study) increases the time
necessary to enter data, increases keystroke,
format and data input errors as well as incorrect
solutions (Czaja and Sharit 1993, 1998). This
result is also consistent with Speier and
Venkatesh (2002) who found that older
salespeople had a less positive perception of
SFA’s ease of use.
Discussion and Managerial Implications
The premise of this paper was that sales force
automation improves salesperson performance
by facilitating the accomplishment of key sales
tasks. Indeed, the results from the research
support this contention. Comprehensiveness of
SFA use was found to positively influence
salesperson task outcomes.
Specifically,
increased comprehensiveness of use of SFA
improved salespeople’s ability to manage their
accounts and the effectiveness of their sales
process. These results are consistent with other
Winter 2006
51
research that suggests that increased SFA
utilization (i.e., frequency of SFA use) leads to
increased productivity (Brunjolfsson and Hitt
1996).
typical sales situations and customer types that
they normally encounter, and those that capture
and disseminate company-specific knowledge of
best selling practices for training purposes.
Several sales management implications derive
from these results. First, more comprehensive
SFA systems appear to be preferable to less
comprehensive systems in facilitating account
management and sales process effectiveness.
Sales managers should focus on adopting
technologies that improve sales people’s account
management abilities such as those that support
pricing and order placement, allow for the
reduction of mistakes by providing real time,
correct information, and technologies that help
sales people to handle more accounts and
enhance their ability to assess their customer’s
needs. Sales managers should also concentrate
on adopting technologies that have the capability
to analyze reasons for won and lost
opportunities and provide the communications
capabilities to enhance teamwork with other
people in the sales organization.
Other sales force productivity gains accrue by
providing salespeople quick feedback on how
they are doing on the job, by encouraging
salespeople to analyze their won and lost
opportunities, and enhancing their ability to
manage accounts and the selling process. The
present research results suggest that more
effective sales force automation systems should
have these capabilities.
In addition, sales managers should focus on
adopting technologies that are user friendly.
Assuming that user friendliness of the SFA
system is positively related to number of SFA
features used, user friendliness of the SFA
system may be of paramount importance.
Increased user friendliness should lead to a wider
breadth of SFA use, which in turn, should lead
to improved account management and sales
process effectiveness. A salesperson’s improved
account management and sales process
effectiveness were found to be positively related
to their ability to work smarter. Managerially,
this is an important finding. Working smarter
during their interactions with customers has
been found to be a key factor for increasing sales
force productivity (Sujan, Weitz, and Sujan
1988).
Sales managers should consider
automation approaches that increase a
salesperson's ability to work smarter, such as
those that provide salespeople with timely access
to market research information, those that allow
salespeople to organize information around
Salespeople’s improved account management
ability resulting from the use of SFA was found
to be negatively related to their necessity to work
harder. This implies that SFA systems should
have the capability to enhance the ability of
salespeople to handle more accounts, increasing
the efficiency of the sales organization. This
implication is further bolstered by the finding
that a given level of sales performance could be
achieved with less effort through more
comprehensive SFA usage.
Salespeople’s improved ability to manage their
accounts was also found to be directly related to
increased job performance. This finding is in
line with others’ who contend that salespeople's
performance is more strongly related to what
they do rather than to how hard they work
(Sujan, Weitz, and Sujan 1988).
Finally, salespeople’s increased job performance
led to increased job satisfaction. Overall, the
generally high levels of explained variance found
in this study indicate sales force automation
success among the salespeople in this sample.
Several of the hypotheses were not supported.
For example, it was surprising that two factors,
SFA experience and SFA training were not
found to be related to the task outcome variables
in this study.
The lack of demonstrated
relationships between SFA experience or SFA
training and sales task outcomes in this study
does not suggest that these variables are not
Vol. 6, No. 1
52 Journal of Selling & Major Account Management
important predictors of sales task outcomes
generally. The present research only explored two
composite measures of sales task outcomes.
Therefore, it is plausible that SFA training and
experience could have a positive impact on other
salesperson tasks not included in this study.
This research did not find a relationship between
sales experience and working smarter – post
SFA as initially hypothesized. The increased
ability of salespeople to work smarter as a result of
sales force automation was independent of their job
experience. However, the post hoc results
revealed that more experienced salespeople
reported that they worked harder using SFA.
One explanation of this is that older, more
experienced salespeople must work harder to
integrate automation into their jobs. If this is
true, sales managers must provide these sales
people with extra assistance through enhanced
training on the use of SFA hardware and
software. In addition, SFA user friendliness
becomes even more important for this group of
sales people.
Limitations and Future Research
There are several limitations associated with this
study that suggest avenues for future research.
First, while the sample for the study provides a
picture of the effect of SFA’s
comprehensiveness of use on sales performance
across a broad cross section of firms, the sample
size is relatively small and confined to
respondents from one region of the United
States. However, there is little reason to believe
that the variables and relationships in our model
should be region or industry specific. Moreover,
there is value to looking beyond data collected
within one or a few firms only. While the
limited sample size in this study did not appear
to jeopardize the internal validity of the study's
findings, it does have a negative impact on the
ability of the final model to generalize to larger
populations of salespeople (e.g., MacCallum,
Roznowski, and Necowitz 1992). Thus, any
generalizations should be made with that caveat
in mind. Additional studies will be required to
Northern Illinois University
develop a more thorough understanding of the
performance benefits of SFA.
Second, this study was also confined to singleitem measures of certain variables, and relied on
self-report measures of salespeople’s
perceptions. Future research should focus on
improved measures of SFA, its antecedents, and
its consequences, including sales effectiveness
measures such as actual dollar sales volume
increases.
The focus of this research was on two specific
sales task outcome constructs. Future research
should examine additional task outcome
measures. An alternative approach for future
research might involve changing the focus to the
development of a taxonomy of SFA users based
on task outcome profiles, which could then be
related to select situational and job outcome
measures.
This study is an initial attempt to examine the
relationship of SFA comprehensiveness of use to
sales performance.
As additional studies
investigate SFA issues among salesperson
samples, attention also should be focused on
sales manager’s perceptions of SFA’s impact on
the sales job and on the sales manager’s job.
Moreover, future studies could productively
focus more attention on the potential customer
benefits deriving from SFA. Finally, with
respect to issues of training, comprehensiveness
of use, and sales force satisfaction with SFA,
studies relying on longitudinal panel data would
be a potentially productive approach to
examining the evolutionary aspects of SFA
implementation and usage.
REFERENCES
Anderson, James C. and David W. Gerbing (1988),
"Structural Equation Modeling in Practice:
A Review and Recommended Two-Step
Approach," Psychological Bulletin, 103 (3),
411-423.
Bagozzi, Richard P. (1980), “Performance and
Satisfaction in an Industrial Sales Force:
An Examination of their Antecedents and
Winter 2006
Simultaneity,” Journal of Marketing, 44
(Spring), 65-77.
__________ and Lynn W. Phillips (1982),
"Representing and Testing Organizational
Theories A Holistic Construal,"
Administrative Science Quarterly, 27 (3), 459489.
Behrman, Douglas N. and William D. Perreault, Jr.
(1984), “A Role Stress Model of the
Performance and Satisfaction of Industrial
Salespersons,” Journal of Marketing, 48 (4),
9-21.
Blodgett, Mindy (1995), “Vendor Tries to Simplify
Sales Force Automation, Computer World,
30 (1), 62.
Boles, James, Thomas Brashear, Danny Bellenger,
and Hiram Barksdale, Jr. (2000),
"Relationship Selling Behaviors:
Antecedents and Relationship With
Performance," The Journal of Business and
Industrial Marketing, 15 (2/3), 141- 149.
Boorom, Michael L., Jerry R. Goolsby, and
Rosemary P. Ramsey (1998), “Relational
Communication Traits and Their Effect
on Adaptiveness and Sales Performance,”
Academy of Marketing Science Journal, 26 (1),
16-30.
Brynjolfsson, Erik and Lorin Hitt (1996), "Paradox
Lost? Firm-level Evidence on the Returns
to Information Systems Spending,"
Management Science, 42 (4), 541- 558.
Churchill, Gilbert A., Neil M. Ford, Orville C.
Walker, Jr., Mark W. Johnston, and John
F. Tanner (2000), Sales Force Management,
6th ed., Boston: Irwin McGraw-Hill.
Czaja, Sara J. and Joseph Sharit (1993), “Age
Differences in the Performance of
Computer-Based Work,” Psychology and
Aging, 8 (1), 59-67.
____________ and ____________ (1998), “Age
Differences in Attitudes Toward
Computers,” Journal of Gerontology:
Psychological Sciences, 53B (5), P329-P340.
Davis, Fred D. (1989), “Perceived Usefulness,
Perceived Ease of Use, and User
Acceptance of Information Technology,”
MIS Quarterly, 13, 3, 318-340.
Dellecave, Tom Jr. (1996), "How DoYou Stack
53
Up?" Sales and Marketing Management,
December, 34-36.
DeSanctis, Gerardine and Marshall Scott Poole
(1994), “Capturing Complexity in
Advanced Technology Use: Adaptive
Structuration Theory,” Organization Science,
5 (2), 121-147.
Erffmeyer, Robert C. and Dale A. Johnson (2001),
“An Exploratory Study of sales force
Automation Practices: Expectations and
Realities,” The Journal of Personal Selling
and Sales Management, 21 (2), 167-175.
Fornell, Claes and Larcker, D.F. (1981),
"Evaluating Structural Equation Models
with Unobservable Variables and
Measurement Error," Journal of Marketing
Research, 18, 39-50.
Gentilcore, Anthony (1996), “Sales Force
Automation Comes of Age,” Computing
Canada, 22 (25), M10.
Goodhue, Dale L. and Ronald L. Thompson
(1995), "Task-Technology Fit and
Individual Performance," MIS Quarterly,
19 (2), 213-236.
Hatcher, Larry (1994), A Step by Step Approach to
Using the SAS System for Factor
Analysis
and Structural Equation Modeling, Cary, NC:
SAS Institute Inc.
Hanover, Dan (2000), “Independents Day,” Sales
and Marketing Management, 152 (4), 64-68.
Hunter, Gary K., William D. Perreault, Jr. and
Gary M. Armstrong (1998), “Sales
Technology, Selling Smart, and Sales
Performance in Business Markets,” AMA
Educators’ Proceedings: Enhancing Knowledge
Development in Marketing, vol. 9, 1-2,
Chicago: American Marketing
Association.
Ingram, Thomas N., Raymond W. LaForge, and
Thomas W. Leigh (2002), "Selling in the
New Millennium: A Joint Agenda,"
Industrial Marketing Management, 31, 559567.
Jones, Eli, Suresh Sundaram, and Wynne Chin
(2002), “Factors Leading to Sales Force
Automation Use: A Longitudinal
Analysis,” Journal of Personal Selling & Sales
Management, 22, 3, 145-156.
Vol. 6, No. 1
54 Journal of Selling & Major Account Management
Kotler, Philip (1997), Marketing Management:
Analysis, Planning, Implementation, and
Control, 9th ed., Upper Saddle River, NJ:
Prentice-Hall.
Lorge, Sarah (1999), “A Real-Life SFA Success
Story,” Sales and Marketing
Management, by, 515 (1), 1999.
McCausland, Richard (2002), "CRM: the
Momentum Builds; Customer
Relationship Management Software is
Shaping Up As a Hot Market. Just Ask
Microsoft," Accounting Technology, 18 (5): 36
(5), 1-5.
MacCallum, Robert C., Mary Roznowski, and
Lawrence B. Necowitz (1992), "Model
Specifications in Covariance Structure
Analysis: The Problem of Capitalization
on Chance," Psychological Bulletin, 111 (3),
490-504.
MacKenzie, Scott B., Philip M. Podsakoff, and
Michael Ahearne (1998), "Some Possible
Antecedents and Consequences of InRole and Extra-Role Salesperson
Performance," Journal of Marketing, 62 (3),
87-98.
Microsoft (1998), "Adding Value Through
Customer Management," (online),
Available http://sffaonline.com/sffan2/
case/microsoft61.htm.
Moncrief, William C. III (1986), "Selling Activity
and Sales Position Taxonomies for
Industrial Salesforces," Journal of Marketing
Research, 23 (3), 261-271.
Orenstein, Lon and Kenneth Leung (1997), “The
Do’s and Don’ts of Sales Force
Automation,” Marketing News, 31 (23), 14.
Peppers, Don and Martha Rogers (1997), Enterprise
One to One: Tools for Competing in the
Interactive Age, New York: Currency
Doubleday.
Rivers, L. Mark and Jack Dart (1999), “The
Acquisition and Use of Sales Force
Automation by Mid-Sized
Manufacturers,” Journal of Personal Selling &
Sales Management, 19 (2), Spring, 59-73.
Schottmiller, Paul (1996), “Apparel Industry: How
the New SFA Can Help,” Apparel
Industry Magazine; Atlanta; Nov
Northern Illinois University
Simon, Herbert A. (1955), "A Behavioral Model of
Rational Choice," Quarterly Journal of
Economics, 69, 99-118.
____________ (1974), "How Big is a Chunk?"
Science, 63, 81-97.
Speier, Cheri and Viswanath Venkatesh (2002),
“The Hidden Minefields in the Adoption
of Sales Force Automation
Technologies,” Journal of Marketing, 66
(July), 98-111.
Spiro, Rosann L. and Barton A. Weitz (1990),
“Adaptive Selling: Conceptualization,
Measurement, and Nomological Validity,”
Journal of Marketing Research, 27 (February),
61-69.
Sujan, Harish (1986), “Smarter Versus Harder: An
Exploratory Attributional Analysis of
Salespeople’s Motivation,” Journal of
Marketing Research, 23 (February), 41-49.
____________, Barton A. Weitz, and Nirmalya
Kumar (1994), “Learning Orientation,
Working Smart, and Effective Selling,”
Journal of Marketing, 58 (July), 39-52.
____________, ____________, and Mita Sujan
(1988), "Increasing Sales Productivity by
Getting Salespeople to Work Smarter,"
Journal of Personal Selling and Saless
Management, 8 (2), 9-19.
Stiroh, Kevin J. (2002), "The Economic Impact of
Information Technology," Encyclopedia of
Information Systems, Vol. 2, Hossein Bidgoli
(ed.), San Diego, CA: Academic Press, p
1-15.
Szymanski, David M. (1988), “Determinants of
Selling Effectiveness: The Importance of
Declarative Knowledge to the Personal
Selling Concept,” Journal of Marketing, 52
(January), 64-77.
Tanner, John F., Jr., Michael Ahearne, Thomas W.
Leigh, Charlotte H. Mason, and William
C. Moncrief (2005), “CRM in SalesIntensive Organizations: A Review and
Future Directions,” Journal of Personal
Selling & Sales Management, 25, 2, 169-180.
Taylor, Thayer C. (1994), “Take Your Time,” Sales
and Marketing Management, 146 (July), 4546.
Thetgyi, Olivia (2000), “Radical Makeovers,” Sales
55
Winter 2006
and Marketing Management, April, 78-88.
Venkatesh, Viswanath, Michael G. Morris,
Gordon B. Davis, and Fred D. Davis
(2003), “User Acceptance of Information
Technology: Toward a Unified View,”
MIS Quarterly, 27, 3, 425-478.
Verity, John W. (1993), “Taking a Laptop on a
Call,” Business Week, October 25, 124-135.
Walker, Orville C., Gilbert A. Churchill, and Neil
M. Ford (1977), "Motivation and
Performance in Industrial Selling: Present
Knowledge and Needed Research,"
Journal of Marketing Research, 14 (May), 156178.
Weitz, Barton A. (1981), “Effectiveness in Sales
Interactions: A Contingency
Framework,” Journal of Marketing, 45 (1),
85-103.
__________, Harish Sujan and Mita Sujan (1986),
“Knowledge, Motivation, and Adaptive
Behavior: A Framework for Improving
Selling Effectiveness,” Journal of Marketing,
50 (4), 174-191.
APPENDIX
Multi-Item Measures Used in the Study
I. Sales Force Comprehensiveness (adapted
from Hunter, Perreault, and Armstrong 1998)
(Formative Scale).
Please tell us the type of sales force automation
components you are using (check all that apply).
Software:
a. Word processing
b. Order status
c. Promotion funds
d. Spreadsheet
e. Graphics
f. Order entry
g. Sales forecasting
h. Data management
i. Contact management
j. Time management
k. Shelf space management
Hardware:
a. Laptop
b. Email
c. Computer based presentations
d. Fax
e. Color printer
f. Black & white printer
g. Teleconferencing
h. Mobile phone
i. LCD project presentations
j. Personal digital assistant
k. TV/Video conferencing
l. Web
II. Account Management (Composite
Reliability = .9074).
Please tell us the degree to which sales force
automation helps you in the following areas (Not
Very Helpful = 1, Very Helpful = 7).
a. Providing more accurate pricing information.
b. More accurate order placement.
c. Making fewer costly mistakes based on
incorrect information.
d. Enhances productivity.
e. To sell more consultatively by helping you
assess customer needs. Please tell us the degree
to which sales force automation helps you in the
following areas (Not Very Helpful = 1, Very
Helpful = 7).
a. Providing more accurate pricing information.
b. More accurate order placement.
c. Making fewer costly mistakes based on
incorrect information.
d. Enhances productivity.
e. To sell more consultatively by helping you
assess customer needs.
III. Sales Process Effectiveness (Composite
Reliability = .8224).
Please tell us the degree to which sales force
automation helps you in the following areas (Not
Very Helpful = 1, Very Helpful = 7).
a. Ability to analyze reasons for won and lost
opportunities.
b. Improves closing rates.
c. Improves customer retention.
d. Enhances teamwork.
Vol. 6, No. 1
56 Journal of Selling & Major Account Management
IV. Working Hard – After Versus Before SFA
( Adapted from Sujan 1986) (r = .571).
a. The number of hours per week that you work
are: 1 = Much Fewer, 7 = Much Greater.
b. How hard you work during these hours is: 1 =
Much Less, 7 = Much Greater.
V. Working Smart – After Versus Before SFA
(Adapted from Sujan 1986) (r = .683).
a. The way in which you approach your customers
is: 1 = Much Less Effective, 7 =
Much More
Effective.
b. The number of different approaches you use
with your customers has: 1 = decreased, 7 =
increased.
VI. Job Performance (Composite Reliability
= .8755)
Please tell us about your productivity after
implementing sales force automation compared to
before you had sales force automation.
a. What best describes what happened to your
sales volume? (Decreased more than 20% = 1,
Increased more than 20% = 7).
b. How much selling time do you think you
gained (lost) per month? (Lost more than 4 days
= 1, Gained more than 4 days = 7).
c. How much did sales force automation increase
(decrease) your productivity? (Decreased
productivity by 31% or more = 1, Increased
productivity by 31% or more = 7).
d. How much more difficult did sales force
automation make your job? (Much more difficult
= 1, Much easier = 7).
James E. Stoddard (Ph.D. Virginia Tech, AMA
Doctoral Consortium Fellow) is an Associate Professor
of Marketing in the John A. Walker College of Business
at Appalachian State University in Boone. His research
has appeared in several scholarly journals including the
Journal of Marking Channels, the Marketing
Management Journal, Psychology and Marketing,
Services Marketing Quarterly, and Tourism Economics
among other marketing and business publications.
stoddardje@appstate.edu
Northern Illinois University
Stephen W. Clopton (Ph.D., University of North
Carolina) is Professor of Marketing at the John A.
Walker College of Business, Appalachian State
University. His research has appeared in the Journal of
Marketing Research, the Journal of the Academy of
Marketing Science, Journal of Marketing Education,
Decision Sciences, the Journal of Purchasing and
Materials Management, Marketing Management
Journal, and various other marketing and business
publications. cloptonsw@appstate.edu
Ramon A. Avila (Ph. D. Virginia Tech) is the
George and Frances Ball Distinguished Professor of
Marketing and the Director of the H. H. Gregg Center
for Professional Selling, Ball State University. His
research has appeared in the Journal of Marketing
Research, the Journal of Personal Selling and Sales
Management, the Journal of Management, Industrial
Marketing Management, the Journal of Euromarketing,
Marketing Management Journal, and various other
marketing and business publications ravila@bsu.edu
Application Article
Winter 2006
57
Relationships: The 21st century asset
By Jerry Acuff and Lori Champion
It is no surprise that when executives are asked, “How important are relationships to the success of your business,” the
answer is almost always, “relationships are everything,” or “they are very, very important,” or “we would not be in
business without relationships.” If this is, indeed, the truth that relationships are everything, what are companies doing
to protect and grow those important business assets (customer relationships)?
Ask financial controllers in most organizations about the most valuable assets of the company, and you will likely hear:
fixed assets, employee assets, customer assets, and brand assets. Many corporations have asset managers to watch over
physical and financial assets. Human Resources and Department Heads watch over employee assets, and the position
of Brand Manager is responsible for growing and protecting the company brand.
It is interesting that the most important asset—the customer—does not appear to hold the same value; although, none
of the others exist without it. Organizations are people dealing with people. In most situations, there is minimal control
over your company’s relationships because there is usually only one person responsible for managing them—the sales
person. Think about it, if there is only one key contact with your client, what kind of value are you really placing on
that relationship?
This article provides methods on how to look at the value of company’s relationships and secure them as an asset. It
outlines what is necessary to be successful in managing relationships and building a culture to support it.
Ask financial controllers in most organizations
about the most valuable assets of the company
and you will likely hear that there are four major
asset categories: fixed assets, employee assets,
customer assets, and brand assets. Many
corporations have asset managers to watch over
physical and financial assets. Human Resources
and Department Heads watch over employee
assets and the position of Brand Manager is
responsible for growing and protecting the
company brand.
It is interesting that the most important asset—
the customer, does not appear to hold the same
value, although, none of the others exist without
it. People influence business and people are what
truly make up an organization. Organizations are
people dealing with people. In most situations,
there is minimal control over your company
relationships because there is usually only one
person responsible for managing them—the
sales person. Think about it, if there is only one
key contact with your client, what kind of value
are you really placing on that relationship?
It is no surprise that when we ask executives,
“how important are relationships to the success
of your business,” that the answer is almost
always, “relationships are everything,” or “they
are very, very important,” or “we would not be
in business without relationships.” If this is
indeed the truth, that relationships are
everything, what are companies doing to protect
and grow those important business relationships
(customer assets)?
The answer is that relationships which are crucial
to your business’ success need to be managed
and protected as an organizational asset. Jerry
Acuff, CEO of DELTA POINT- THE SALES
AGENCY and author of The Relationship Edge
in Business says that in order to build
relationships as organizational assets your must
consider the three ways in which people have
relationships with your company. Look at the
diagram below and you will see the three kinds
of relationships people develop with a
company—individual, brand, company.
Vol. 6, No. 1
58 Journal of Selling & Major Account Management
Diagram 1.
Company
Individual
Brand
The question a company must ask is what level
of relationship do our key clients have with us?
Is it mostly with our brand or mostly with an
individual representative? The goal is for key
accounts to have relationships at the top--with
the company. This is the only way companies
will be able to secure their growth with critical
business partners.
First and most importantly Relationships as
Organizational Assets must be seen as a highlevel, cross-functional initiative that is driven
from the top and throughout the infrastructure
of a company. The process becomes part of a
company’s culture, so without alignment at a
senior management level it is a futile effort.
There are four key components to building your
relationships as assets:
1. Data – The information a team has on every
relationship that is imperative to their company.
2. Expectation- As a company, expectations for
relationships must be very clear in terms of
communication team members responsible, and
tracking of relationship building process.
3. Accountability – Implement a system for
tracking progress with company relationships
and holding people responsible for the activities
that will move the relationship forward.
4. Skill Development – Relationship building is a
skill. Companies who want to include
relationships as part of their corporate culture
must identify the skill gaps and provide
appropriate training and practice so that people
become accomplished at forming valuable
business relationships.
Northern Illinois University
Component one is collecting data-- identify the
relationships that are critical to maintain for the
company and compile their information in one
location. Most companies have a CRM system
for tracking this kind of client information. Find
out as much as possible about each key client
identified and update the files frequently. Once
team members have captured all the pertinent
information, share it!
Accessibility of
information is key for the process to work. As a
team, determine everyone within your
organization who will be responsible for
“touching” this particular client and develop a
method for accurately sharing data. In some
cases the team may involve the Sales Rep, the
Director of Sales and perhaps a pertinent
operations manager. In others, the company will
have senior executives as part of a relationship
management team.
Companies as a whole must set expectations
(component two) for client interactions. There
needs to be complete clarity about how each
person will communicate with every client and
each other. Be very specific about the quantity
and quality of interactions. This means
designating the number of “touches” and by
whom on a weekly and monthly basis. What is
the desired quality or nature of the interface- email, phone call, coffee, dinner, etc.? Think
about the client for a minute. What we are
proposing will make regular follow-up part of
everyday life for team members. It is
Important that while these types of actions are
a normal part of business for your team, the
client view each and every one as special.
Planning is essential with every action teams
take. Planning insures that you meet or exceed
your quality of interaction expectations.
Communication is critical so, once a “touch” is
complete; the information is then entered into a
data base and shared with the relationship team
responsible for the client. You can see that
while managing relationship assets may not be
difficult, the process could become complicated
without clear expectations and communication
both from the executive level as well as among
Application Article
the team of people responsible for maintaining
and growing a particular relationship.
We have said that in order to effectively adopt
the process of relationships as organizational
assets into your company, there must be
complete top down alignment. The key to all of
it, as with any new process, is accountability
(component three). Systems are in place and
there are multiple people engaging with every
imperative relationship. How does one know
that progress is moving forward and
relationships are becoming more secure for the
company versus an individual or brand? Make it
part of culture by holding people accountable.
Decide whether relationship management is a
regular agenda item where team members give
weekly updates on key account progress or
perhaps each team submits a monthly report
around three target customers. There are
multitudes of ways to hold people accountable
for responsibilities. Figure out what works best
for the company and track progress regularly.
The fourth component, skill development is
perhaps the most essential. The program
structure is complete and everyone from the top
executive to the intern is on board with securing
relationships as organizational assets, so how
well are people going to perform? Measuring
current skills and increasing them to expectation
levels requires some analysis and most definitely
training.
Building a strong business relationship is a
process. It is not magic, it’s not chemistry, it’s
not luck…it is a process. The skills necessary to
grow a relationship involve understanding the
process for building relationships and being able
to correctly assess where you stand in the
relationship at any given time. The Relationship
Edge in Business states, “Building business
relationships that last is a skill virtually anyone
can learn. It requires a process you can master
since you already know instinctively what the
process requires. If you master the simple steps
your business (and personal) relationships will
improve.”
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Winter 2006
Building relationships requires three-steps:
1. Have the right mindset—what you think.
What you think about the client and yourself has
equal impact. You must think that relationships
are important. You must believe that you are
someone with whom other people would want
to have a relationship. Why would they want to?
Because you have experience, training, skills,
abilities, knowledge (or all five) they value. You
must also think well of others and learn to think
as much as you can from the other person’s
point of view.
2. Gather information- what you ask. You must
also ask the right questions. The goal through
asking is to discover common ground—mutual
friends, interests or concerns. Or if there is no
obvious common ground and the other person
cares passionately for something about which
you know little, your goal should be to learn
from him or her.
3. Demonstrate your professionalism, integrity,
caring, and knowledge, and when appropriate, do
unexpected, inexpensive, thoughtful acts based
on what you have learned about the other
person—what you do. Knowledge is only as
useful as the actions you take. Once you learn
about the client, do something with the
information that demonstrates you care.
The relationship process will not work on
everyone—but it will work on most people if
you follow the steps.
You can use the steps in the process to assess
progress or lack of progress in any given
relationship. As a group of managers responsible
for a given relationship, ask these questions:
Do we have the right mindset about the client
and about ourselves?
Have we asked the right questions or have we
asked enough questions? What questions will we
ask the next time we encounter this person?
What have we done based on what we know?
Taking steps unknowingly, the way most people
Vol. 6, No. 1
60 Journal of Selling & Major Account Management
build relationships is the difference between
unconscious competence and conscious
competence. Most of us are unconsciously
competent at building good relationships,
meaning we do it naturally, without having to
really think about it. Understanding the process,
however, puts you at a level of conscious
competence, where you can and do think about
how you go about building the relationship. The
process does not merely happen. You know how
to do it and you can do it when it counts.
The second skill is to be able to assess the
strength of dialogue. Solid relationships reflect
strong trust and rapport. And where trust and
rapport are present, people can have meaningful
dialogue. Meaningful dialogue is defined as an
adult conversation rooted in the truth.
Relationships and companies are too often
ruined because people cannot get at the truth. If
clients will not tell you what they honestly think
about your company, products and services,
what is the likelihood you can do business with
them?
Too many salespeople do not address this issue.
They don’t make it a priority to build personal
relationships or to establish dialogue. So, the
goal is to strive for a better business relationship
because it encourages meaningful dialogue.
When you have a strong relationship, the other
person listens differently and shares more
openly. Similarly, you expect colleagues with
whom you have a positive relationship to listen
to
you because they know they can trust
what you say.
Assess your dialogue skills with your team mates.
There are six rules of “Meaningful Dialogue.”
Use them as a report card to determine how well
team members accomplish these points:
•
Without meaningful dialogue, there is no
selling--did you have dialogue that
enabled you to sell?
•
There may be buying or purchasing, but
there is no selling--how complex is the
sale? Did your client purchase or did you
sell?
Northern Illinois University
•
The ideal listen/talk ratio is as close to
50/50 as you can make it-- how much did
they talk and how much did you talk?
•
Conversations are voluntary- you must
manage the content and condition of the
call – how safe did your client feel? Did
they open up and have an honest
conversation?
Meaningful dialogue begins with your intent-what was your intent and was it in the client’s
best interest?
Meaningful dialogue should end with your
assessment of the exchange – did you take the
time to assess your conversation and plan the
next conversation?
Use the relationship building process and
meaningful dialogue to climb the Relationship
Pyramid (Diagram 2). The Relationship Pyramid
reflects the five positive relationship levels one
can have with another human being. They form
a pyramid because a great many people, literally
billions, form the base—people who do not
know you by name—and relatively few are at the
peak—the people who value a relationship with
you.
Diagram 2- The Relationship Pyramid
People
who value
a relationship
with me
Knowledge & Action
People who
respect me
People who are
friendly with me
People who like me
Like Me
People who know me by name
Know Me
People who don’t know me by name
It is relatively easy to move up from the base to
the first level where people know you by name.
The best way to get people to remember your
name is to remember and use theirs. The next
level includes people who know you by name
and who like you. By “like you,” we mean they
don’t mind having you around. They are not
offended when you visit. You are not close (yet),
but the door is open to becoming closer.
Application Article
The third level covers those who are friendly with
you. ”Friendly” means they will talk about more
than the immediate business at hand. They will
chat about the football game or what you did last
weekend or where they went on vacation. At this
level, you are establishing and sharing common
interests and concerns, and you now routinely
talk about those concerns.
Level four consists of people who respect you.
Respect is defined as: “esteem for or a sense of
the worth or excellence of a person, a personal
quality, or ability.” Someone who has a high
opinion of your integrity, your knowledge, your
courage, or all three respects you by definition.
The last level contains people who value a
relationship with you because they believe it is in
their best interest to have one. They trust you,
think you can help them, and are confident you
will not abuse their trust. Even better, the feeling
is mutual; just as you help people at the top of the
pyramid, they will help you.
Most business relationships hover at level threepeople who are friendly with me. These
relationships are about likeability which is the
driver for achieving levels four and five. Just to
be liked is not enough. When you reach the top
two levels in the Relationship Pyramid, the
Respect Me/ Value a Relationship with Me levels,
you have relationships that can help you even
reach your stretch goals.
Winter 2006
61
1. The first step is to agree as an entire company
that you have relationships important enough to
the growth of business that you want to secure
them beyond the sales rep and brand
relationship. You want this client to partner in
the best interest of the company’s future.
2. Identify specific clients or key thought leaders
to engage in this process and determine who in
your organization will share in each relationship.
Determine the desired end result as a company
from the relationships.
3. Each group of people or relationship asset
team classifies the level where s/he is on the
Relationship Pyramid with the client.
4. Executives assess skill sets of all participants
for the relationship process and ability to have
meaningful dialogue. Set expectations and
arrange for training so all team members achieve
same skills and have common language to work
successfully in new program.
5. Once every team member demonstrates
understanding and is able to begin doing the right
things to move up the pyramid, set very clear
expectations with in each group of individuals as
to who will “touch” the client, when and how
often.
6. Create very clear communication and data
tracking system among teams and with the
company.
Achieving the top two levels involves finding out
what people treasure both personally and
professionally and acting on that information. It
is also a function of your knowledge, your
integrity and your actions.
7. Use the Pyramid and relationship process, to
continually assess progress in each relationship
and hold people accountable. Develop an ongoing reporting process for entire organization.
Adapt as necessary.
The Relationship Pyramid is an effective tool to
help companies define where they truly are in
those crucial relationships. Corporate teams
begin by taking each relationship and have every
person involved identify where s/he is on the
pyramid with that client. This is the starting point
for the relationship plan.
The MGM Grand Resort and Casino in Las
Vegas is a great example of how to secure
relationships as organizational assets. David
VanKalsbeek, executive vice president of Sales
and Marketing will tell you that he is an “asset
manager” for the most important asset—the
customer. In a recent interview with Van
Kalsbeek, he explained that “if you leave the
client relationship in the hands of one person
How do we apply these skills and components
into a workable plan?
Vol. 6, No. 1
62 Journal of Selling & Major Account Management
(the sales rep), you are setting yourself up for
fast failure.”
The MGM Grand is a large, Las Vegas hotel
where one might assume that a group could be
considered just part of “the machine” vs. having
a real relationship with the property. David
assures us that is not the case. In fact, the
number of “touches” per client is many and the
staff as a whole insures that the clients are not
only touched frequently, but they have
relationships with multiple members of the
resort team. The relationship a group meeting
planner has with the sales person is just the
beginning. His or her relationship is equal, if not
greater with the conference coordinator and the
conference team. There are other operational
managers as well who will have responsibility for
the relationship. The deeper the relationship
goes within their organization the better.
David tells us that he “touches” every meeting at
some level and if they feel he needs to make a
personal appearance or phone call, etc. He is
there and more than happy to do it! He goes on
to say, “You need a great product and the service
to go with it. In order to broaden the sales
contact surface, everyone needs to be involved
with the client. You also need the infrastructure
to support it. We need the synergistic qualities of
the whole team.”
When a client plans a meeting at the MGM
Grand, the staff goes out of its way to learn as
much as they can about you and if you are
returning, they remember. Van Kalsbeek
explains,” We know who the meeting planners
are, we make everything in their world special
and aim for a hassle-free meeting. We know that
some of them might lose in the casino, so we
want to be sure that they experience the synergy
of our team and our property. We want to be
sure that when they ask themselves, did I have
good time that the answer is yes!”
The MGM Grand takes it one step further by
designing a website that forges an electronic
relationship with the customer. David tells us
Northern Illinois University
that, “there used to be travel agents who handled
client travel arrangements. Now people surf the
web and make their own plans. Our website is
also the beginning of the relationship. We want
people to feel like we know them at every
possible contact.”
“What is your message? Are you accessible and
responsive to your clients—and does your team
also communicate the same message? Our team
is very accessible and our policy is to follow-up
every call or request within 24 hours. I am
personally on the phone or in meetings with
clients or third-party vendors on a daily basis.
We are in the people business and it all boils
down to relationships. The more I can show a
customer I know about them—without being
scary—the stronger our relationship will
become.”
This type of company-wide relationship building
does not happen overnight. The MGM puts
their money where their mouth is and trains their
staff. Van Kalsbeek tells us that they give people
all of the skills they need to be successful
relationship managers, they even train them in
areas like time management and how to get to
the top. They teach and create a highly skilled,
synergistic team that surrounds each meeting
and ensures its success.
Jerry Acuff of The Relationship Edge has a
favorite line. He always says if he could sum up
relationship building in one sentence it would be,
“Be other focused!” I am certain David Van
Kalsbeek would agree. The MGM Grand wins
around 30 awards every year for excellence.
Clearly the team approach to relationship
management along with product and service is a
winner.
Application Article
Winter 2006
63
Jerry Acuff is a principal and founder of Delta Point
in Scottsdale, Arizona.
Prior to founding Delta Point Jerry founded JBI
Associates, a healthcare consulting firm in Morristown,
New Jersey. Jerry was also Vice President and General
Manager of Hoechst-Roussel Pharmaceuticals prior to its
merger with Marion Merrell Dow. In his twenty-year
career at Hoechst, Jerry was Salesman of the Year twice
and District Manager of the Year five times.
Jerry has been featured in Sales and Marketing
Management Magazine, Investors Business Daily,
Managed Care Pharmacy Practice and Hospital
Pharmacist Report. He has been an Executive in
Residence at Northern Illinois University and The
Amos Tuck School of Business at Dartmouth College.
He is a graduate of The Virginia Military Institute.
For over 15 years, he has spoken and consulted
extensively on the issues of sales excellence, change
leadership, and building customer-focused organizations.
Jerry is the author of The Relationship Edge In
Business, a book that focuses on leveraging interpersonal
skills to build meaningful customer relationships.
jacuff@gottochange.com
Lori
Champion joined Jerry Acuff and his
Scottsdale, AZ. based company, Delta Point—The
Sales Agency in July,2004 with over 20 years experience
in the both the sales and training arena. Lori’s
experience includes senior management positions with
Sheraton Hotels and Tanner Companies- the original
direct sales women’s clothier. In addition, she owned her
own consulting company in both Alaska and California,
and she and her husband owned and operated the historic
St. James Hotel in New Mexico.
Lori’s background in training and sales includes the
development of learning workshops in the customer service
and leadership arena to very specific skills for the
entrepreneurial start-up company. Lori has a BA from
the College of Wooster and is a certified trainer for
Situational Leadership. She is a member of ASTD and
SMT. lchampion20@cox.net
Vol. 6, No. 1
64 Journal of Selling & Major Account Management
Word of Mouth Process: Your Way to Sales Success
By Joe Cullinane
Generating leads is a challenge that most business-to-business sales organizations face. In this article we describe a
lead generation system based on Word-of-mouth (WOM). WOM is getting a lot of attention in consumer marketing
today. It is touted as an alternative to traditional marketing disciplines, like advertising and direct mail. But WOM has
not received as much attention in the world of business-to-business sales. The purpose of this article is to describe how
WOM applies to business-to-business sales and lead generation. The article outlines a process that is called WOMP
(Word-of-Mouth Process) designed help business-to-business sales organizations and individual sales people benefit
from WOM. The article identifies seven elements of WOMP
Word-of-mouth (WOM) is getting a lot of
attention in consumer marketing today. It is
touted as an alternative to traditional marketing
disciplines, like advertising and direct mail. But
WOM has not received as much attention in the
world of business-to-business sales. Word-ofMouth can be a powerful tool that can drive
sales and supercharge the sales process, in
particular, as a lead generation tool. The
purpose of this article is to describe how WOM
applies to business-to-business sales and provide
a process that is called WOMP (Word-of-Mouth
Process) to help business-to-business sales
organizations and individual sales people benefit
from this powerful approach.
Now, of course, WOM is not new. All good
sales people know that WOM is a powerful
factor in sales success. Take a minute now to
think about your biggest and best sale. Think
about how WOM played a role in that sale. It’s
even possible that WOM played some role in the
majority of your best sales. What’s new about
harnessing WOM today is that we have learned
more about its effectiveness, and we have new
tools and technologies that facilitate the process.
WOMP as a Sales-Lead Generator
According to a variety of recent studies, each of
us is exposed to anywhere from 247 to 3000
commercial messages each day. No wonder it’s
Northern Illinois University
difficult getting the attention of prospects.
Business buyers are inundated with sales people
and marketers trying to get their attention. Many
buyers avoid contact with sales people by using
technology like caller ID, employing gatekeepers,
or simply ignoring this ceaseless onslaught. Cold
calling – that old staple of selling – is becoming
increasingly ineffective.
A study by Huthwaite found
63 % of salespeople say cold calling is what they
most dislike about their jobs.
91 % of buyers never respond to an unsolicited
inquiry.
71 % of buyers find cold calls annoying.
88 % of buyers will have nothing to do with cold
callers.
In the face of over-saturated media and
messages even in the professional buyers world,
what is a company or salesperson to do? The
answer may be WOMP. Think about the last
time you bought a car or a computer. Did you
buy purely on the advertising or TV
commercials? Or did you seek out information
from experts, friends, family, or trusted
publications and Web sites? If you are like most
people, you consulted with trusted sources. The
same is true for corporate purchasing.
Companies buy from trusted sources and seek
out information from experts and influencers.
They value referrals and references from other
Application Article
65
Winter 2006
companies in their field.
WOMP’s Seven Steps
Despite WOMP’s advantages, most sales people
would tell you that they do not use it
purposefully or effectively. The reason is that
they do not have or understand the system. The
Word of Mouth Process or WOMP is a system
that anyone can use to harness the power of
word of mouth.
Although it’s a simple concept, a number of
crucial factors give word-of-mouth its
tremendous power. Follow these seven steps of
WOMP to harness the power of word-of-mouth
and generate new business-to-business leads.
It All Starts With A WOMP Story
If you want to create favorable word of mouth
about yourself, company, and/or products, you
have to give people something to talk about.
The way to accomplish this is to create a
“WOMP story.”
Humans have used stories to communicate since
ancient times. Rhetorical scholar Walter Fisher’s
narrative theory explains how we as humans
communicate by taking complicated information
and transforming it into narrative stories. For
example, when Fed Ex first started their service,
it seemed miraculous that a company could
actually get a package anywhere overnight. Early
users were quite evangelistic about Fed-Ex –
seems like everyone had a favorite “Fed Ex
story” to tell about how Fed Ex saved the day.
Success stories like these make it easy for the
customers to relate to the benefits of a product
and are far more effective than simply stating
features and functions.
Here are some things to consider when creating
your WOMP story.
1. What’s unique and different about you, your
company, and/or product that’s worth talking
about from the customer perspective?
2. What’s remarkable about what you are doing
that will stimulate WOM?
3. What’s the valuable proposition you wish to
convey? What problem do you solve?
4. What’s your elevator pitch? Your 30 second
story?
5. How will you disseminate your message; e.g.,
e-mail, telephone, blogs, publicity, etc.?
1. Leverage Influentially.
“In times of change, people naturally seek a
guide, someone who's been ahead of them,
who's already identified the issues, addressed
them in his or her own life, and can offer good,
reliable, informed insights, advice, information
about what's going on now and what's to come,
someone they trust.
Americans are placing
increasing stock in the simplest form of
communication, word-of-mouth advice and
information from people they know and trust.”
Ed Keller and Jon Berry, The Influentials
In their book, The Influentials, Ed Keller and
Jon Berry point out that one person in ten
influences the other nine. These people can be
analysts, columnists or experts. For example, I
will not make a technology decision without
conferring with Roger Green, a former CIO. Get
your message across to the Rogers of the world.
Find out where they go for information, what do
they read? What Web sites do they visit? Identify
the influential people in your industry and put
together a strategy to get them talking about
your product or service. Send them a free copy
of your software, forward favorable articles or
reviews. Do you know someone who can
introduce you to the right Influentials?
Every buying organization has an “Influential”
or “a go to person” for your product area. In
Enterprise software sales it was the systems
programmer. The systems programmer is highly
respected for their technical knowledge and
often influence the CIO’s decisions. Even if the
system programmer was not involved in the use
of the product, his or her endorsement had a big
impact in the sale.
Vol. 6, No. 1
66 Journal of Selling & Major Account Management
2. Become a Recognized Expert.
“Experts are the most important and leveraged
sources of word of mouth. When you have the
experts behind you and can get them talking
about your product, they will often start a
stampede toward your product is unstoppable.”
George Silverman, The Secret of Word-ofMouth Marketing
When you become known as an expert in your
field, clients will come to you. How do you gain
this “expert” status? Write and publish a book.
Teach a course at a university. Publish articles in
industry journals or trade papers. Speak or
participate in panels at industry events. Publish
in scholarly journals. Get yourself quoted in the
media. Also, advanced degrees, certifications,
and awards all build credibility and help establish
expertise. If you are perceived as an expert,
prospects will be drawn to you and seek you out.
Ask yourself: Are there opportunities to speak at
trade association events? What about writing an
article for an industry newsletter? Is there an
industry certification that will increase your
credibility?
3. Create High Visibility.
“Whether you are a lawyer, a physician, a
marketing manager, or an artist, the ability to
create and manage your visibility is vital to
maximizing your success.”
Irv Rein, Philip Kotler and Martin Stoller,
High Visibility
Speaking of media, raise your visibility by
appearing in as many media channels as possible.
Participate in radio, TV, and print interviews.
Hire a PR firm to get you in front of the editors
and journalists in your market niche. Also
consider an online service like Media Map’s
Sourcenet or Bacon’s ProfNet to find story
opportunities. Create visibly events like golf
tournaments and product launches that draw
media attention. Become the go-to person for
the journalists in your niche for quotes and
Northern Illinois University
stories. Highly visible sales people often bring
home the big deals. Ask Donald Trump!
Sales people can raise their visibility by becoming
actively involved in trade associations, alumni
groups, and local Chambers of Commerce.
Getting involved with organizations like The
Sales and Marketing Executives International
(SMEI) and The American Marketing
Association, are also ways to become more
visible. Offer to speak at their events and attend
their trade shows as well.
In addition, creating visibility opportunities and
events can increase your leads and sales success.
Many companies like AT&T and Buick sponsor
golf tournaments or other events to create
opportunities for their sales staff to interact with
customers and prospects in a more relaxed an
informal setting.
4. The Halo Effect.
Associate with the big names, partner with wellrecognized companies like IBM or Cisco. Be
associated with celebrities – generate your own
word-of mouth by associating with those who
already have it. Do joint sales calls with your big
name partners. (Look for celebrity
endorsements. Oprah’s endorsement on her
book club created numerous best sellers. Who’s
the Oprah in your industry?)
An example of the halo effect is Microsoft. In
the early 1980's IBM was looking for a company
to provide the operating system for their new
personal computer. When their first choice was
not available they went to a small company in
Redmond, Washington and asked them to
provide the operating system. Microsoft was
able to leverage the fact that they provided the
operating system for IBM to get other personal
computer companies to license their operating
system, and thus, they became the largest
software company in the world. A side note is
that IBM recently sold their personal computer
business to a Chinese company (Lenovo) and is
no longer in the business.
Application Article
Creating a Halo Effect can be as simple as giving
away something that establishes a connection
with something well known. A colleague of
mine provided a “Dilbert” drawing every hour at
a training conference.
The audience was
trainers and training managers, and they
responded very well to the Dilbert promotion –
they connected with Dilbert, and by implication,
connected with the company.
Alliance partners are also a great way to gain
access to new customers and bring additional
value to your clients. When I was selling
enterprise software, it was a real plus to make
joint sales presentations with the IBM sales rep.
They had high level relationships established that
opened executive’s doors.
5. Use Customer Reference Selling.
We all know we should do this, but how many
really do a good job of it? Have your customers
open the doors for you and get leads and
references from your clients. The first step is to
ask. When a client says something nice about
your work, always ask if they’d be willing to say
it writing. It’s also much easier to get a referral
when the success of your project is fresh in their
mind. Make it a point to find out who else can
benefit from your knowledge, products or
services.
“How do references help sales? Referenceable
customers, at each stage of the sales cycle, are
invaluable. Customer validation -- a success
story, logo or quote -- opens the door and
creates an audience for your company’s solution.
Later in the sales cycle, customer references, case
studies, ROI reports and onsite visits can be
employed to get users, lines of business buyers,
senior management and CFOs onboard. The
reality is that vendors vying for wallet-share are
doing so in highly-competitive situations.”
Promise Phelon, Partner The Phelon Group
Finally, references and referrals help prospects
mitigate risk and feel comfortable with your
products and services.
67
Winter 2006
6. Leverage Your Social Network.
We all have amazing networks of former
colleagues, people we knew in school or met in
community organizations. Neighbors or fellow
health club members may need our products or
know someone who does. Take out a piece of
paper and write down 20 names of people you
haven’t contacted recently. Give them a call and
tell them what you’re up to. Be sure to ask if
they know of anyone who can benefit from your
product or service. Remember, the weak ties or
friends of friends are often better sources of
leads than your direct ties.
Take the time to mine your social network for
leads and contacts. For friends and close
colleagues--pick up the phone and give them a
call and get reacquainted. For casual friends and
business acquaintances--an e-mail may be more
appropriate.
7. Employ Technology and Tools.
“What still needs to happen for b-to-b marketers
to fully realize the value of word-of-mouth
marketing, experts say, is for them to tweak and
leverage these existing customer-driven
approaches to take full advantage of the power
of online networks. That includes things such as
blogs, social networks, user forums and gripe
Web sites, all of which hold the promise of
sending traditional word-of-mouth techniques
into overdrive.”
Richard Karpinski in BtoB Magazine
Even though this is a person-to-person
application, it can also be leveraged to generate
b-t-b sales leads. The hot word-of-mouth tools
on the Internet are social networking Web sites
and Web logs, or blogs and podcasts (audio
blogs). Social networking Web sites like
LinkedIn, Ryze, and Alwayson are automating
the word-of-mouth process. For the first time
you not only can manage your contacts but
exponentially expand your network by leveraging
your contacts’ networks. Good sales people have
engaged in referral-based selling for years, but
Vol. 6, No. 1
68 Journal of Selling & Major Account Management
these tools offer a new way to efficiently manage
the networking process and take it to the next
level.
So zoom yourself and see what you find. Build
some “good Google” if you don’t like what you
see!
A note of caution – be careful not to abuse your
contacts who may be inundated with invitations
to join social nets.
Even with the power of new technologies,
“knees-to-knees” is still the best!
As much as technology can help WOMP is still
best delivered in person. Below is a quote from
“Trust Media,” a white paper produced by
Edelman and Intelliseek that validates that point.
"When asked how they make recommendations,
80 percent of consumers say they make them in
person, followed by 68 percent who say they
make them over the telephone. This
phenomenon is even stronger among influentials
(the one in ten Americans who tell the other
nine how to vote, where to eat and what to buy,
according to over 60 years of NOP World
research), with 90 percent of this group making
in-person recommendations and 79 percent
making recommendations by phone.”
As traditional methods of generating leads
become less effective, it makes sense to try new
approaches. Give these tools a try. Create a
process that combines them most effectively to
tell your unique story to your customers and
prospects. Harness the power of word-of-mouth
with WOMP, the unstoppable sales-lead
generator.
Here’s what Charlene Li, an analyst at Forrester
Research, had to say about influencing Google
searches in Fast Company magazine:
"You can't ask Google not to find something
about you that's on the Web. But what you can
do is make sure that you're putting stuff out
there that it will find.
That might mean making sure your corporate
Web site includes a profile of you, maintaining a
Web log, or writing articles for online
publications in your field.”
Northern Illinois University
Joe
Cullinane
is an Executive Advisor,
Consultant, Educator and Author. He has held
executive and sales positions with Xerox
Corporation, NCR Corporation, SalesLink
Systems and Diversified Software Systems, Inc.
He was the Founder and CEO of the Telum
Group, Inc., a Silicon Valley consulting firm
dedicated to providing professional sales and
marketing services to hi-tech start-ups. Cullinane
published the book: 21st Century Selling: An
anthology of advice from the top sales pros. He is
the chair of the MSC steering committee at
Northwestern University and a board member of
the NIU Executive Club. Mr. Cullinane holds a
Master of Science in Communication degree from
Northwestern University, a Master of Business
Administration degree from Dominican University,
and a Bachelor of Science degree in marketing from
Northern Illinois University. joe@joecullinane.com
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