10th Global Conference on Business & Economics
ISBN : 978-0-9830452-1-2
Responsiveness as Antecedent of Satisfaction and Referrals in Financial Services
Marketing
Dr. S. K. Pandey
Assistant Professor - Marketing
FORE School of Management
B-18, Qutab Institutional Area,
New Delhi – 110016
Ph – 9968832646
shivendra_p@rediffmail.com, skpandey@fsm.ac.in
and
Dr. Raj Devasagayam
Professor of Marketing and Management
Siena College
Colbeth 113
Loudonville, NY 12211
518-782-6863
raj@siena.edu
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Responsiveness as Antecedent of Satisfaction and Referrals in Financial Services
Marketing
ABSTRACT
Financial institutions across the globe are still recovering from the meltdown of 2008 and
several nations continue their struggle to stabilize national economies. However, there might be
some important lessons to be learnt from this debacle. Some economies, notably the emergent
ones, were more resilient to this slowdown than the developed ones. In fact, the banking sector in
some of these economies posted a robust growth in spite of the downturn in global banking. We
report on a detailed study of a multinational bank operating in the emergent economy of India
with a random national sample of over 9000 of their customers. Our research provides valuable
insights into a market driven bank’s drive for customer satisfaction and referrals, and examines
antecedents and consequences of such initiatives. We provide empirical evidence suggesting that
responsiveness to customer enquiries and complaints might be a strong driver of customer
satisfaction, irrespective of the outcome of the resolution process. Our finding that
responsiveness supersedes a positive outcome in service provider-customer conflict resolution, is
a contribution of this research to extant literature with important strategic and managerial
implications for firms.
INTRODUCTION
As these words are being penned, the European Union is in the process of resuscitating
the economy of Greece from aftershocks of the global meltdown. However, the economic
headlines from India seem to be in complete contrast with the banking industry in other parts of
the world. For instance, a Wall Street Journal report from 2009 indicated that India (along with
Turkey and Argentina) had the best-performing financial benchmark indexes in their respective
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regions. The report alluded to a strong and vibrant democracy driving the Indian financial sector
in addition to the profitability of banks. This comes as a surprise to most of us in the USA where
banks pleaded for aid from the Federal Government to maintain liquidity. Contrast this also with
not just a transitory event but a trend in India, lending by foreign banks in India increased by
16.9% in 2008 while lending by private-sector banks rose 11.8% in 2008, although these lending
numbers are about half of the previous year, most analysts are astonished by this performance
(WSJ March 30, 2009). The State Bank of India (SBI) which is India's largest nationalized bank
by assets and is 60% owned by the government, has remained focused on its mission to serve
rural India and its consumers – small, but many. An estimated 800 million Indians comprise the
rural marketplace. This commitment to customer satisfaction has yielded great results, deposit
base at SBI rose by close to 40% in the three months ended Dec. 31, 2008! Now, SBI is on a
lending spree (a rise of 29% over the previous year), lowering interest rates, gaining customers
from competitors and leading the nation in keeping India’s financial sector from joining the
global slowdown. The 200 year old bank is busy building its brand identity by repainting its
branches with a uniform color scheme, has invested in customer comfort by adding air
conditioning and televisions. Further SBI is reiterating its commitment to customer service by
implementing an electronic token system to serve customers more effectively and efficiently.
Service quality improvements include a simple smile to be offered along with financial services,
a customer-friendly orientation of the service providers.
It seems like the rest of the world may find lessons in the Indian experience with
retaining customer confidence, building trust, and assuring customer satisfaction. Our research
provides some insights into the Indian banking sector’s drive for customer satisfaction and looks
at some of the antecedents and consequences of such initiatives. Datamonitor (2006) report says
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that many customers are increasingly skeptical of the service that banks provide and are more
and more willing to change provider to get the right kind of service they want. The banking
industry is trying out new and innovative initiatives to impress the consumer. Customer
satisfaction is no longer the benchmark but many marketers have coined the term customer
delight – delivering quality service beyond customer expectations. The banks are also trying to
embrace the concept of customer advocacy where they act in the best interest of the customers
even though it may mean lesser profits in the short run. The importance of customers and their
experience is enhanced even more in services industry because of the intangibility of banking
services. Terms like customer relationship management have given way to customer experience
management (Rahman 2006, for instance) and companies are trying to maximize the satisfaction
derived at each customer touch point. The post purchase behavior of customers has gained
enormous importance in this scenario, especially with the unsatisfied customers (Devasagayam
and DeMars 2004, Hogarth et al 2001). The banking industry has faced one of the toughest
challenges of recession in the recent past. Some of the biggest names were unable to survive this
catastrophe and some more are in the danger zone. Indian regulators and the Reserve Bank (the
central bank in India) were proactive which prevented any major mayhem in the industry but the
customer confidence was certainly shaken, especially among the private players. The
nationalized banks such as the aforementioned SBI, gained from this loss of confidence in
private banks. SBI’s financial benchmarks and results bear ample testimony to this effect. In any
case, the customer’s satisfaction holds the key to long term sustainability and profitability but
banks realize these hard facts better in troubled times.
This paper uses empirical evidence from one of the largest multinational banks operating
in India to underscore some of the conceptual foundations and learning tenets of customer
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satisfaction and customer complaints resolution mechanism in enhancing overall performance of
the banking sector. We contribute to the extant knowledge in not only examining the relationship
between complaint resolution, customer satisfaction, and possibility of generating referrals, but
also in providing evidence that indicates the importance of firm responsiveness over the outcome
of conflict resolution process. In other words, the outcome of the complain resolution being
positive or negative is shown to have little bearing on the level of satisfaction when compared to
the responsiveness of the firm in resolving the issue.
In the following section we examine the past research in this stream of enquiry; we then
proceed to delineate our research objectives. In the subsequent section we describe our
methodology, followed by a discussion of our findings. We conclude with limitations and future
research avenues that emerge as a result of this research.
PAST LITERATURE
An article in the banking wire (2008) which quoted Forrester Research survey indicated
that among nine industries in the survey, banking industry finished near the bottom of the heap in
customer loyalty. The financial services marketing literature has examined the notion of
customer satisfaction with considerable breadth and depth. Aksoy et al (2008) posit that
customer satisfaction is a valuable intangible asset that generates positive returns. They showed
that investing in a portfolio of firms with high and increasing customer satisfaction is far superior
to investing in a portfolio of firms with low and decreasing customer satisfaction. Furthermore, it
also beats the S&P 500 index. The results remained similar even after adjusting for risk and these
are similar to the findings of previous studies of this nature. Luo and Homburg (2007) found a
fascinating result that marketing efforts to enhance customer satisfaction not only make
employees feel good about their employer, but may improve employee’s future performance.
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Since our study focuses on the emergent economy of India, we specifically focus on
some of the past research from this country. Jham and Khan (2008) in an empirical study on
Indian banking customer in the region of UP, Delhi and NCR provided evidence that satisfaction
results in building better relationships with customers through better services. They concluded
that a standardized global strategy affecting performance may not be valid in India, rather banks
need to develop unique relationship marketing strategies based on the regions they serve. They
inferred that since the nature of services is such that interaction of the external customer with the
internal customer is essential, satisfaction from these interactions play a very important role in
developing relationships. The results in this research revealed that satisfaction of the customer
varies from bank to bank and from customer to customer. This study also provided evidence that
customer satisfaction affects banks' sales and profitability.
An article published in Mortgage Banking (2008) quoted a JD Powers' 2008 Home Equity
Line/Loan Origination Study finding that there are five key performance indicators for lenders
that are critical to satisfying customers— approving applications and providing customers with
access to their funds quickly; setting and meeting expectations during the application approval
process; avoiding surprising the customer during the origination process; being versatile and
flexible in the location of the closing; and being mindful of the pitfalls of using a mortgage
broker. The author (Ryan 2008) noted that lenders that perform well in these performance
indicators tend to increase their percentage of highly committed customers, who are more than
twice as likely to recommend their lender to others and to reuse their current lender for their next
home-equity or mortgage product. In turn, this growth can help these lenders outperform their
competitors over time.
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Mazur (2007) quoted Informa Research Services findings who sampled 2,863 American
consumers nationwide to find out how they viewed banks and credit unions. The results showed
that smaller institutions such as community banks received higher ratings for customer
satisfaction and loyalty than larger institutions with deposits above $50 billion, with notable
exceptions being Washington Mutual (WaMu), SunTrust, and Wachovia. Eskildsen and
Kristensen (2007) provided evidence of a clear relationship between the perceived transparency
and the perceived value. The study also indicated that the relationship differs between industries
since the companies from the three different industries form distinct clusters. The analysis of
individual industries indicated that the relationship between perceived transparency and
perceived value was very strong. A decrease in perceived transparency by 1 index point was
shown to be followed by a decrease in perceived value by 0.75 index points, and subsequently by
a decrease in customer satisfaction.
Clapp (2007) suggests building loyalty is an organizational effort across all customer
contact points and business units. Relationship strength is more important than satisfaction as a
true indicator of loyalty. Customizing the experience of our customers, in-branch and in-home,
impacts the strength of relationship as it builds. Helgesen (2006) study indicated that there seems
to be a positive relationship between customer satisfaction and customer loyalty, and there also
seems to be a positive relationship between customer loyalty and customer profitability. The two
relationships under consideration are both found to be nonlinear. Both the relationship between
customer satisfaction and customer loyalty and the relationship between customer loyalty and
customer profitability seem to be positive at a declining rate.
Solnik (2007) provided information on how banks today are going beyond traditional
methods of collecting and analyzing customer feedbacks to track customer satisfaction. The
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newer methods include customer satisfaction kiosks by Citibank and return postage and emails
of Suffolk Federal Bank. An article in 2005 in the ABA Bank Marketing highlighted the
importance of small things in financial institutions like making a clean sweep of the bank to
remove clutter. According to it a series of small changes can instill a connection with customers
and make them feel welcome, significant and engaged. Many bank branches who participated in
a survey after implementing these small changes found that the customer satisfaction, customer
loyalty and employee engagement increased between 10 and 30%.
Mittal et al. (2005) found that the association between customer satisfaction and longterm financial performance is positive and relatively stronger for firms that successfully achieve
a dual emphasis, successfully achieving both customer satisfaction and efficiency
simultaneously. Lee and Hwan (2005) did a study in Taiwanese banking industry and found that
customer satisfaction directly influences purchase intention; furthermore, service quality also
influences purchase intention. Loyalty to the bank increases with customer purchase intentions,
imperceptibly influencing bank business activity growth and profitability. Viewed from a
managerial model perspective, managers consider that customer satisfaction with service quality
influences profitability while an actual improvement in service quality also influences
profitability. Some perceived service quality discrepancies may exist between the customer and
management aspect models.
Motley (2004) argued that smaller banks have been showing higher scores on customer
satisfaction because of their focus on the day-to-day, people-to-people service protocols. The
larger banks were having a misguided notion that internet banking would replace live bankers.
However, the larger banks have also understood the importance of customer satisfaction and are
improving their customer satisfaction scores.
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Lynn (2000) quoted a Virginia based consulting firm TARP whose 25 year banking
industry research showed twice as many people hear about bad experiences as good ones.
Customers who are dissatisfied with a bank’s attempt to resolve a problem or answer a question
will tell as many as 16 friends about it. Customers who complain and have their complaints
resolved are more brand-loyal than customers who have no complaints. The study also found out
that an increase in loyalty can decrease administrative costs by 10 to 40 percent.
OBJECTIVES OF CURRENT RESEARCH
All these studies make significant contributions in theoretical terms; they fail to provide
practical insights that may lead to successful strategy formulations based on the experiences of
banks in India. Our research focuses on empirical evidence from an international bank in India
that has to compete with a state owned bank which is gaining momentum as a leading
competitor. The experience of this bank provides insights in parsimoniously reducing the
antecedents of customer satisfaction in Indian banking sector to a few manageable variables.
Theoretically our model is based on a hierarchical model posited by Bhattacharya and Singh
(2008) which is attractive to us because it subsumes multiple variables in a neat and manageable
manner. As additional advantage of such a model is that our results will be helpful in drawing
conclusions that lead to clear managerial implications to improve customer satisfaction with a
focused and efficient marketing strategy.
This study attempts to develop a predictive model to examine consumer behavior in
financial services sector based on factors such as customer satisfaction, customer complaints, and
complaint resolution time. The specific research issues we examine relate to the relationship
between customer satisfaction and product recommendation to a friend, customer satisfaction
and case resolution time, optimal time expectations of the customer in complaint and case
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resolution and its impact on resultant customer satisfaction, and finally the impact of increased
customer satisfaction upon propensity to make referrals.
Building on a prior study based on data from 350 customers of scheduled commercial
bank branches in Orissa (India) we opertionalize our key variables. Lenka et al (2009) elicited
information on human, technical, and tangible aspects of service quality, customer satisfaction,
and loyalty. Human aspects of service quality were found to influence customer satisfaction
more than the technical and tangible aspects. In the Indian banking sector, human aspects were
found to be more important than technical and tangible aspects of service quality in influencing
customer satisfaction and promoting and enhancing customer loyalty. In a similar study based on
a grounded theory approach, Bhattacharya and Singh (2008) found that customers used a
hierarchical set of service attributes, consequences of services, and the end state achieved as a
result of the service experience, in ascertaining satisfaction. This hierarchical structure was found
to be both generalizable and stable.
We build our hypothesis based on these findings. In our research, the attribute level deals
with front-line performance on basic service dimensions, the consequence of service is
operationalized as case resolution time (irrespective of outcome of such case considerations), and
the end-state relates to product recommendation to a friend over a period of time. The case
resolution could result in outcomes favorable to the complainant or unfavorable; in both cases we
operationalize the efficiency in terms of time taken to resolve rather than the outcome of the
resolution itself. This is in tune with the standards set by the Reserve Bank of India, the central
bank regulating the operations of banks in India. Based on past literature and evidence, the
following hypotheses were developed to address the research issues:
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H1: There is a significant relationship between case resolution time and customer satisfaction,
irrespective of the outcome of the complaint resolution process.
H2: There is a significant relationship between case resolution time and recommendation to a
friend, irrespective of the outcome of the complaint resolution process.
H3: There is a significant relationship between customer satisfaction and customer willingness to
recommend the bank to a friend.
RESEARCH METHODOLOGY
The larger research study that the data is obtained from was undertaken in the emergent
economy of India for a multinational bank with multiple branches numbering in hundreds
serving both urban and rural populations. The cross sectional data consists of a random sample
of customers that had filed a complaint pursuant to service delivery. Data was collected from
various branches of the bank over a specific time period. The effective sample size consists of
9605 respondents that responded to a telephonic survey, participation was voluntary. Survey
addressed questions about how many times the customer had to call the bank to solve their
complaint and query, based on their experience would they be willing to recommend the bank to
a friend, their overall rating of the satisfaction, etc. The overall satisfaction and the satisfaction
from service items were measured on a five point scale with one being excellent and five being
poor. The recommendation to the friend was measured on a 10 point likelihood scale with 10
being extremely likely and 1 being extremely unlikely. Case resolution time is the number of
days in which the query was resolved and zero meant that the query was resolved on the day of
complaint being raised. The overall satisfaction was measured on a five point scale with 1 being
excellent and 5 being poor. The number of times a person contacted the bank was one for one
time, two for two times, three for three times and four meant more than or equal to four times,
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five meant that the case was not resolved and respondent was provided with the option “can not
recall,” to avoid guessing. Correlation and regression analysis was used to test the hypothesis.
Results are summarized in Table 1.
RESULTS AND DISCUSSION
On an average case resolution time for a complaint is approximately 13 days, which is
well within the prescribed guidelines (30 days) of Reserve Bank of India, the governing federal
body in the financial services sector. There is an ombudsperson-based readressal of grievances
in place if the bank does not reply or the reply is unsatisfactory. Individual banks have their own
ombudsperson to resolve issues as needed, trying to reduce customer dissatisfaction. However,
the standard deviation of case resolution time in the data is high (13.48) with the upper limit
going as high as six months (198 days). Some of the satisfaction data (at least for some in our
sample) will be influenced by this statistic, as we proceed with further analysis. Data suggests
that respondents have been active in good word of mouth publicity with a rating of 7 on a 10point scale. This is an important factor for any marketer because the influence of peers in choice
decisions, especially in a high involvement product such as financial services, could make or
break a product. Satisfaction and service ratings of the bank both are close to 2.5 (2- very good
and 3-good) indicating an average response between good and very good. Also, since the
customers are very satisfied from the service of the bank the high recommendation to the friend
is understood. Respondents reported that on an average they had to contact the bank 2.5 times for
complaint resolution, which ideally should be only once for most routine queries and complaints.
Data indicates that more than one service encounters is needed to perform satisfactory service.
The correlation (see Table 2) is significant between all variables and is along expected
lines. Customers whose cases are resolved quickly and had to contact lesser number of times
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were more satisfied with the bank and rate it higher. Also, they are very likely to recommend the
bank to a friend.
We then proceeded to fit ordinary least squares regression models to further test our
hypothesis. Hypothesis 1 found support at the 0.05 level of significance (p: 0.0001; F= 53.898)
and the regression coefficients were found to be significant at the 0.0001 level. The coefficient of
determination was low (6%), but the data fit the model well. Customer satisfaction was seen to
rise as the amount of time taken to resolve a customer complaint was lowered.
Hypotheses 2 and 3 found support at the 0.05 level of significance (p: 0.0001; F =
23610.510) and the regression coefficients were found to be significant at the 0.0001 level. The
coefficient of determination was high (71.1%) and the data fit the model well. Customer
willingness to recommend to a friend was seen to rise as the amount of time taken to resolve a
customer complaint was lowered and customer satisfaction went up.
The model where we regressed the recommend to a friend variable on service rating,
complaint resolution time, contact made, and satisfaction rating was tested for the overall model
fit. The resultant model indicated an excellent fit with a coefficient of determination of 74.5
percent. All the variables loaded significantly at the 0.001 level, with the exception of customer
contact frequency for dispute resolution and query (p: 0.913). The overall model fit was excellent
with F= 7028.830 (p:0.0001).
CONCLUDING REMARKS
We found that customer satisfaction results in better recommendation to friends and thus
helps in bringing more customers to the company. Our findings are in line with those of Jham
and Khan (2008) that an increase in satisfaction was seen to improve the relationship of the
customer with the bank. Our study is also in line with J D Power because we also find that
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resolving the case quickly is very important for the customer and banks should try to reduce this
time by all possible means. Our study also is in sync with Lee and Hwan (2005) study where
they linked customer satisfaction with purchase intention. We also found that customer
satisfaction leads to better recommendations to the friends.
An interesting finding of this study relates to the impact of outcome of the complain
resolution process. Effectively, regardless of the outcome of the process (in favor of the customer
or not), as long as the bank was perceived to be quick in resolving the complaint, respondents
indicated heightened satisfaction. This might seem counterintuitive on the face of it; however,
given a population of more than a billion individuals being served in India, one can empathize
with the customer merely clamoring to be heard! It seems like the respect shown a customer by
merely being responsive far outweighs the actual outcome of the process. This leads to us
suggesting future research in the area of comparing this particular aspect with a more developed
economy, one with fewer customers being served by larger number of banks.
As with most survey based research, despite our large sample size we caution the readers
to be pragmatic in drawing conclusions based on a small sample from a very large emergent
economy of India. Although multiples of hundreds of branches were involved in the study, only
one bank (albeit a leader among the largest multinational banks in India and indeed the world)
was involved in the study. Generalization of results to other emergent economies might be an
erroneous extension of our results. These limitations also open up new vistas of enquiry,
comparative studies across other banks within India and then comparative studies between India
and other emergent economies seem to be the natural offshoot of our research. Further
researchers can probe the monetary implications on the firm based on our variables of interest in
this study, the cost to benefit analysis of such marketing expenditure will add to the popular
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stream of research on “Return on Marketing (ROM)”. In summary, our findings are of interest to
managers and scholars alike and present a first step in what should be a rich and rewarding
stream of research in the global financial services marketing sector.
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Table 1: Descriptive Statistics
N
Case resolution time (in
9605
days)
Recommend to a Friend
Times contacted
Service Rating
Satisfaction
Min
.00
Max
198.0
0
Mean
Std. Dev.
12.7041
13.48538
9605
1.00
10.00
7.1498
3.17032
9605
1.00
6.00
2.4454
1.62647
9605
9605
1.00
1.00
5.00
5.00
2.5324
2.5185
1.50769
1.51612
Table 2: Correlations
CRT
Pearson
Correlation
CRT
Recommend
Service
friend
Contact rating* Satisfaction*
1.000
-.067**
.076**
-.077**
-.075**
.000
.000
.000
.000
1.000
-.493**
.843**
.843**
.000
.000
.000
1.000
-.547**
-.530**
.000
.000
1.000
.908**
Sig. (2-tailed)
Recommend friend
Contact
Service rating
Pearson
Correlation
Sig. (2-tailed)
-.067**
Pearson
Correlation
Sig. (2-tailed)
Pearson
Correlation
Sig. (2-tailed)
.076**
-.493**
.000
.000
-.077**
.843**
-.547**
.000
.000
.000
.000
Satisfaction
.000
Pearson
-.075** .843**
-.530** .908** 1.000
Correlation
Sig. (2-tailed)
.000
.000
.000
.000
**Correlation is significant at the 0.01 level (2-tailed). *Satisfaction and Service Rating are
recoded for consistence of directionality.
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10th Global Conference on Business & Economics
ISBN : 978-0-9830452-1-2
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October 15-16, 2010
Rome, Italy
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