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Marketing Research - Summary Books
Marketing Research for E&BE (Rijksuniversiteit Groningen)
StudeerSnel wordt niet gesponsord of ondersteund door een hogeschool of universiteit
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Marketing Research
Malhotra Chapter 2.
Problem definition  a broad statement of the general problem and identification of the
specific components of the marketing research problem.  only when the marketing
research problem is clearly defined can research be designed and conducted properly. Of all
the tasks in a marketing research project, none is more vital to the ultimate fulfillment of a
client’s needs than a proper definition of the research problem.
The tasks involved in problem definition consist of discussions with the decision makers,
interviews with industry experts and other knowledge individuals, analysis of secondary
data and sometimes qualitative research.
Primary data – is data originated by the researcher for the specific purpose of addressing
the research problem.
Secondary data – are data collected for some purpose other than the problem at hand,
economical and quick source of background information  such as information by
government sources, commercial marketing research firms and computerized databases.
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Primary data should not be collected until the available secondary data has been
fully analyzed.
Qualitative research  an unstructured, exploratory research methodology based on small
samples intended to provide insight and understanding of the problem setting.
Pilot surveys  surveys that tend to be less structured than large-scale surveys in that they
generally contain more open-ended questions and the sample size is much smaller.
Case studies  involve an intensive examination of a few selected cases of the
phenomenon of interest. Cases could be customers, stores or other units.
Environmental context of the problem  consists of the factors that have an impact on the
definition of the marketing research problem, including past information and forecasts,
resources and constraints of the firm, objectives of the decision maker, buyer behavior,
legal environment, economic environment and marketing and technological skills of the
firm.
Past Information and Forecasts of trends with respect to sales, market share, profitability,
technology, population, demographics and lifestyle can help the researcher understand the
underlying marketing research problem.
Resources and Constraints  to formulate a marketing research problem of appropriate
scope, it is necessary to take into account both the resources available, such as money and
research skills, and the constraints on the organization, such as cost and time.
Decisions are made to accomplish objectives  goals of the organization and of the
decision maker must be considered in order to conduct successful marketing research.
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Buyer behavior  a body of knowledge that tries to understand and predict consumers’
reactions based on an individual’s specific characteristics. The buyer behavior factors that
should be considered include:
1. The number and geographical location of the buyers and nonbuyers
2. Demographic and psychological characteristics
3. Product consumption habits and the consumption of related product categories
4. Media consumption behavior and response to promotions
5. Price sensitivity
6. Retail outlets patronized
7. Buyer preferences
Legal environment  regulatory policies and norms within which organizations must
operate.
Economic environment  consist of income, prices, savings, credit and general economic
conditions.
Marketing and Technological Skills  also affect the nature and scope of the marketing
research project.
Management Decision Problem (MDP)  the problem confronting the decision maker. It
asks what the decision maker needs to do.
Marketing Research Problem (MRP)  a problem that entails determining what
information is needed and how it can be obtained in the most feasible way.
 Conceptual map  a way to link the broad statement of the marketing research
problem to the management decision problem.
Defining the MRP
1. Allow the researcher to obtain all the information needed to address the
management decision problem
2. Guide the researcher in proceeding with the project
Two common errors:
1. Defining the problem too broadly  no clear guidelines for the subsequent steps
involved in the project.
2. Defining the problem too narrowly  may preclude consideration of action,
particularly those that are innovative and may not be obvious. It may also prevent
the researcher of addressing important components of the management decision
problem.
The likelihood of committing either type of error in problem definition can be reduced by
stating the marketing research problem in broad, general terms and identifying its specific
components.
Broad Statement  the initial statement of the MRP that provides an appropriate
perspective on the problem.
Specific Components  the second part of the MRP definition. The specific components
focus on the key aspects of the problem and provide guideline on how to proceed further
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Components of the approach  should include objective/theoretical framework, analytical
models, research questions, hypotheses and specification of information needed
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Objective/Theoretical Framework
o Theory – a conceptual scheme based on foundational statements, or axioms,
that are assumed to be true.
o Objective evidence – unbiased evidence that is supported by empirical
findings
Analytical model  an explicit specification of a set of variables and their
interrelationships designed to represent some real system or process in whole or in
part.
o Verbal models – analytical models that provide written representation of the
relationships between variables.
o Graphical models – analytical models that provide a visual picture of the
relationships between variables.
o Mathematical models – analytical models that explicitly describe the
relationships between variables, usually in equation form.
Research Questions  are refined statements of the specific components of the
problem.
Hypothesis  an unproven statement or proposition about a factor or phenomenon
that is of interest to the researcher.
Ethics in Marketing research  ethical issues arise if the proves of defining the problem
and developing an approach is compromised by the personal agendas of the client or the
researcher.
Malhotra Chapter 3.
Research design  a framework or blueprint for conducting the marketing research project.
It specifies the details of the procedures necessary for obtaining the information needed to
structure and/or solve marketing research problems.
 Classification
o Exploratory research  one type of research design, which has its primary
objective the provision of insights into and comprehension of the problem
situation confronting the researcher.
o Conclusive research  research designed to assist the decision maker in
determining, evaluating and selecting the best course of action to take in a
given situation.
 Descriptive research  a type of conclusive research that has as its
major objective the description of something  usually market
characteristic or function
The six Ws:
1. Who
2. What
3. When
4. Where
5. Why
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6. Way
Cross-Sectional Designs  a type of research design involving the collection of information
from any given sample of population elements only once.
 Single cross-sectional design  cross sectional design in which one sample of
respondents is drawn from the target population and information is obtained from
this sample once.
 Multi cross-sectional design  cross sectional design in which there are two or
more sample of respondents, and information from each sample is obtained only
once.
 Cohort analysis  A multiple cross-sectional design consisting of a series of surveys
conducted at appropriate intervals. The cohort refers to the group of respondents
who experience the same event within the same time interval.
Longitudinal Designs  a type of research design involving a fixed sample of population
elements that is measured repeatedly. The sample size remains the same over time, thus
providing a series of pictures that, when viewed together, portray a vivid illustration of the
situation and the changes that are taking place over time.
 Panel – a sample of respondents who have agreed to provide information at
specified intervals over an extended period.
Causal Research  a type of conclusive research where the major objective is to obtain
evidence regarding cause-and-effect (causal) relationships.
Potential Sources of Error
 Total error  the variation between the true mean value in the population of the
variable of interest and the observed mean value obtained in the marketing research
project
 Random sampling error  the error due to the particular sample selected being an
imperfect representation of the population of interest. It may be defined as the
variation between the true mean value for the sample and the true mean value of
the population
 Non-sampling error  errors that can be attributed to sources other than sampling,
and they can be random or non-random
 Non-response error  error that occurs when some of the respondents include in
the sample do not respond. This error may be defined as the variation between the
true mean value of the variable in the original sample and the true mean value in the
net sample.
 Response error  error arising from respondents who do respond, but give
inaccurate answers or their answers are mis-recorded or mis-analyzed. It may be
defined as the variation between the true mean value of the variable in the net
sample and the observed mean value obtained in the marketing research project.
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Budgeting and Scheduling  management tools needed to help ensure that the marketing
research project is completed within the available resources.
 Critical path method (CPM) – management technique of dividing a research project
into component activities, determining the sequence of these components and the
time each activity will require.
 Program evaluation and review technique (PERT) – A more sophisticated critical
path method that accounts for the uncertainty in project completion times.
 Graphical evaluation and review technique (GERT) – A sophisticated critical path
method that accounts for the completion probabilities and the activity costs.
Marketing Research Proposal  the official layout of the planned marketing research
activity for management. It describes the research problem, the approach, the research
design, data analysis methods and reporting methods.
International Marketing Research  due to environmental differences, the research design
appropriate for one country may not be suitable in another.
Ethics in Marketing Research  During the research design stage, not only are the concerns
of the researcher and the client involved, but the rights of the respondents must also be
respected. Although there usually isn’t any direct contact between the respondent and the
other stakeholders (client and researcher) during research design, this is the stage when
decisions with ethical ramifications, such as using hidden video or audio tape recorders, are
made. The researcher should design the study so as not to violate the respondents’ right to
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safety, right to privacy, or right to choose. Furthermore, the client must not abuse its power
to jeopardize the anonymity of the respondents.
Malhotra Chapter 4.
Classification of Secondary data
 Internal data  data available within the organization for which the research is
being conducted
 External data  originated external to the organization
Database Marketing  involves the use of computers to capture and track customer
profiles and purchase detail.
Classification of Computerized Databases
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Syndicated Data from Households
International Marketing Research
Ethics in Marketing Research  the researcher is ethically obligated to ensure the
relevance and usefulness of secondary data to the problem at hand. Only data judged to be
appropriate should be used. It is also important that the data were collected using
procedures that are morally appropriate. Data may be judged unethical if they were
gathered in a way that harms the respondents or invades their privacy. Ethical issues arise if
the users of secondary data are unduly critical of the data that do not support their interests
and viewpoints.
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A Concept Map of Secondary Data
A Concept Map for Syndicated Data
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Malhotra Chapter 5.
Primary Data: Qualitative vs. Quantitative Research
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Qualitative research – An unstructured, exploratory research methodology based on
small samples that provides insights and understanding of the problem setting.
Quantitative research – A research methodology that seeks to quantify the data and
typically, applies some form of statistical analysis.
o Sometimes qualitative research is undertaken to explain the findings
obtained from quantitative research.
Rationale for Using Qualitative Research  It is not always possible, or desirable, to use
fully structured or formal methods to obtain information from respondents. People may be
unwilling or unable to answer certain questions. People are unwilling to give truthful
answers to questions that invade their privacy, embarrass them, or have a negative impact
on their ego or status. Second, people may be unable to provide accurate answers to
questions that tap their subconscious. The values, emotional drives, and motivations
residing at the subconscious level are disguised from the outer world by rationalization and
other ego defenses.
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A Classification of Qualitative Research Procedures
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Direct approach  one type of qualitative research in which the purposes of the
project are disclosed to the respondent or are obvious, given the nature of the
interview
Indirect approach  a type of qualitative research in the purposes of the project are
disguised from respondents
Focus group  an interview conducted by a trained moderator among a small group
of respondents in an unstructured and natural manner.
Depth interview  an unstructured, direct, personal interview in which a single
respondent is probed by a highly skilled interviewer to uncover underlying
motivations, beliefs, attitudes and feelings on a topic.
o Techniques
 Laddering  a technique for conducting depth interviews in which a
line of questioning proceeds from product characteristics to user
characteristics.
 Hidden issue questioning  a type of depth interview that attempts
to locate personal sore spots related to deeply felt personal concerns.
 Symbolic analysis  a technique for conducting depth interviews in
which the symbolic meaning of objects is analyzed by comparing them
with their opposites.
o Grounded theory  an inductive and more structured approach in which
each subsequent depth interview is adjusted based on the cumulative
findings from previous depth interviews with the purpose of developing
general concepts or theories.
o Protocol interview  a respondent is placed in a decision-making situation
and asked to verbalize the process and the activities that he or she would
undertake to make the decision.
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o Projective technique  an unstructured and indirect form of questioning that
encourages the respondents to project their underlying motivations, beliefs,
attitudes, or feelings regarding the issues of concern.
o Association techniques  a type of projective technique in which the
respondent is presented with a stimulus and asked to respond with the first
thing that comes to mind.
 Word association  respondents are presented with a list of words,
one at a time. After each word, they are asked to give first word that
comes to mind.
o Completion technique  the respondents are asked to complete an
incomplete stimulus situation
 Sentence completion or story completion
o Construction techniques  require respondent to construct a response in the
form of a story, dialogue or description
 Picture response technique  tell a story by looking into a picture
 Cartoon test  what the character might say?
o Expressive techniques  the respondent is presented with a verbal or visual
situation and asked to relate the feeling and attitudes of other people to the
situation
 Role playing and third-person technique
Analysis of Qualitative Data
Three general steps:
1. Data reduction. In this step, the researcher chooses which aspects of
the data are emphasized, minimized or set aside for the project at
hand.
2. Data display. In this step, the researcher develops a visual
interpretation of the data with the use of such tools as a diagram,
chart or matrix. The display helps to illuminate patterns and
interrelationships in the data.
3. Conclusion drawing and verification. In this step, the researcher
considers the meaning of analyzed data and assesses its implications
for the research question at hand.
Software Packages  can be used to assist in the analysis of qualitative data.
1. Coding
2. Memoing/Annotation
3. Data Linking
4. Search and Retrieval
5. Conceptual/Theory Development
6. Data Display
7. Graphics Editing
International Marketing Research  Qualitative research may reveal the differences
between the foreign and domestic markets
Ethics in Marketing Research  When conducting qualitative research, ethical issues
related to the respondents and the general public are of primary concern. These issues
include disguising the purpose of the research and the use of deceptive procedures,
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videotaping and recording the proceedings, the comfort level of the respondent and
misusing the findings of qualitative research.
Concept Map for Qualitative Research
Malhotra Chapter 6.
Survey Methods  a structured questionnaire given to a sample of a population and
designed to elicit specific information from respondents.
 Structured data collection – use of formal questionnaire that presents questions in a
prearranged order
 Fixed-alternative questions – questions that require respondents to choose from a
set of predetermined answers
Personal Methods  in-home, mail-intercept or computer assisted
Electronic Methods  e-mail or administered on the Internet or the Web
A Comparative Evaluation of Survey Methods
 Sample control – the ability of the survey mode to reach the units specified in the
sample effectively and efficiently.
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Sampling frame – A representation of the elements of the target population. It
consists of a list or set of directions for identifying the target population.
Random digit dialing (RDD) – a technique used to overcome the bias of unpublished
and recent telephone numbers by selecting all telephone number digits at random.
Random digit directory design – a research design for telephone surveys in which a
sample of numbers is drawn from the telephone directory and modified to allow
unpublished numbers a chance of being included in the sample.
A Concept Map for Quantitative Descriptive Data
Malhotra Chapter 8.
Measurement and Scaling
 Measurement means assigning numbers or other symbols to characteristics of
objects according to certain prespecified rules. Note that what we measure is not
the object, but some characteristic of it. Thus, we do not measure consumers—only
their perceptions, attitudes, preferences, or other relevant characteristics; First,
numbers permit statistical analysis of the resulting data. Second, numbers facilitate
the communication of measurement rules and results
 Scaling involves creating a continuum upon which measured objects are located.
Description  the unique labels or descriptors that are used to designate each value of the
scale. All scales possess description.
Order  the relative sized or positions of the descriptors. Order is denoted by descriptors
such as greater than, less than and equal to.
Distance  the characteristic of distance means that absolute differences between the
scale descriptors are known and may be expressed in units.
Origin  the origin characteristic means that the scale has a unique or fixed beginning or
true zero point
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Primary Scales of Measurement
Nominal scale  a scale whose numbers serve only as labels or tags for identifying and
classifying objects. When used for identification, there is a strict one-to-one correspondence
between the numbers and the objects.
Ordinal scale  a ranking scale in which numbers are assigned to objects to indicate the
relative extent to which some characteristics is possessed. Thus, it is possible to determine
whether an object has more or less of a characteristic than some other object.
Interval scale  a scale in which the numbers are used to rate objects such that numerically
equal distances on the scale represent equal distances in the characteristic being measured.
Ratio scale  The highest scale. It allows the researcher to identify or classify objects, rankorder the objects and compare interval or differences. It is also meaningful to compute
ratios of scale values.
A Comparison of Scaling Techniques
Comparative scales  one of two types of scaling techniques in which there is direct
comparison of stimulus objects with one another.
Noncomparative scales  one of two types of scaling techniques in which each stimulus
object is scaled independently of the other objects in the stimulus set.
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Comparative Scaling Techniques
Paired comparison scaling  a comparative scaling technique in which a respondent is
presented with two objects at a time and asked to select one object in the pair according to
some criterion. The data obtained are ordinal in nature.
 Transitivity of preference  an assumption made in order to convert paired
comparison data to rank order data. It implies that if brand A is preferred to brand B
and brand B is preferred to brand C, then brand A is preferred to brand C.
o Rank order scaling  A comparative scaling technique in which respondents
are presented with several objects simultaneously and asked to order or rank
them according to some criterion;
 advantage is that most respondents easily understand the instructions
for ranking. The major disadvantage is that this technique produces
only ordinal data.
o Constant Sum Scaling  a comparative scaling technique in which
respondents are required to allocate a constant sum of units such as points,
dollars, chits, stickers or chips among a set of stimulus object with respect to
some criterion.
 The main advantage of the constant sum scale is that it allows for fine
discrimination among stimulus objects without requiring too much
time. However, it has two primary disadvantages. Respondents may
allocate more or fewer units than those specified; Another potential
problem is rounding error if too few units (e.g., points) are used.
Q-Sort scaling  a comparative scaling technique that uses a rank order procedure to sort
objects based on similarity with respect to some criterion.
Ethics in Marketing Research
The researcher has the responsibility to use the appropriate type of scales to get the data
needed to answer the research questions and test the hypotheses.
A Concept Map for Primary Scales
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Malhotra Chapter 9.
Noncomparative Scaling Techniques  one of two types of scaling techniques in which
each stimulus object is scaled independently of the other objects in the stimulus set.
Continuous Rating Scale  also referred to as graphic rating scale, this measurement scale
has the respondents rate the objects by placing a mark at the appropriate position on a line
that runs from one extreme of the criterion variable to other.
Itemized Rating Scales  a measurement scale having numbers and/or brief descriptions
associated with each category. The categories are ordered in terms of scale position.
Likert Scale  a measurement scale with five response categories ranging from “strongly
disagree” to “strongly agree”, which requires the respondents to indicate a degree of
agreement or disagreement with each of a series of statements related to the stimulus
objects.
Semantic Differential Scale  a 7-point rating scale with endpoints associated with bipolar
labels that have semantic meaning.
Stapel Scale  a scale for measuring attitudes that consists of a single adjective in the
middle of an even-numbered range of values, from -5 to +5, without a neutral point (zero).
Noncomparative Itemized Rating Scale Decisions  six major decisions
1. The number of scale categories to use  Two conflicting considerations are involved
in deciding the number of scale categories. The greater the number of scale
categories, the finer the discrimination among stimulus objects that is possible. On
the other hand, most respondents cannot handle more than a few categories. If the
respondents are interested in the scaling task and are knowledgeable about the
objects, a larger number of categories may be employed.
2. Balanced versus unbalanced scale  balanced scale – a scale with an equal number
of favorable and unfavorable categories - In general, the scale should be balanced in
order to obtain objective data. However, if the distribution of responses is likely to
be skewed, either positively or negatively, an unbalanced scale with more categories
in the direction of skewness may be appropriate.
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3. Odd or even number of categories  With an odd number of categories, the middle
scale position is generally designated as neutral or impartial The decision to use an
odd or even number of categories depends on whether some of the respondents
may be neutral on the response being measured.
4. Forced versus non-forced choice  forced rating scales – that forces the
respondents to express an opinion because “no opinion” or “no knowledge” option
is not provided.
5. The nature and degree of the verbal description  Scale categories may have verbal,
numerical, or even pictorial descriptions. Furthermore, the researcher must decide
whether to label every scale category, some scale categories, or only extreme scale
categories. Surprisingly, providing a verbal description for each category may not
improve the accuracy or reliability of the data
6. The physical form of the scale
Multi-Item Scales  consists of multiple items, where an item is a single question or
statement to be evaluated. The researcher begins by developing the construct of interest.
Next, the researcher must develop a theoretical definition of the construct that states the
meaning of the central idea or concept of interest. For this, we need an underlying theory of
the construct being measured.
 Construct  a specific type of concept that exists at a higher level of abstraction
than do every day concepts.
Measurement Accuracy
 Measurement error  the variation in the information sought by the researcher and
the information generated by the measurement process employed.
 True score model  a mathematical model that provides a framework for
understanding the accuracy of measurement.
 Systematic error  affects the measurement in a constant way and represents
stable factors that affect the observed score in the same way each time the
measurement is made.
 Random error  measurement error that arises from random changes or
differences in respondents or measurement situations.
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Reliability  the extent to which a scale produces consistent results if repeated
measurements are made on the characteristic.
 Test-retest reliability  an approach for assessing reliability in which respondents
are administered identical sets of scale items at two different times under as nearly
equivalent conditions as possible
 Alternative-forms reliability  an approach for assessing reliability that requires
two equivalent forms of the scale to be constructed and then the same respondents
are measured at two different times.
 Internal consistency reliability  an approach for assessing the internal consistency
of the set of items when several items are summated in order to form a total for the
scale
 Split-half reliability  a form of internal consistency reliability in which the items
constituting the scale are divided into two halves and the resulting half scores are
correlated
 Coefficient alpha  a measure of internal consistency reliability that is the average
of all possible split-half coefficients resulting from different splattings’ of the scale
items.
Validity  the extent to which differences in observed scale scores reflect true differences
among objects on the characteristic being measured, rather than systematic or random
errors.
 Content validity  a type of validity, sometimes called face validity, that consists of
a subjective but systematic evaluation of the representativeness of the content of a
scale for the measuring task at hand.
 Criterion validity  a type of validity that examines whether the measurement scale
performs as expect in relation to other variables selected as meaningful criteria.
 Construct validity  a type of validity that addresses the question of what construct
or characteristic the scale is measuring. An attempt is made to answer theoretical
questions of why a scale works and what deductions can be made concerning the
theory underlying the scale.
 Convergent validity  a measure of construct validity that measures the extent to
which the scale correlates positively with other measures of the same construct.
 Discriminant validity  a type of construct validity that assesses the extent to which
a measure does not correlate with other constructs from which it supposed to differ.
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Nomological validity  a type of validity that assesses the relationship between
theoretical constructs. It seeks to confirm significant correlations between the
constructs as predicted by theory.
Relationship Between Reliability and Validity - The relationship between reliability and
validity can be understood in terms of the true score model. If a measure is perfectly valid, it
is also perfectly reliable. In this case XO XT, XR 0, and XS 0. Thus, perfect validity implies
perfect reliability
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Generalizability  the degree to which a study based on a sample applies to a universe of
generalizations.
Choosing scaling techniques  As a general rule, using the scaling technique that will yield
the highest level of information feasible in a given situation will permit the use of the
greatest variety of statistical analyses; whenever feasible, several scale items should
measure the characteristic of interest.
Ethics in Marketing Research  The researcher has the ethical responsibility to use scales
that have reasonable reliability, validity, and generalizability. The findings generated by
scales that are unreliable, invalid, or not generalizable to the target population are
questionable at best and raise serious ethical issues
A Concept Map for Non-comparative Scales
Malhotra Chapter 10
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Questionnaires and Observation Forms
Questionnaire - A structured technique for data collection that consists of a series of
questions, written or verbal, that a respondent answer. Any questionnaire has three specific
objectives. First, it must translate the information needed into a set of specific questions
that the respondents can and will answer. Second, a questionnaire must uplift, motivate,
and encourage the respondent to become involved in the interview, to cooperate, and to
complete the interview. Third, a questionnaire should minimize response error.
Questionnaire Design Process  The great weakness of questionnaire design is lack of
theory. Because there are no scientific principles that guarantee an optimal or ideal
questionnaire, questionnaire design is a skill acquired through experience. It is an art rather
than a science.
Individual Question Content
Is the Question Necessary?  Every question in a questionnaire should contribute to the
information needed or serve some specific purpose. If there is no satisfactory use for the
data resulting from a question, that question should be eliminated.
Are Several Questions Needed Instead of One?  Once we have ascertained that a
question is necessary, we must make sure that it is sufficient to get the desired information.
Sometimes, several questions are needed to obtain the required information in an
unambiguous manner.
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Double-barreled question  A single question that attempts to cover two issues.
Such questions can be confusing to respondents and result in ambiguous responses.
Overcoming Inability to Answer
Researchers should not assume that respondents can provide accurate or reasonable
answers to all questions. The researcher should attempt to overcome the respondents’
inability to answer. Certain factors limit the respondents’ ability to provide the desired
information. The respondents may not be informed, may not remember, or may be unable
to articulate certain types of responses.
Is the Respondent Informed?  Respondents are often asked about topics on which they
are not informed. Research has shown that respondents will often answer questions even
though they are uninformed.
 Filter questions  An initial question in a questionnaire that screens potential
respondents to ensure they meet the requirements of the sample
Can the Respondent Remember?  Many things that we might expect everyone to know
are remembered by only a few
 Telescoping  A psychological phenomenon that takes place when an individual
telescopes or compresses time by remembering an event as occurring more recently
than it actually occurred.
Can the Respondent Articulate?  Respondents may be unable to articulate certain types
of responses. If the respondents are unable to articulate their responses to a question, they
are likely to ignore that question and may refuse to respond to the rest of the
questionnaire. Thus, respondents should be given aids, such as pictures, maps, and
descriptions, to help them articulate their responses.
Overcoming Unwillingness to Answer
Effort Required of the Respondents  Most respondents are unwilling to devote a lot of
effort to provide information. Hence, the researcher should minimize the effort required of
the respondents.
Context  Some questions may seem appropriate in certain contexts but not in others.
Respondents are unwilling to respond to questions that they consider inappropriate for the
given context. Sometimes, the researcher can manipulate the context in which the
questions are asked so that the questions seem appropriate.
Legitimate Purpose  Respondents are also unwilling to divulge information that they do
not see as serving a legitimate purpose. Why should a firm marketing cereal want to know
their age, income, and occupation? Explaining why the data are needed can make the
request for the information seem legitimate and increase the respondents’ willingness to
answer.
Sensitive Information  Respondents are unwilling to disclose, at least accurately, sensitive
information because this may cause embarrassment or threaten the respondent’s prestige
or self-image. If pressed for the answer, respondents may give biased responses, especially
during personal interviews. Sensitive topics include money, family life, political and religious
beliefs, and involvement in accidents or crimes. The techniques described in the following
section can be adopted to increase the likelihood of obtaining information that respondents
are unwilling to give.
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Increasing the Willingness of Respondents:
1. Place sensitive topics at the end of the questionnaire. By then, initial mistrust has
been overcome, rapport has been created, the legitimacy of the project has been
established, and respondents are more willing to give information.
2. Preface the question with a statement that the behavior of interest is common.
3. Ask the question using the third-person technique, phrase the question as if it
referred to other people.
4. Hide the question in a group of other questions that respondents are willing to
answer. The entire list of questions can then be asked quickly.
5. Provide response categories rather than asking for specific figures. Do not ask,
“What is your household’s annual income?” Instead, ask the respondent to check the
appropriate income category: under $25,000, $25,001–$50,000, $50,001–$75,000,
or over $75,000. In personal interviews, give the respondents cards that list the
numbered choices. The respondents then indicate their responses by number.
6. Use randomized techniques. In these techniques, respondents are presented with
two questions, one sensitive and the other a neutral question with a known
probability of a “yes” response (e.g., “Is your birthday in March?”). They are asked to
select one question randomly, for example, by flipping a coin. The respondent then
answers the selected question “yes” or “no,” without telling the researcher which
question is being answered. Given the overall probability of a “yes” response, the
probability of selecting the sensitive question, and the probability of a “yes”
response to the neutral question, the researcher can determine the probability of a
“yes” response to the sensitive question using the law of probability. However, the
researcher cannot determine which respondents have answered “yes” to sensitive
questions.
Choosing Question Structure
Unstructured questions  Open-ended questions that respondents answer in their own
words.
Structured questions  Questions that prespecify the set of response alternatives and the
response format. A structured question could be multiple choice, dichotomous, or a scale.
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
Multiple choice questions
o Order or position bias  A respondent’s tendency to check an alternative
merely because it occupies a certain position or is listed in a certain order.
Dichotomous question  A structured question with only two response alternatives,
such as yes and no.
Scales
Choosing Question Wording
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Question wording is the translation of the desired question content and structure into
words that respondents can clearly and easily understand. Deciding on question wording is
perhaps the most critical and difficult task in developing a questionnaire.
Define the Issue  a question should clearly define the issue being addressed.
Use Ordinary Words  Ordinary words should be used in a questionnaire and they should
match the vocabulary level of the respondents.
Use Unambiguous Words  The words used in a questionnaire should have a single
meaning that is known to the respondents. A number of words that appear to be
unambiguous have different meanings to different people. These include “usually,”
“normally,” “frequently,” “often,” “regularly,” “occasionally,” and “sometimes”.
Avoid Leading or Biasing Questions
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
Leading questions  A question that gives the respondent a clue as to what answer
is desired or leads the respondent to answer in a certain way.
Acquiescence bias  This bias is the result of some respondents’ tendency to agree
with the direction of a leading question (yea-saying).
Avoid Implicit Alternatives  An alternative that is not explicitly expressed in the options is
an implicit alternative. Making an implied alternative explicit may increase the percentage
of people selecting that alternative.
Avoid Implicit Assumptions  Questions should not be worded so that the answer is
dependent upon implicit assumptions about what will happen as a consequence. Implicit
assumptions are assumptions that are not stated in the question.
Avoid Generalizations and Estimates  Questions should be specific, not general.
Moreover, questions should be worded so that the respondent does not have to make
generalizations or compute estimates
Determining the Order of Questions
Opening Questions  The opening questions can be crucial in gaining the confidence and
cooperation of respondents. The opening questions should be interesting, simple, and
nonthreatening. Questions that ask respondents for their opinions can be good opening
questions, because most people like to express their opinions.
Type of information  The type of information obtained in a questionnaire may be
classified as (1) basic information, (2) classification information, and (3) identification
information.
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
Basic information relates directly to the research problem.
Classification information, consisting of socioeconomic and demo- graphic
characteristics, is used to classify the respondents and understand the results.
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
Identification information includes name, postal address, e-mail address, and
telephone number. Identification information may be obtained for a variety of
purposes, including verifying that the respondents listed were actually interviewed,
remitting promised incentives, and so on.
Difficult questions  Difficult questions or questions that are sensitive, embarrassing,
complex, or dull should be placed late in the sequence. After rapport has been established
and the respondents become involved, they are less likely to object to these questions.
Effect on Subsequent Questions  Questions asked early in a sequence can influence the
responses to subsequent questions. As a rule of thumb, general questions should precede
specific questions. This prevents specific questions from biasing responses to general
questions.

funnel approach  A strategy for ordering questions in a questionnaire in which the
sequence starts with general questions that are followed by progressively specific
questions in order to prevent specific questions from biasing general questions.
Logical Order  Questions should be asked in a logical order. All of the questions that deal
with a particular topic should be asked before beginning a new topic. When switching
topics, brief transitional phrases should be used to help respondents switch their train of
thought.

Branching questions  Question used to guide an interviewer through a survey by
directing the interviewer to different spots on the questionnaire depending on the
answers given.
Pretesting  The testing of the questionnaire on a small sample of respondents for the
purpose of improving the questionnaire by identifying and eliminating potential problems.
Lilien et al. Chapter 7
The Marketing Mix  refers to the levers that marketing managers pull to create a
marketing plan
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

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Product
Price
Place
Promotion
Advertising  any paid form of nonpersonal presentation and promotion of ideas, goods,
or services by an identified sponsor.
Direct marketing  the use of mail, telephone, the Internet, and other non-face-to-face
contact tools to communicate with or solicit a response from specific customers and
prospects.
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Sales promotion  short-term incentives to encourage customers to try or purchase a
product or service
Personal selling  face-to-face interactions with one or more prospective customers for the
purpose of making a sale.
Pricing Decision
Price is the only marketing variable that directly affects revenue:
The Classical Economics Approach
For a classical economist  price is the driving force that allocates goods and services in the
marketplace
For the customer  it represents the cost of a purchase in monetary terms
For the producer/seller  helps in determining the level of supply and allocate economic
resources on the production side
Price elasticity:
The classical model relies on several key assumptions that limits its applicability:






The firm’s objective in setting its price is maximizing the short-run profits it can
realize from a particular product.
The only outside parties to consider in setting the price are the firm’s immediate
customers
Price setting occurs independently of the levels set for other variables in the
marketing mix
Demand and cost equations can be estimated with sufficient accuracy
The firm has true control over price; it is a price maker, not a price taker
Market responses to price changes are well understood
Cost-Oriented Pricing
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Many firms set their prices largely or even wholly on the basis of their costs  typically,
they compute all costs, including allocations for overhead expenses, based on expected
operating levels.
Most elementary examples:


Markup
cost-plus pricing
Demand-Oriented Pricing
Demand-oriented approaches observe demand for the product at various price levels and
thereby focus on customer value. It attempts to charge a higher price when demand is
strong and a lower price when demand is weak, even if production costs remain the same.
The Gabor-Granger Method (1964)  simple method to estimate customers’ willingness to
buy at different price points (and interpolate between those price points). It can be viewed
as simple alternative to conjoint analysis, except that it focuses only on price, keeping all
other attributes constant.
Limitations:

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The results are sensitive to how the survey responses are translated into
purchase likelihood.
If the optimal price point falls outside the range of tested price levels, the
model predictions are not reliable, and the study should be conducted again
to include those price levels.
The model does not readily provide margins of error or confidence intervals
for the optimal price level.
An insight from the model is that at the optimal price point, sales never reach maximum
potential. At the price level that optimizes profit, there will always be customers who do not
buy the product because it falls outside their price range. Thus, if no customer complains
that your price are too high, it means your product is priced too low for optimal profit.
Competition-Oriented Pricing
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When a company bases its prices chiefly on what competitors are charging. In the most
common type of competition-oriented pricing, a firm tries to maintain its price at the
average price level charged by the industry, also called going-rate or imitative pricing.
Commonly applied to homogeneous commodities  like oil.  firms have no choice in
setting price
In markets characterized by product differentiation, individual firms have more latitude in
their pricing decisions. Firms make their product and marketing programs compatible within
each pricing zone and respond to competitors’ price changes to maintain their own relative
prices.
Price Discrimination and Revenue Management
If a firm uses demand-based pricing, it faces the issue of how to implement price
discrimination.
A firm trying to implement direct price discrimination in practice faces several difficulties:
1. Identifying customers’ reservation prices is difficult. Rarely are the observable
characteristics of customers closely correlated with their reservation prices, and
firms cannot obtain accurate estimates by simply asking customers how much they
will pay
2. Targeting a particular price at a particular segment is difficult. Most consumer goods,
for example, feature posted prices and thus are available to every customer at an
equal price.
3. Preventing arbitrage is difficult. Customers with low reservation prices may buy up a
lot of the product and supply it to customers with higher reservation prices at a price
higher than what they initially paid but lower than the reservation price of the latter
group.
4. Charging different prices to different segments for an identical product may be illegal
if price differences are based on certain groups, such as gender and race, or if the
price discrimination has the effect of reducing competition in that industry. The
Robinson-Patman Act governs discrimination in business practice in the US.
5. Customers may view price discrimination as unfair. Those who pay a higher price for
an item resent price breaks given to others, unless the firm can position a price break
positively, such as by framing it as a form of charity (senior citizen discounts, student
discounts). In many situations, sellers “throw” other items into the package – free
service, beneficial financing, free software – that make the price discrimination less
obvious and perhaps more acceptable.
To implement price discrimination, the firm must understand how to separate the market
segments and support the price discrimination program through advertising, distribution,
and other marketing instruments. Some of the most common schemes rely on geographic
and temporal variation in pricing, use nonlinear pricing (i.e., base pricing on customer
characteristics), and employ nonprice marketing instruments.
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Pricing Product Lines
Most firms market more than a single product, and if these products are not related,
through either shared costs or interdependent demand, a price discrimination approach
may be appropriate.
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Products in a line may relate to one another on the demand side, whether
substitutes or complements.
Cost interdependencies may mean shared production, distribution, or marketing
expenditures.
Some products might be sold together as a bundle (e.g., stereo system vs. individual
components), which creates complementarities.
The price of one product in a line may influence the buyer’s subjective evaluation of
other products in the line.
Resource Allocation and the Marketing Communications and Promotion Mix
1. How much should we spend in total during a given planning horizon?
2. How should that spending be allocated to each marketing mix element? How much
of our budget should be spent on advertising and other forms of impersonal
marketing communications? On sales promotion? On the sales force?
3. How should those individual budgets be allocated? To customers? To geographies?
To sub-elements of the marketing communications mix? Over time?
Advertising and Impersonal Marketing Communications
Personal selling  more effective than advertising but more expensive, it is most effective
only when the expected level of sales to a single prospect is large
Branding  when a firm carries different brand names, it has to advertise each brand
independently.
Pricing  the copy, or message and media placement of any advertising must reinforce and
be consistent with the brand’s price position.
Distribution channel  to influence wholesaler or retailers, a firm can use two different
strategies: push or pull.


Push strategy  the firm directs its marketing efforts towards salespeople or the
trade industry, with the objective of pushing the product through the distribution
channel
Pull strategy  requires the firm to aim its marketing strategy at the ultimate
consumer in an attempt to stimulate consumer demand, which then pulls
merchandise through distribution channels.
Three major decisions surrounding advertising:
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1. Setting objectives  drive copy decisions and copy effects, vary by response group,
affect media decisions.
2. Developing copy (what message?)
3. Choosing media and vehicles through which the message will be delivers, both on
and offline
Advertising Decision in Practice
Affordable method  Company should spend whatever funds are available for advertising
and use advertising as a form of insurance. The basic weakness of this approach is that it
leads to a fluctuating advertising budget that makes it difficult to plan for a long-range
market development.
Percentage-of-sales method  set advertising expenditures at a specified percentage of
firm sales (either current or anticipated) or the sales price.
Advantages:
Disadvantages:
Expenditures vary with what the company
can afford. It encourages managers to think
in terms of the relationship among
advertising cost, selling price and profit per
unit. It encourages competitive stability by
the extent that competing firms spend
approximately the same percentage of
their sales on advertising.
Percentage-of-sales method really has little
to justify it. It uses circular reasoning; in
that it makes sales the determinant of
advertising rather than its result. It also
leads executives to set advertising
appropriation on the basis of the
availability of funds rather than the
available opportunities. Furthermore, the
model provides no logical basis for
choosing a specific percentage, except
historical precedent, competitors’ actions
or costs. Finally, it does not encourage
firms to appropriate funds for advertising
constructively on a product-by-product or
territory-by-territory basis but instead
suggests that all allocations occur for the
same percentage of sales.
Competitive parity method
Some companies set their advertising budgets specifically to match competitors’ outlays –
that is, to maintain competitive parity. Since competitors’ expenditures represent the
collective of the industry and maintaining competitive parity helps prevent advertising wars.
However, there are no priori grounds that competitors’ use logical methods to determine
their outlays. Knowing what the competition spends on advertising is undoubtably useful
information, but it is one thing to have this information and another to copy it blindly.
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Objective-and-task method
Helps advertisers to develop their budgets by:
1. Defining their advertising objectives as specifically as possible
2. Determining the tasks required to achieve these objectives
3. Estimating the costs of those tasks
Sum of these costs provides the proposed advertising budget. If firms undertake this
method, they should develop their advertising goals as specifically as possible to guide them
when they develop copy, select media, and measure results.
This method enjoys strong appeal and broad popularity among advertisers. However, it
cannot indicate how to choose the specific objectives or how to evaluate them to determine
whether they are worth the cost of attaining them.
Sales Force Decisions
Sales for sizing and allocation
Breakdown method:
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Sales Promotions: Types and effects
Objectives of Promotions
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Lilien et al. Chapter 6
Marketing managers view products at three levels:
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

Core product  the part of the product that satisfies the customer’s central
underlying need or want; the essence or fundamental aspect of a product.
Tangible product  the transformed core product, consisting of features, styling,
quality level, brand name and packaging that make the core product into something
that customers can buy.
Augmented product  enhancements to the tangible product in the form of
additional services and features that make the product attractive, such as toll-free
customer information, installation guides, delivery, warranty or after-sale services.
The product is the most important element of the marketing mix around which all other
aspects of the marketing program revolve.
The new product development process
If a firm decides that a new idea is attractive, it proceeds to the second stage  design.
There the idea is transformed to a physical model, picture or verbal description to denote its
form, features and meaning. During the design stage, managers also seek a better
understanding of the target market segments, explore alternative ways to position the
product in those segments, work with engineers to determine cost-benefit trade-offs for
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various product features, develop and evaluate product prototypes, create initial marketing
plans and generate sales forecasts for selected product designs.
The testing stage comes next, and managers use it to assess whether the product will gain
market acceptance when it is introduced or meet the firm’s profit and market share goal
according to the proposed marketing plan. Testing also offers diagnostic information about
which changes to the product or marketing program might improve its chances of success. If
the various tests indicate success, the firm proceeds to introduce the product.
The fourth stage, actually introducing the product into the market, calls for careful decisions
about coordinating production and marketing plans, fine-tuning the product design for
manufacturability and managing the distribution pipeline. It also requires continuous market
performance monitoring to refine the introductory strategy (e.g. price, advertising copy).
Finally, if the firm successfully introduces a new product, it institutes a life cycle
management plan with the goal of maintain the growth and profitability of the product.
Successful products invite competition, so the firm needs both offensive and defensive
strategies. Successful products also draw a disproportionate percentage of organizational
resources, so the firm needs to undertake portfolio, not just individual product,
management strategies to ensure the short-term and long-term profitability of its entire
portfolio of products.
Models for Idea generation and evaluation
Creativity in NPD requires both divergent (lateral) and convergent thinking. Using divergent
thinking techniques such as free association, brainstorming and synectics, people can
generate many ideas. In the synectics process a facilitator stimulates new thoughts about
familiar things, typically using analogies and metaphors (e.g., “How is music like water?”).
Convergent thinking, in contrast, describes the process used to identify the most promising
of the generated ideas, a step we call idea evaluation.
Creativity Software
Idea generation - several commercial software packages offer support to the creative
process, based on the premise that interactions between people and software enhance
creativity.
Idea evaluation – software programs also can help evaluate new ideas, especially if there
are so many that the task seems overwhelming.
Conjoint analysis for product design
Conjoint analysis uses data pertaining to customers’ overall preferences for a selected
number of product bundles and decomposes them into the utility values (pathworths) that
the customers assign to each level of each attribute. The set of decomposed utility values
thus represents the partworth function.
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How to conduct conjoint analysis
Strengths and Limitations of Conjoint analysis
The following checklist provides guidelines to determine if conjoint analysis is suitable in a
particular decision context:
1. In designing the product, you must make trade-offs among various attributes and
benefits offered to customers.
2. You can decompose the product or service category into basic attributes that
managers can act on and that are meaningful to customers.
3. The existing products are well described as combinations off attribute levels, and
new product alternatives can be synthesized from those basic attribute levels.
4. You can describe the product bundles realistically, either verbally or pictorially. (If
you cannot, consider using actual product formulations for the evaluations.)
A well-executed conjoint study helps marketers distinguish between product attributes that
people say are important and those that are truly important in terms of driving their
preferences or choices.
Malhotra Chapter 7
Concept of Causality
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Conditions for Causality
concomitant variation - A condition for inferring causality that requires that a cause, X, and
an effect, Y, occur together or vary together as predicted by the hypothesis under
consideration.
Time order of occurrence of variables
The time order of occurrence condition states that the causing event must occur either
before or simultaneously with the effect; it cannot occur afterwards. By definition, an effect
cannot be produced by an event that occurs after the effect has taken place. However, it is
possible for each event in a relationship to be both a cause and an effect of the other event.
In other words, a variable can be both a cause and an effect in the same causal relationship.
Absence of Other Possible Causal Factors
The absence of other possible causal factors means that the factor or variable being
investigated should be the only possible causal explanation. In an after-the-fact examination
of a situation, we can never confidently rule out all other causal factors. In contrast, with
experimental designs, it is possible to control for some of the other causal factors. It is also
possible to balance the effects of some of the uncontrolled variables so that only random
variations resulting from these uncontrolled variables will be measured. These aspects are
discussed in more detail later in this chapter.
Role of evidence
Evidence of concomitant variation, time order of occurrence of variables, and elimination of
other possible causal factors, even if combined, still do not demonstrate conclusively that a
causal relationship exists. However, if all the evidence is strong and consistent, it may be
reasonable to conclude that there is a causal relationship. Accumulated evidence from
several investigations increases our confidence that a causal relationship exists. Confidence
is further enhanced if the evidence is interpreted in light of intimate conceptual knowledge
of the problem situation. Controlled experiments can provide strong evidence on all three
conditions.
Definitions and concepts
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independent variables - Variables that are manipulated by the researcher and whose effects
are measured and compared.
test units - Individuals, organizations, or other entities whose response to independent
variables or treatments is being studied.
dependent variables - Variables that measure the effect of the independent variables on
the test units.
extraneous variables - Variables, other than the independent variables, that influence the
response of the test units.
Experiment - The process of manipulating one or more independent variables and
measuring their effect on one or more dependent variables, while controlling for the
extraneous variables.
experimental design -The set of experimental procedures specifying, (1) the test units and
sampling procedures, (2) independent variables, (3) dependent variables, and (4) how to
control the extraneous variables.
Definition of Symbols
Validity of experimentation
Internal validity - A measure of accuracy of an experiment. It measures whether the
manipulation of the independent variables, or treatments, actually caused the effects on the
dependent variable(s)
external validity - A determination of whether the cause-and-effect relationships found in
the experiment can be generalized.
Extraneous Variables
history (H) - Specific events that are external to the experiment but occur at the same time
as the experiment.
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maturation (MA) - An extraneous variable attributable to changes in the test units
themselves that occur with the passage of time.
main testing effect (MT) - An effect of testing occurring when a prior observation affects a
latter observation.
interactive testing effect (IT) - An effect in which a prior measurement affects the test unit’s
response to the independent variable.
instrumentation - An extraneous variable involving changes in the measuring instrument or
in the observers or scores themselves.
statistical regression (SR) - An extraneous variable that occurs when test units with extreme
scores move closer to the average score during the course of the experiment.
selection bias (SB) - An extraneous variable attributable to the improper assignment of test
units to treatment conditions.
mortality (MO) - An extraneous variable attributable to the loss of test units while the
experiment is in progress.
confounding variables - Synonymous with extraneous variables, used to illustrate that
extraneous variables can confound the results by influencing the dependent variable.
Randomization - One method of controlling extraneous variables that involves randomly
assigning test units to experimental groups by using random numbers. Treatment conditions
are also randomly assigned to experimental groups
Matching - One method of controlling extraneous variables that involves matching test units
on a set of key background variables before assigning them to the treatment conditions.
statistical control - One method of controlling extraneous variables by measuring the
extraneous variables and adjusting for their effects through statistical methods.
design control - One method of controlling extraneous variables that involves using specific
experimental designs.
A classification of experimental designs
preexperimental designs - Designs that do not control for extraneous factors by
randomization.
true experimental designs - Experimental designs distinguished by the fact that the
researcher can randomly assign test units to experimental groups and also randomly assign
treatments to experimental groups.
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quasi-experimental designs - Designs that apply part of the procedures of true
experimentation but lack full experimental control.
statistical design - Designs that allow for the statistical control and analysis of external
variables.
Preexperimental Designs
one-shot case study - A preexperimental design in which a single group of
test units is exposed to a treatment X, and then a single measurement on the dependent
variable is taken.
one-group pretest- posttest design - A preexperimental design in which a group of test units
is measured twice.
static group - A preexperimental design in which there are two groups: the experimental
group (EG), which is exposed to the treatment, and the control group (CG). Measurements
on both groups are made only after the treatment, and test units are not assigned at
random.
True Experimental Designs
pretest-posttest control group design - A true experimental design in which the
experimental group is exposed to the treatment but the control group is not. Pretest and
posttest measures are taken on both groups.
posttest-only control group design - A true experimental design in which the experimental
group is exposed to the treatment but the control group is not and no pretest measure is
taken.
Quasi-Experimental Designs
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time series design - A quasi-experimental design that involves periodic measurements on
the dependent variable for a group of test units. Then, the treatment is administered by the
researcher or occurs naturally. After the treatment, periodic measurements are continued in
order to determine the treatment effect.
multiple time series design - A time series design that includes another group of test units
to serve as a control group.
Statistical Designs
randomized block design - A statistical design in which the test units are blocked on the
basis of an external variable to ensure that the various experimental and control groups are
matched closely on that variable.
Latin square design - A statistical design that allows for the statistical control of two
noninteracting external variables in addition to the manipulation of the independent
variable.
factorial design - A statistical experimental design that is used to measure the effects of two
or more independent variables at various levels and to allow for interactions between
variables.
Laboratory vs. Field Experiments
laboratory environment - An artificial setting for experimentation in which the researcher
constructs the desired conditions.
field environment - An experimental location set in actual market conditions.
demand artifacts - The respondents attempt to guess the purpose of the experiment and
respond accordingly
Limitations of Experimentation  time, cost and administration
Application: Test Marketing
Test marketing – An application of controlled experiment done in limited, but carefully
selected, test markets. It involves a replication of the planned national marketing program
for a product in the test markets.
test markets - A carefully selected part of the marketplace that is particularly suitable for
test marketing.
standard test market - A test market in which the product is sold through regular
distribution channels. For example, no special considerations are given to products simply
because they are being test-marketed.
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controlled test market - A test-marketing program conducted by an outside research
company in field experimentation. The research company guarantees distribution of the
product in retail outlets that represent a predetermined percentage of the market.
simulated test market - A quasi–test market in which respondents are preselected, then
interviewed and observed on their purchases and attitudes toward the product.
debriefing - After the experiment, informing test subjects what the experiment was about
and how the experimental manipulations were performed.
Lilien et al. Chapter 3
Segmentation and Targeting
Markets are heterogeneous. Customers differ in their needs, wants, constraints, beliefs,
values and incentives to act. Segmenting markets, allows forms to better understand their
customers and target their marketing efforts efficiently and effectively.
Three fundamental factors provide the conditions that create the opportunity for a firm to
segment a market successfully:
1. Heterogeneity of customer needs and wants. When customers are heterogeneous,
some actively seek and pay a premium for products and services that better meet
their needs and wants.
2. Though customers may be heterogenous, they must cluster into specific groups
within which members’ needs are more similar to those of other customers in that
group than they are to the needs of customers in other groups
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3. The overall costs of serving customers in a segment must be equal or less than the
prices they are willing to pay, even if those costs are higher than the costs of serving
an average customer.
The segmentation, targeting and positioning approach
Targeting determines which groups a firm should try to serve (and how); and positioning
addresses how the firm’s offering competes with other offerings in the targeted segment.
Benefits of STP:
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By focusing marketing resources to better meet the needs of customers, a firm can
profitably deliver more value to those customers
Customers who perceive and realize more value from a specific brand will develop a
stronger preference for it than for competing brands
As a firm continues to provide good value to its customers, those customers become
loyal to its brands and tend to repeat their purchases and communicate their
favorable experiences to other potential customers
Strong brand loyalty can lead to increased market share and provide a barrier to
competition
Strong brand loyalty requires fewer marketing resources over time to maintain
market share
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Segmentation analysis
A segmentation model requires a dependent variable, usually called a segmentation basis
and independent variables, or segmentation descriptors.
The STP Approach
Segmentation consists of two phases:
1. Phase 1: segment the market using basis variables (e.g., customer needs, wants,
benefits sought, problem solutions desired, preferences, values, usage
situations).
2. Phase 2: Describe the market segments identified using variables that help the
firm understand how to serve those customers (e.g., shopping patterns,
geographic location, clothing size, family size), how to talk to these customers
(e.g., media preferences and use, attitudes, activities, interests, options) and
buyer switching costs (costs associated with changing products or suppliers).
Targeting consists of three phases:
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1. Phase 3: Evaluate the attractiveness of each segment using variables that
quantify the demand levels and opportunities associated with each segment
(e.g., growth rate), the costs of producing the offerings that customers want
(e.g., production and product differentiation costs), and the fit between the
firm’s core competencies and the target market opportunity.
2. Phase 4: Select one or more target segments to serve on the basis of their profit
potential and fit with the firm’s corporate strategy; determine the level of
resources to allocate to those segments
3. Phase 5: Find and reach targeted customers and prospects within targeted
segments in a variety of ways, including direct mail contact, advertising in
selected media vehicles, targeted sales force presentations and the like.
Segmentation Research: Designing and Collecting Data
1. Develop the measurement instrument: What information needs to be collected,
and how should it be collected (e.g., survey form)?
2. Select a sample: Who (which respondents? Where? In what households or
organizations?) needs to be studied?
3. Select and aggregate respondents: How do different responses from several
individuals in a household or organization s combine to predict how the
household or organization will behave
4. Analyze the data and segment the market: What statistical procedure will
segment (potential) customers and describe aspects of their characteristics or
behavior that are crucial to serving their needs?
Forming Segments
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Hierarchical methods: Build up or break down the data row by row
Partitioning methods: Break the data into a prespecified number of groups and then
reallocate or swap data to improve some statistical measure of fit (i.e., the ratio of
with-in-group to between-group variation).
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Malhotra Chapter 20
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Cluster analysis is a class of techniques used to classify objects or cases into relatively
homogeneous groups called clusters. Objects in each cluster tend to be similar to each other
and dissimilar to objects in the other clusters.
Statistics Associated with Cluster Analysis
Select a Clustering Procedure
hierarchical clustering  A clustering procedure characterized by the development of a
hierarchy or tree-like structure.
agglomerative clustering  Hierarchical clustering procedure where each object starts out
in a separate cluster. Clusters are formed by grouping objects into bigger and bigger
clusters.
divisive clustering  Hierarchical clustering procedure where all objects start out in one
giant cluster. Clusters are formed by dividing this cluster into smaller and smaller clusters.
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linkage methods  Agglomerative methods of hierarchical clustering that cluster objects
based on a computation of the distance between them.
single linkage  Linkage method that is based on minimum distance or the nearest
neighbor rule.
complete linkage  Linkage method that is based on maximum distance or the furthest
neighbor approach.
average linkage  A linkage method based on the average distance between all pairs of
objects, where one member of the pair is from each of the clusters.
variance methods  An agglomerative method of hierarchical clustering in which clusters
are generated to minimize the within-cluster variance.
Ward’s procedure Variance method in which the squared euclidean distance to the
cluster means is minimized.
centroid methods  A method of hierarchical clustering in which clusters are generated so
as to maximize the distances between the centers or centroids of clusters.
nonhierarchical clustering  A procedure that first assigns or determines one or more
cluster centers and then groups all objects within a prespecified threshold value from the
center(s).
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sequential threshold method  A nonhierarchical clustering method in which a cluster
center is selected and all objects within a prespecified threshold value from the center are
grouped together.
parallel threshold method Nonhierarchical clustering method that specifies several
cluster centers at once. All objects that are within a prespecified threshold value from the
center are grouped together.
optimizing partitioning method  Nonhierarchical clustering method that allows for later
reassignment of objects to clusters to optimize an overall criterion.
Assess Reliability and Validity
1. Perform cluster analysis on the same data using different distance measures.
Compare the results across measures to determine the stability of the solutions.
2. Use different methods of clustering and compare the results.
3. Split the data randomly into halves. Perform clustering separately on each half.
Compare cluster centroids across the two subsamples.
4. Delete variables randomly. Perform clustering based on the reduced set of
variables. Compare the results with those obtained by clustering based on the entire
set of variables.
5. In nonhierarchical clustering, the solution may depend on the order of cases in the
data set. Make multiple runs using a different order of cases until the solution
stabilizes.
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