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Definition of Marketing Research:
Marketing research is defined as the systematic and objective identification, collection, analysis, and
dissemination of information for the purpose of assisting management in decision making related to the
identification and solution of problems (and opportunities) in marketing.
1) Identification: Involves defining the marketing research problem (or opportunity) anddetermining the information that is needed to address it.
2) Collection: Data must be obtained from relevant sources.
3) Analysis: Data are analyzed, interpreted, and inferences are drawn.
4) Dissemination of information: The findings, implications, and recommendations are provided
in a format that makes this information actionable and directly useful as an input into decision making.
Classifications of marketing research.:
1) Problem identification research: The goal is to identify existing or potential problems not apparenton the surface. Examples include market potential, market share, market characteristics, sales analysis,
short-range forecasting, long-range forecasting, and business trends research.
2)Problem solution research: The goal is to solve specific marketing problems such as segmentation,
product, pricing promotion, and distribution research.
Steps involved in the MARKETING RESEARCH process:
1)Problem definition: Defining the marketing research problem to be addressed is the most important
step because all other steps will be based on this definition.
2)Developing an approach to the problem: Development of a broad specification of how the problem
will be addressed allows the researcher to break the problem into salient issues and manageable pieces.
3)Research design formulation: A framework for conducting the marketing research project that
specifies the procedures necessary for obtaining the required information. It details the statisticalmethodology needed to solve the problem and thus the data requirements needed from data collection.
4)Fieldwork or data collection: A field force (personal interviewing, phone, mail, or electronic
surveys) gathers project data. Although seemingly trivial in nature, to obtain meaningful results field
workers must be accurate and thorough in data collection.
5)Data preparation and analysis: The editing, coding, transcription, and verification of data allowresearchers to derive meaning from the data.
6)Report preparation and presentation: The findings are communicated to the client. The reportshould address the specific research questions identified in the problem definition, describe the
approach, the research design, data collection and the data analysis procedures adopted, and present the
results and the major findings.
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Nature ofMarketing Research and its components :
Marketing research provides the information for decision makers at each step of the marketing decision
process. It is the goal of marketing research to provide relevant, accurate, reliable, valid, and current
information to management in order to facilitate managerial decisions. Each of these characteristics
can be defined for students as:
Information that is relevant, addresses the problem or issue being investigated.
Information that is accurate, correct, and precise.
Information that is reliable, and originates from competent, trustworthy sources.
Information that is valid is applicable to the problem at hand.
Information that is current is timely and up-to-date for both the industry and issue underconsideration.
Two types of marketing research suppliers:
The two types of suppliers by their relationship to the client, internal or external are:
a) Internal supplier a marketing research department located within the firm where all the
marketing research staff members are employees of the firm. Most major corporations have their own
marketing research departments.
b) External supplierresearch suppliers that are not a part of the firm. The external supplier may
offer the entire range of marketing services including problem definition, developing an approach,
questionnaire design, sampling, data collection, data analysis, interpretation, and report preparation andpresentation.
Services offered by a full-service marketing research supplier:
1) Syndicated services: Offered by research organizations that provide information from a common
database to different firms that subscribe to their services.
2) Standardized services: Research studies conducted for different client firms but always in the same
way.
3) Customized services: Offer a wide variety of marketing research services customized or tailor-made
to suit the specific needs of a particular client.
4)Internet services: Offered by firms that have specialized in conducting marketing research on the
Internet.
Services offered by limited-service suppliers:
1) Coding and data entry services: The supplier will take the administered questionnaires, edit them,develop a coding scheme, and transcribe the data onto diskettes or magnetic tapes for input into the
computer.
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2)Analytical services: These services include questionnaire design and pretesting, determining the best
means of collecting data, sampling plans, and other aspects of the research design.
3)Data analysis services: Offer sophisticated data analysis using multivariate techniques.
4)Branded product and services: Consist of specialized data collection and analysis procedures
developed to address specific types of marketing research problems.
Criteria when selecting an External Supplier:
1) The firm selected should be capable of working on the project which includes the employees of the
supplier, facilities for fieldwork, and the data analysis.2) The firm should possess a high degree of technical competence.
3) There should not be any personality clashes between the client and the supplier.
4) Good communication between the client and the supplier is essential to the success of a project.
5) The supplier should provide supervision and control of the fieldwork and other phases of theproject and offer acceptable validation procedures.
6) The supplier should be flexible to meet the unique needs of the client and the project.7) The supplier should be able to complete the work on time.8) The supplier should have experience in order to use sound judgment when conducting certain
marketing research tasks.
9) The supplier should understand the role of research in developing marketing strategies and makingmarketing decisions.
10) The supplier should maintain high ethical standards.
11) The approach adopted would be influenced by the research ideology of the supplier.
12) The supplier should have a good reputation.13) How much the supplier is charging for conducting the project should be a factor.
14) A location close to the client is desirable but not necessary.
Ethical considerations in marketing research:
There is the potential to abuse or misuse marketing research by taking advantage of the respondentsand the general public, for example, by misrepresenting the research findings in advertising. The profit
motive may occasionally cause researchers or clients to compromise the objectivity or professionalism
associated with the marketing research process.
Marketing research has often been described as having four stakeholders. These stakeholders are (1)
the marketing researcher, (2) the client, (3) the respondent, and (4) the public. Ethical issues can be
understood in terms of the responsibilities these stakeholders have to each other and to the researchproject. When conflict occurs, it becomes the responsibility of the stakeholders involved to behave
honorably. Sometimes accepted codes of conduct help guide this behavior. Often decisions rely solely
on the character of the stakeholder.
Importance of the Problem Definition Process:
A clearly defined problem serves as a guideline to the researcher in designing and conducting research
properly. Thus, it helps the researcher in answering the question: What is to be done? In absence of a
well-defined problem, the data collected may be worthless to the decision maker. Stress that a clearly
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laid down research problem leads to goal-directed research, which will meet the objectives of the
decision maker instead of haphazard research, which often provides incomplete information.
Process of formulating the problem.
Formulating the problem is a sequential process. The first step involves discussion with the decision-
maker. The researcher needs to understand the nature of both the problem and the decision whichmanagement faces in order to determine the underlying information needs. Sometimes discussions
with industry experts, analysis of secondary data, and preliminary research are required to identify thefactors that must be considered for the proper identification of the decision problem. The final step is
to translate the decision problem into a research problem.
Importance of the decision maker (DM) to the researcher.
The researcher must communicate with the DM in order to understand the nature of the problem the
DM faces and what he hopes to learn from the research. Such an understanding will help the researcherin gathering information relevant to the problem faced by the decision-maker. Note that a candid and
open discussion between the researcher and DM may help in identifying:
1) The events that led to the need for making a decision.
2) The alternative courses of action available to DM.
3) The criteria to be used in evaluating various courses of action.4) The information that is needed by the DM in making the decision.
A systematic approach to working with the DM is the problem audit. It enables the researcher to get
beyond the mere symptoms to understand the causes of the problem.
Problem audit:
A problem audit is a comprehensive examination of a marketing problem situation with the purpose ofunderstanding its origin and nature. The problem audit involves discussions with the DM on the
following issues:
a) The events that led to the decision that action is needed, or the history of the problem.
b) The alternative courses of action available to the DM. The set of alternatives may be
incomplete at this stage, and qualitative research may be needed to identify the more innovativecourses of action.
c) The criteria that will be used to evaluate the alternative courses of action. For example, new
product offerings might be evaluated on the basis of sales, market share, profitability, return on
investment, and so forth.d) The potential actions that are likely to be suggested based on the research findings.
e) The information that is needed to answer the DMs questions.
f) The manner in which the DM will use each item of information in making the decision.g) The corporate culture as it relates to decision making. In some firms, the decision making
process is dominant; in others, the personality of the DM is more important.
Role of industry experts and secondary data in identifying problem(s):
Note that industry experts can provide useful information about the prevailing market conditions. They
can be especially useful in the case of industrial marketing research where technical knowledge is
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required. Regarding secondary data, it is important to provide economical and quick information that
can be useful in understanding the problem clearly. Sometimes focus groups are used to provideinformation that is then used in refining the problem.
Role of qualitative research in the process of developing an approach:
The purpose of qualitative research is to get a feel for the situation rather than a conclusive result. Suchresearch can and should play a useful role in helping the researcher to understand the problem more
clearly. Techniques such as focus group interviews, pilot surveys, and in-depth interviews are oftenused to find the opinion of the consumers. This helps the researcher in refining the problem and
guiding the research in the right direction.
Factors affecting the problem definition process:
1) Past information and forecasts: Past information and forecasts provide industry data that put
the current problem into context.2) Resources and constraints: Resources and constraints force the problem to be defined in an
appropriate scope.3) Objectives: An understanding of the objectives of the organization and decision maker allowsthe researcher to pinpoint the exact desires for the study.
4) Buyer behavior: An understanding of the ultimate consumers behavior is critical to
understanding their response to specific marketing actions.5) Legal behavior: The legal environment may regulate certain aspects of the marketing mix and
the research effort, thus affecting the problem definition.
6) Economic environment: The economic environment can affect the decisions of consumers and
impact the marketing mix.7) Marketing and technological skills: The abilities of the organization to develop and market
products may affect the scope of the research to be done. In addition, technological advances
offer new methods of conducting marketing research.
Marketing Research Problem and Management Decision Problem:
The management decision problem asks what the DM needs to do, whereas the marketing research
problem entails determining what information is needed and how it can be obtained in the mostfeasible way.
For example:
MIDM
MANAGEMENT DECISIONPROBLEM
MARKETING RESEARCHPROBLEM
Should the price be cut in response to a
price-cut by a competitor?
Determine the buyer-behavior at various
price levels.
Should the product X be introduced in the
market?
Assess the probable market size and share
for product X
What should be done to increase the
relative market share of product Y?
Determine the strengths and weaknesses of
Y vis--vis those of the competitors.
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Components of a well-defined marketing research problem:
A well-defined marketing research problem consists of both a broad statement and a list of specific
components of the problem. The broad statement provides perspective on the problem and acts as a
safeguard against overlooking important aspects of the marketing research and management decision
problems. The specific components focus on the key aspects of the problem and provide clearguidelines on how to proceed further.
A broad definition does not provide guidelines for subsequent steps in research. A narrow definition,on the other hand, may preclude the consideration of some courses of action. In either case, the
solution reached will not be directly related to the problem and may be of little use to the manager.
An example -
Department Store Project: Problem Definition
MR problem -
To determine the relative strengths and weaknesses of Shoppers Stop, vis--vis other major
competitors, with respect to factors that influence store patronage.
Specifically, research should provide information on the following questions.
1. What criteria do households use when selecting department stores?2. How do households evaluate Shoppers Stop and competing stores in terms of the choice
criteria identified in question 1?
3. Which stores are patronized when shopping for specific product categories?Department Store Project: Problem Definition
4. What is the market share of shoppers Stop and its competitors for specific product categories?
5. What is the demographic and psychological profile of the customers of Shoppers Stop? Does it
differ from the profile of customers of competing stores?6. Can store patronage and preference be explained in terms of store evaluations and customer
characteristics?
Research Design
Importance of a good research design:
Research design is a framework or blueprint for conducting the marketing research project. It specifies
the precise details of the procedures necessary for obtaining the required information. Finally, stress
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that it is important to have a good research design in order to ensure that the marketing research project
is conducted effectively and efficiently.
Exploratory and Conclusive Research Designs:
Exploratory research is used in situations where the problem may have to be defined more precisely,
relevant courses of action identified, hypotheses formulated, or additional insights gained before anapproach can be developed. Conclusive research would be used to test specific hypotheses, examine
specific relationships, or make predictions.
Descriptive and Causal Research.:
Although both descriptive and causal research are classified as conclusive research, they differ in terms
of their objectives.
Descriptive research is used to describe something, usually market characteristics or functions.
Causal research is used to obtain evidence regarding cause-and-effect relationships.
Distinction between exploratory, descriptive, and causal research:
Exploratory research is typically used to provide structure and insight into the research problem. Forexample, using focus groups to determine key factors related to the use of your product.
Descriptive research begins with the structure already defined and proceeds to actual data collection in
order to describe some market variable. For example, determining the average age of purchasers ofyour product.
Causal research also proceeds from a pre-established structure but attempts to infer causalrelationships between variables as opposed to describing variables. For example, determining if
increased advertising spending has led to an increase in sales.
Six Ws of descriptive research:
The six Ws are used by journalists when trying to gather facts for a story. In like manner, because
descriptive research is marked by the prior formulation of specific hypotheses, the design requires a
clear specification of the six Ws of the research:
1) Who: Who should be considered?
2) Where: Where should the respondents be contacted to obtain the required information?
3) When: When should the information be obtained from the respondents?4) What: What information should be obtained from the respondents?
5) Why: Why are we obtaining information from the respondents?
6) Way: The way in which we are going to obtain information from the respondents.
These questions form the basis for describing the research to be conducted.
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Descriptive research is characterized by a clear statement of the problem, specific hypotheses, and
detailed information needs.
Causal research is appropriate to use when the purposes are to understand which variables are the
cause and which variables are the effect, and to determine the nature of the functional relationship
between the causal variables and the effect to be predicted.
Six components of a research design:
a) Define the information needed.
b) Design the exploratory, descriptive, and/or causal phases of the research.c) Specify the measurement and scaling procedures.
d) Construct and pretest a questionnaire or an appropriate form for data collection.
e) Specify the sampling process and sample size.
f) Develop a plan of data analysis.
Primary and Secondary Data
Primary data are originated by researcher for the specific purpose of addressing the research problem.
Secondary data is data that has already been collected for purposes other than the problem at hand.
The data are often found internally, and also from published materials, computerized databases, orfrom syndicated services. Secondary data are characterized as easily available and relatively
inexpensive to obtain.
A comparison of Primary and Secondary Data
PRIMARY DATA SECONDARY DATA
Collection Purpose For the problem at hand For other problems
Collection Process Very involved Rapid and easy
Collection Cost High Low
Collection Time Long short
Scope of secondary data:
Secondary data can cover a broad range of factors that affect the problem at hand. It does not always fitthe specific problem at hand, but can be useful in developing an approach to the problem and providing
a comprehensive understanding of the problem environment.
It is important to obtain secondary data before primary data because secondary data, as compared to
primary data, are easily available, inexpensive, and retrieving secondary data requires a short amountof time. In addition, secondary data generally provide valuable insights for collecting primary data.
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The difference between internal and external secondary data is that internal data are those available
within the organization for which the research is being conducted although external data are thosegenerated by sources outside the organization.
Advantages of secondary data:
Secondary data can help you:
Identify the problem.
Better define the problem.
Develop an approach to the problem.
Formulate an appropriate research design (for example, by identifying the key variables).
Answer certain research questions and test some hypotheses.
Interpret primary data more insightfully.
Examination of available secondary data is a prerequisite to the collection of primary data. Proceed to
primary data only when the secondary data sources have been exhausted or yield marginal returns.
Disadvantages of Secondary Data:
Because secondary data have been collected for purposes other than the problem at hand, their
usefulness to the current problem may be limited in several important ways, including relevance andaccuracy.
The objectives, nature, and methods used to collect the secondary data may not be appropriate to thepresent situation.
Secondary data may be lacking in accuracy, or may not be completely current or dependable.
Internal Sources of Secondary Data:
Internal sources can supply some of the most vital data for research. The information generated by thecorporations daily business operations can represent a wealth of data useful to the researcher and
should be the starting point of a project. It offers the advantages of being proprietary to the company
and is available at a low cost relative to outside suppliers.
For example, sales data are valuable information for any marketing project because it shows the exact
results of a program, salesperson, or sales region. Actual costs allow the researcher to estimate costsfor a research study or project costs for a marketing program. Detailed information can be gathered on
precise questions; for example, the percentage of sales to industry versus government, or sales brokenout by company accounts. With planning, sales data can be recorded in the companies managementinformation systems to allow for optimal use by analysts.
Published External Secondary Data:
Published data is abound but the key is knowing where to look for it. Both government and
nongovernmental published sources exist, as well as guides, directories, and indexes to help locate the
necessary information. The difficulty is locating either the right directory or index to guide you, or to
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understand the classification system used. A good librarian is a real advantage and can cut down the
search time remarkably. You may want to bring a copy of a directory or index to show howcomplicated they can be to use.
Census data - a major source of secondary data:
The Census Bureau is the largest source of statistics. Census data can provide important information ondemographics, manufacturers, retail trade agriculture, transportation, and so on. The quality of census
data is very high, making it a very reliable and useful source.
Databases in marketing research:
The use of databases has increased phenomenally due to the rocketing sales of PCs and due to the
increase in the number of vendors providing such databases. Both online and offline databases are
available consisting of bibliographic, numeric, full-text, directory, and specialized databases. In
addition, directories of databases exist to aid in locating the proper information.
Syndicated sources of secondary data:
Companies which collect and pool information and sell it to a number of clients are termed syndicated
sources of data. They provide information on both the consumer and industrial market via a variety of
data gathering techniques. Based on the unit of measurement, syndicated services can be classified ashousehold/consumer-oriented or institutionally-oriented.
Household services emphasize the consumer. The most popular form of measurement is the survey.
Institutional services emphasize the distribution chain. Information is more difficult to obtain herebecause of the strategic and proprietary nature of information in the business realm. As a result, it is
often the case that valid reports on institutions will be more general than most marketers would like.
Panels and surveys:
A panel is a sample of respondents that provide specified information at regular intervals over anextended period of time. The distinguishing feature of purchase panels is that the respondents in the
panel are required to record specific behaviors as they occur. In media panels, the behavior is
automatically recorded by electronic devices.
Advantages:
1) Panels provide longitudinal data, i.e. data obtained from the same respondents repeatedly.
2) Panel members may provide higher quality data than would a sample because of their willingness
to serve on the panel.
Disadvantages:
1) Most panels are not representative of the population.
2) Over a period of time maturation sets in and the panel members must be replaced.
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3) Response biases may occur as simply being on the panel may alter behavior.
Psychographics and AIO:
Psychographics is psychological characteristics of consumers that can be quantified. They can then be
classified as consisting of two types of variables: lifestyle and personality.
A lifestyle may be defined as a distinctive pattern of living that is described by the activities people
engage in, the interests they have, and the opinions they hold of themselves and the world aroundthem. These activities, interests, and opinions are termed AIOs. The AIOs can be used to segment
people into groups with different lifestyles and then the marketing effort can be geared to meet the
needs of any group(s).
Need to use multiple sources of secondary data:
No single source of secondary data can provide information that completely fits the need of the present
problem. Moreover, each method has certain weaknesses. One may suffer from biases, the other maybe dated, the third may not be very accurate, and so on. Combining various secondary sources cancancel out the weaknesses of one another and provide accurate, comprehensive, and high-quality data.
Qualitative and Quantitative Research:
Qualitative Research is a unstructured, exploratory research methodology based on small sample that
provides insights and understanding of the problem setting.
Quantitative Research is a research methodology that seeks to quantify the dats and typically, applies
some form of statistical analysis.
Qualitative Versus Quantitative Research
QUALITATIVE RESEARCH QUANTATIVE RESEARCH
Objective To gain a qualitativeunderstanding of the underlying
reasons and motivation
To quantify the data andgeneralize the results from the
sample to the population of
interest.
Sample Small number of non
representative case
Large number of representative
cases
Data collection Unstructured Structured
Data analysis Non statistical StatisticalOutcome Develop an initial understanding Recommend a final course of
action
The primary differences between quantitative research and qualitative research are that in quantitative
research the objective is to quantify the data and generalize the results from the sample to the
population of interest, whereas qualitative researchs objective is to gain a general understanding of the
underlying reasons and motivations of the group.
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Other differences are that qualitative research employs a small number of nonrepresentative cases, usesunstructured data collection techniques, nonstatistical data analysis, and results in an initial
understanding of the problem. Quantitative research, however, employs a large number of
representative cases in the sample, uses structured data collection techniques, statistical data analysis,
and results in recommendations for action.
Qualitative research is called the why research. Its basic purpose is to provide additional insights
and understanding of the problem at hand. This type of research is typically based on a looselystructured nonrepresentative sample, unstructured interviews or observations, and a nonstatistical
approach to data analysis.
Inter-relationship between qualitative research and quantitative research:
Qualitative research is primarily used to gain an initial understanding of underlying motivations for
peoples attitudes, preferences, and behavior. The goal is to gain sufficient knowledge about the scopeand the general nature of the problem at hand to direct future quantitative research. The findings fromqualitative research can then be used to generate hypotheses on key variables that can be tested
quantitatively.
Classification of Marketing Research Data
Categories of Qualitative Research.
MIDM 13
Marketing Research Data
Secondary Data Primary Data
Qualitative Data Quantitative Data
CausalDescriptive
Survey
Data
Observational
& Other Data
Experimental
Data
Qualitative Research
Procedure
Direct (Non Disguised) Indirect (Disguised)
Focus Group Depth Interview
ExpressiveTechniques
AssociationTechniques
CompletionTechniques
ConstructionTechniques
Projective Techniques
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The three types of qualitative research can be classified as direct or indirect. The difference is that in
direct research the purpose of the research is disclosed to the respondent or is otherwise obvious tothem, whereas the reason for the research is not disclosed to the respondents of indirect qualitativeresearch. Focus groups are an example of direct techniques whereas word association is an illustration
of indirect procedures.
Focus groups consist of 8 to 12 people interviewed by a trained moderator to gain insights on the
salient aspects of a marketing problem by listening to a group of people from an appropriate target
market. Depth interviews are conducted on a one-on-one basis to uncover underlying motivations,
beliefs, attitudes, and feelings on a topic. Indirect techniques, also called projective techniques, areused to ask the respondent to interpret the behavior of others and thus add insight into personally held
beliefs of the respondent.
Focus group:
A focus group is an interview conducted by a trained moderator among a small group of respondents ina nonstructured and natural manner. The focus group is the most popular qualitative research technique
because it is a relatively inexpensive technique that can be used in almost any situation requiring
preliminary understanding and insights. This technique has several advantages that include synergism,snowballing, stimulation, security, spontaneity, serendipity, specialization, scientific scrutiny,
structure, and speed.
Planning and conducting focus groups:
1) Examine the objectives of the research projectprovides the rationale for conducting the focus
group.2) Specify the objectivesoutlines the goals of the study in order to guide the interview.
3) State the questions to be answered from the focus groupa detailed set of questions to be
answered.4) Write a screening questionnaireensures that participants represent an appropriate sample for
the study.
5) Develop a Moderators Outlineensures that the moderator understands the nature of the
study and the key findings desired by the client.
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6) Conduct the interview
7) Review tapes and analyze dataallows the researcher to uncover inconsistent responses,missed remarks, nonverbal communication and new ideas.
8) Summarize findings and plan follow-up researchto probe further into the issues and sample
statistically significant populations.
Role and skill requirements of effective focus group moderators:
The moderator plays a vital role in the success of a focus group. He is responsible for setting a tone inthe focus group that makes the respondents feel comfortable enough to discuss their thoughts. He also
must establish the rules, direct the study, communicate the objectives to the respondents, probe the
respondents for deeply held attitudes, and facilitate a free-flowing discussion in the relevant areas.Finally, he must summarize the groups responses to ensure agreement on his interpretation of their
responses.
Some key qualifications of focus group moderators include kindness, firmness, permissiveness,involvement, the ability to project incomplete understanding, encouragement, flexibility, and
sensitivity.
Disadvantages of focus groups:
1) It is harder to correctly interpret the responses.2) There is extreme dependence on the performance of the moderator.
3) Coding and analysis is cumbersome.
4) The group is not representative of the general population.
5) The results are subject to researcher or client bias.
Depth interviews:
A depth interview is an unstructured and direct way of obtaining information and is conducted on a
one-on-one basis. The respondent is probed in depth by a highly skilled interviewer to uncover
underlying motivations, beliefs, attitudes, and feelings on a topic. The interviewer attempts to get thesubject to talk freely and the direction of the interview is influenced heavily by the subjects answers.
Depth interviews are preferable to focus groups in cases where detailed probing of the individual is
required, the topic is considered confidential or embarrassing, or detailed understanding of complicatedbehavior is required.
Advantages:
1) Great depths of insights can be uncovered.
2) It associates the responses directly with the respondent.
3) There is no social pressure to conform to group response.
Disadvantages:
1) Skilled interviewers capable of conducting depth interviews are expensive and difficult to find.
2) The lack of structure makes the results very susceptible to the influence of the interviewer.
3) The quality and completeness of the results depends very heavily on the skills of the
interviewer.
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4) The data obtained is problematic to analyze and interpret.
Depth interviews can be effectively employed in special problem situations, such as those requiring:
1) Detailed probing of the individual.
2) Discussions on topics considered confidential, sensitive, or embarrassing.
3) Situations where strong social norms exist and the individual may be easily swayed by groupresponse.
4) Detailed understanding of complicated behavior.5) Interviews with professional people.
6) Interviews with competitors who are unlikely to reveal the information in a group setting.
7) Situations where the product consumption experience is sensory in nature affecting mood statesand emotions.
Projective techniques:
Projective techniques use third person associations to indirectly ascertain the respondents motivations/
attitudes/ beliefs. When a personal or threatening question is asked directly, it is assumed that therespondent will be reluctant to answer in complete truth, but if the same question is asked about a thirdparty, it is assumed a more accurate and complete answer pertaining to the respondent will be supplied.
The four forms of projective techniques are:
1) Association techniques: An individual is presented with a stimulus or stimuli and asked to
respond with the first thing or things that come to mind.
2) Completion techniques: The respondent is required to complete an incomplete stimulus
situation.
3) Construction techniques: The respondent is required to construct response in the form of a
story, dialogue, or description.
4) Expressive techniques: The respondents are presented with a verbal or visual situation and
asked to relate the feelings and attitudes of other people to the situation.
Descriptive Research Design
Descriptive Research consist of Surveys and Observations as the main ways in which relevant data can
be collected.
Survey Method: A structured questionnaire given to respondents and designed to elicit specificinformation
This method of obtaining information is based on the questioning of respondents. The respondents areasked variety of questions regarding their behavior, intentions, attitudes, awareness, motivations and
demographic and lifestyle characteristics.
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Structured data collection: use of a formal questionnaire that presents questions in a prearranged order.
Fixed alternative questions: Questions that require respondents to choose from a set of predetermined
answers.
e.g.
Shopping in department store is fun
Classification of Survey Methods
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Survey Method
TelephoneInterviewing
PersonalInterviewing
ComputerAssisted
In-Home
ElectronicInterviewing
MailInterviewing
Traditional
MallIntercept
ComputerAssisted
Panel
E-mail Internet
Disagree Agree1 2 3 4 5
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Observation : The recording of behavior patterns of people, objects and events in a systematic mannerto obtain information about the phenomenon of interest.
The observer does not question or communicate with the people being observed.
Information may be recorded as the events occur or from records of past events.
Observational method may be structured or unstructured.
Structured Observation: Observation techniques where the researcher clearly defines the behaviors to
be observed and the methods by which they will be measured.
e.g. Auditor performing inventory analysis in the store.
Unstructured Observation: Observation that involves a researcher monitoring all aspects of the
phenomenon without specifying the details in advance.
e.g. observing children playing with new toys.
Measurement and Scaling
Measurement proceeds scaling in test construction.
Measurement is the assignment of numbers or other symbols to characteristics of objects according tocertain prespecified rules. Scaling is an extension of measurement where it involves the generation of a
continuum upon which measured objects are located.
Primary scales of measurement:
1) Nominal scale: This is used only as a labeling scheme where numbers serve only as labels or
tags for identifying and classifying objects. The numbers in a nominal scale do not reflect the amount
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of a characteristic possessed by the objects, rather they are used only for identification. For example,
numbers on cricket players uniforms, street names, or insurance policy numbers.
2) Ordinal scale: This is a ranking scale in which numbers are assigned to objects to indicate the
relative extent to which some characteristic is possessed. It is then possible to determine whether an
object has more or less of a characteristic than some other object. For example, rankings of tennis
players for a championship, socioeconomic status and quality rankings.
3) Interval scale: Numbers are used to rank objects such that numerically equal distances on thescale represent equal distances in the characteristic being measured. Examples include time and
temperature.
4) Ratio scale: This is used to identify or classify objects, rank order the objects, and compare
intervals, differences. For example, height, age, and income.
The differences between a nominal and an ordinal scale are that in nominal scales, the numbers serveonly as labels or tags for identifying and classifying objects while in an ordinal scale the numbers are
used as a ranking device. Although both nominal and ordinal scale data can be used for countingoperations, ordinal scales permit the use of statistics based on percentiles.
The advantage of a ratio scale over an interval scale is that the origin is fixed. Hence, it is meaningfulto take ratios of scale values. Statistics such as the geometric mean, harmonic mean, and coefficient of
variation can be applied to analyze ratio scale data. However, this advantage is not significant
because the commonly used statistics in marketing research can be calculated on interval data.
Two types of scales: comparative and non-comparative.
Comparative scalesa direct comparison of stimulus objects is elicited. Thus, two brands may be
compared along a dimension such as quality.
Non-comparative scales the respondent provides whatever standard seems appropriate to him/her,
thus, only one object is evaluated at a time. In this case, one brand is rated on a scale independent ofother brands.
Classification of Scaling Techniques
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Scaling Techniques
Comparative Scales Non comparative Scales
Continuous ratingScale
ItemizedRating Scales
Constant
Sum
Paired
Comparison
Rank
Order
Q-Sort and Other
Procedures
StapelSemanticDifferential
Likert
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Comparative scaling techniques:
All comparative scaling techniques involve a direct comparison of stimulus objects with one another.
This should be highlighted as each of the scales are discussed in turn.
1. Paired comparison scaling: Here 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 is ordinal
in nature. This is frequently used in marketing when comparisons of products or brands arebeing made. Refer Figure 3 for an example of paired comparison scaling.
2. Rank order scaling: Respondents are presented with several objects simultaneously and asked
to order or rank them according to some criterion. This is commonly used to measurepreferences for brands as well as the importance of attributes.
3. Constant sum scaling: Respondents are required to allocate a constant sum of units such aspoints, dollars, chits, stickers, or chips among a set of stimulus objects with respect to some
criterion. Specific instructions are provided that if an attribute is not at all important, it is
possible to assign zero points. If an attribute is twice as important as some other attribute itshould receive twice as many points.
4. Q-sort scaling: This technique uses a rank order procedure in which objects are sorted intopiles based on similarity with respect to some criterion. In Magnitude estimation numbers are
assigned to objects such that ratios between the assigned numbers reflect ratios among the
objects on the specified criterion. Guttman scaling or scalogram analysis: A procedure for
determining whether a set of objects can be ordered into an internally consistent, one-dimensional scale.
Non-comparative scaling techniques:
Non-comparative scaling is the type of scaling, which does not compare the object against another
object or some standard. Rather, the rater uses whatever standard seems most appropriate to him orher.
1. Continuous rating scale: 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 the other. The form of the
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continuous scale varies considerably depending on the imagination of the researcher. Their use in
marketing has been limited because they are not as reliable as itemized scales, the scoring process iscumbersome, and they provide little additional information.
E.g.
Continuous Rating Scales
How would you rate Shoppers Stop (SS) as a department store?
Version 1
Probably the Worst -----------I------------------------------------------------------------- Probably the Best
Version 2
Probably the Worst -----------I------------------------------------------------------------- Probably the Best
0 10 20 30 40 50 60 70 80 90 100
Version 3
Very bad Neither good Very good
nor bad
Probably the Worst -----------I------------------------------------------------------------- Probably the Best
0 10 20 30 40 50 60 70 80 90 100
2.Itemized rating scale: The respondents are provided with scales having numbers and/or briefdescriptions associated with each category. The respondents are required to select one of the specified
categories that best describes the object being rated. Several types of itemized rating scales exist.
(i. Likert scale: The respondents are required to indicate a degree of agreement or disagreement with
each of a series of statements related to the stimulus objects. The Likert scale is often used inmarketing. It is easy to construct and administer, it is easy for respondents to complete, and it is
suitable for mail, telephone, and personal surveys.
Strongly Disagree Neither Agree Strongly
disagree agree nor agree
disagree
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1. Shoppers Stop sells high quality 1 2X 3 4 5merchandise.
2. SS has poor in-store service. 1 2X 3 4 5
3. I like to shop at SS 1 2 3X 4 5
(ii) Semantic differential scale: It is a seven-point rating scale with end points associated with bipolarlabels that have semantic meaning. Respondents are required to rate objects on a number of itemized,
seven-point rating scales bounded at each end by one of two bipolar adjectives. This scale is popular in
marketing and has been used in image studies, promotion strategy, and new product development
studies.
Shoppers Stop IS:
Powerful --:--:--:--:-X-:--:--: WeakUnreliable --:--:--:--:--:-X-:--: Reliable
Modern --:--:--:--:--:--:-X-: Old-fashioned
(iii). Stapel scale: Is a unipolar rating scale with ten categories numbered from -5 to +5, without a
neutral point. Respondents are asked to indicate how accurately or inaccurately each term describes the
object by selecting an appropriate numerical response category. Though easier to construct than thesemantic differential, while giving the same results, the Stapel scale has not been widely applied in
marketing.
Shoppers Stop
+5 +5
+4 +4
+3 +3+2 +2X
+1 +1
HIGH QUALITY POOR SERVICE-1 -1
-2 -2
-3 -3-4X -4
-5 -5
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The differences between the Stapel scale and the Semantic differential is that with the Stapel scalethere is no need to pretest the adjectives or phrases to ensure true bipolarity and the Stapel scale can
also be administered over the telephone. The semantic differential is more popular than the Stapel
scale.
Major decisions involved in constructing itemized rating scales:
1) Number of scale categories to use: The number of categories should be between five and nine;however, there is no single, optimal number of categories that would be applicable for all scaling
situations. In the Department Store example, the class can debate the trade off between ability to
discriminate among the categories and ability of the respondent to answer.
2) Balanced versus unbalanced scale: A balanced scale has an equal number of favorable and
unfavorable categories used; otherwise, the scale is unbalanced. The scale should be balanced in order
to obtain objective data; however, if the distribution of responses is likely to be skewed, an unbalancedscale with more categories in the direction of skewness may be appropriate.
3) Odd or even number of categories: With an odd number of categories, the middle scale positionis generally designated as neutral. If a neutral or indifferent scale response is a possibility for at least
some of the respondents, an odd number of categories should be used.
4) Forced versus non-forced scales: A forced rating scale does not have a no opinion or no
knowledge option. Thus, the respondents without an opinion may mark the middle scale position. If a
sufficient proportion of the respondents in fact do not have an opinion on the topic, marking the middle
position in this manner will distort measures of central tendency and variance. In situations where therespondents are expected to have no opinion, the accuracy of the data may be improved by having a
nonforced rating scale which includes a no opinion or no knowledge category.
5) Nature and degree of verbal description: The strength of the adjectives used to anchor the scale
has a slight tendency to influence the distribution of the responses. With strong anchors, respondents
are less likely to use the extreme scale categories. Have the students reach consensus on the scaleanchors. Try to encourage multiple anchors that can be used in the survey.
6) Physical form of the scale: There is no agreement as to which form is the most appropriate, butscales could be presented vertically or horizontally, categories could be expressed in terms of boxes,
discrete lines, or units on a continuum and may or may not have numbers assigned to them, and
numerical values could be positive or negative or both. The students should decide which format to use
for the scales. Have them justify their reasons for the scale they choose.
Questionnaire and Form Design
Importance of a well-constructed data collection instrument:
Data collection flows from specifying the information needed, to identifying the method of obtainingit, to determining scaling procedures. Once this is done, a data collection instrument can be created.
This usually is a questionnaire.
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It is vital that the questionnaire be constructed so as to
(1) capture the information needed,(2) be standardized so that data are comparable across test sites and results can thus be generalized, and
(3) maximize the efficiency of tabulating and analyzing data.
Objectives of a questionnaire:
These objectives should guide researchers as they construct a questionnaire and act as guidelines for
making judgment calls on specific aspects of questionnaire design.
a) The questionnaire must translate the information needed into a set of specific questions that the
respondents can and will answer.b) A questionnaire must uplift, motivate, and encourage the respondent to become involved in the
interviewing process, to cooperate, and to complete the interview.
c) A questionnaire should be designed to minimize response error.
Steps involved in the questionnaire design process:
1. Specify the information needed: Translate the information needed into a set of specific questions.Dummy tables are particularly helpful in guiding the design of individual questions in the
questionnaire. It is important to have a clear idea of the target population.
2. Type of interviewing method: In personal interviews, lengthy, complex, but diverse types of
questions can be asked. In telephone interviews, the questions asked are short and simple because
the respondents do not get to see the questionnaire. In mail interviews, the questions have to be
simple and detailed instructions have to be provided because there is no interaction with theinterviewer.
3. Individual question content: For each item of information that is needed, the researcher should askwhether that information is being adequately obtained by questions already formulated. Also, the
data generated by each question should be used to address the information needed. Once it is
determined that the question is needed, it is important to make sure the question is sufficient toobtain the desired information. Sometimes several questions are needed instead of one.
4. Overcoming inability to answer: There are several factors that limit the respondents ability toprovide the desired information:
a) Is the respondent informed: In situations where it might be suspected that not all respondents
are likely to be informed about the topics of interest, filter questions measuring familiarity,
product use and past experience should be asked before asking questions on the topics.b) Can the respondent remember: The ability to remember an event is influenced by the event
itself, the time elapsed since the event, and the presence or absence of events that would assist in
remembering.c) Cans the respondent articulate: Respondents should be provided with aids to help them
articulate their responses. For example, providing a list of descriptions or possible answers can
assist the respondent in articulating.
5. Overcoming unwillingness to answer: The reasons for unwillingness to respond include too much
effort being required, the situation or context may not be seen as appropriate for disclosure, no
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legitimate purpose or need is seen for the information requested, and the information is seen as
sensitive.6. Choosing question structure: Questions can be either structured or unstructured. Unstructured
questions are open-ended questions in which the respondents have the freedom to reply in their own
words rather than being limited to the selection of one of the response alternatives. These are best
used as opening questions. Structured questions prespecify the set of response alternatives and the
response format. They improve respondent cooperation and make administering and coding thesurvey easier.
In designing multiple-choice questions, the number of response alternatives should be collectively
exhaustive in that they exhaust or include the set of all possible alternatives. The general guideline is to
list all alternatives that may be of any importance at all and include an alternative labeled Other(please specify)__________.
In the rare cases in which none of the listed alternatives represent the appropriate response,
respondents can use the Other option and record their responses in the space provided. Also, the
response alternatives should be mutually exclusive. Overlap among alternatives should be avoided. Tocontrol for order bias, several forms of the questionnaire should be prepared. The order in which the
alternatives are listed should be varied from form to form. It is desirable that each alternative appears
once in the extreme positions, once in the middle, and once somewhere in between.
Some of the advantages of multiple-choice questions include a reduction in interviewer bias. Such
questions are faster to administer. Also, coding and processing of data is less costly and time
consuming. In self-administered questionnaires, respondent cooperation is improved if the majority ofthe questions are structured.
Some of the disadvantages of multiple-choice questions include the potential need for exploratory
research using open-ended questions to determine the appropriate response alternatives. It is difficult toobtain information on alternatives not listed. Even if an Other (please specify) category is included,
there is a strong tendency for the respondents to choose from among the listed alternatives. In addition,
showing respondents the list of possible answers has the potential of producing biased responses.Asalready discussed, there is also the potential of order bias in multiple-choice questions.
7. Choosing question wording: The translation of the desired question content and structure intowords that can be clearly and easily understood by the respondents. The following guidelines are
used for framing questions:
a) Define the issue
b) Use ordinary wordsc) Ambiguous words should be avoided
d) Avoid leading questionse) Avoid implicit alternatives
f) Avoid implicit assumptions
g) Avoid generalizations and estimatesh) Use positive and negative statements
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8. Order of the questions: The order in which the questions are presented is a crucial element in
questionnaire design because improper ordering of the questions can seriously bias the responses.The opening questions should be interesting, simple, and nonthreatening so that it will tap the
interest of the respondents and get them involved in the interviewing process. Questions that are
difficult, sensitive, embarrassing, complex, or dull should be placed later in the sequence only after
rapport has been established.
9. Form and layout: It is good practice to divide a questionnaire into several parts, each part dealing
with a specific set of questions. Research has shown that questions at the top of the page receivemore attention than those placed at the bottom.
Some guidelines for form and layout decisions include:
a) Questions at the top of the page receive more attention than when placed at the bottom.
b) It is a good practice to divide a questionnaire into several parts, each part dealing with a specific
set of questions.c) Questions in each part should be numberedparticularly when branching questions are used.
d) Questionnaires should preferably be precoded.e) Questionnaires should be numbered serially.
10.Reproduction of the questionnaire: The following guidelines are used:
a) The questionnaire should have a professional appearance.
b) If the questionnaire runs to several pages, it should be made into the form of a booklet rather
than a number of sheets of paper clipped or stapled together.
c) The entire question should be reproduced on a single page.d) Vertical response category formats should be used for individual questions.
e) The questions should not be overcrowded.
f) Directions or instructions meant for the interviewer or the respondent for individual questionsshould be placed as close to the question as possible.
g) Color does not influence response rates to questionnaires. However, it can be employed
advantageously in branching questions.h) The questionnaire should be reproduced in such a way that it is easy to read and answer.
i) Several opportunities exist for improving the reproduction of an average questionnaire in such
a way as to obtain better quality data and simultaneously reduce costs (e.g., by reducingprinting costs).
11.Pretesting: Pretesting refers to the testing of the questionnaire on a small sample of respondents
for the purpose of improving the questionnaire by identifying and eliminating potential problems. Ingeneral, a questionnaire should not be used in the field survey unless it has been adequately
pretested. (Figure 1 and Figure 2)
The issues involved in pretesting include:
a) Extensive examination of all aspects of the questionnaire.b) Similarity in pretest and survey respondent populations
c) Initial pretest done by a personal interview, followed by a pretest using the interviewing mode to
be actually used if that is different.
d) Selection of actual interviewers.
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e) Sample size.
f) Protocol analysis and debriefing.g) Editing and analysis.
Observational forms versus questionnaires:
Similaritiespreplanning is necessary to obtain the information needed. Specification of the who,what, when, where, why, and how of behavior is necessary.
Form, layout, and reproduction of forms should make it easy for recording data and later tabulating and
analyzing data. Adequate pretesting is required.
Differencesobservational forms are easier to construct because the psychological impact of the form
of questions and the way they are asked is eliminated.
Sampling
The objective of marketing research is to obtain information about the characteristics of a population,either using a sample or census. A representative sample, though not the entire population, contains thesame characteristics as the population, thus, generalizability is high and population parameters can be
inferred from the information from the sample. This information is contained in statistics, and the
inferences that are made use statistical techniques such as estimation procedures and hypothesistesting.
Population, census and sample:
A population is the aggregate of all the elements that share some common set of characteristics, and
that comprise the universe for the purpose of the marketing research problem. The population
parameters are typically numbers, such as the proportion of consumers who are loyal to a particularbrand of toothpaste. Information about population parameters may be obtained by taking a census or a
sample.
A census involves a complete enumeration of the elements of a population. The population parameters
can be calculated directly in a straightforward way after the census is enumerated.
A sample, on the other hand, is a subgroup of the population selected for participation in the study.
Sample characteristics, called statistics, are then used to make inferences about the population
parameters.
Relationship between the sample design process and the research project:
Sampling is the fifth step in the process of formulating a research design. The researcher has already
specified the information that is needed to address the marketing research problem and the primary
sources from which this information would be obtained have also been determined. Furthermore, thescaling and measurement procedures have been specified and the questionnaire designed. At this point
sampling becomes the critical question because the researcher must now administer the questionnaire
to the relevant group of respondents.
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Sampling design process:
This process is depicted in Figure 1. The sampling design originates from the population of interest,
thus, the population must be accurately defined in a precise statement of who should or should not be
included in the sample. It may be very general, such as residents of the state of Delhi, or specific, like
males between 20 and 30 years of age who cannot read. To measure the population, a sampling frameis needed. The sampling frame consists of a list or set of directions for identifying the elements of the
target population. The sampling unit must then be set. This is the element that contains the elements ofthe population, for example, it could be a household, an office, or the individual.
At this point, the researcher is ready to introduce quantitative techniques into the sampling designprocess. The appropriate sampling technique must be chosen which involves making decisions
between using a Bayesian approach versus a traditional approach, sampling with replacement versus
without replacement, and using probability versus nonprobability sampling. When the method is
determined, a particular sample size can be calculated. This number represents the total number ofelements that must be surveyed in order for the results to be valid. Finally, the execution of the
sampling process must be operationalized, i.e., detailed specifications of variable definitions andinterviewing procedures. Doing this ensures that all interviewers use the same guidelines during theinterview process so that the data are comparable.
Population sampling frame discrepancy:
Population sampling frame discrepancy is defined as a sample frame that does not include all elements
of a population. A common example is the telephone directory (it does not include unlisted numbers
and new people who have moved recently). It should always be identified in a study. It can be resolvedin one of the following ways:
1) Redefine the population in terms of the sampling framethis is a simplistic approach that avoidsthe problem that portions of the population are not included in the sampling frame. If the telephone
book is our sampling frame, it now becomes our population.
2) Screen the respondents through qualifying questionnairesalthough this eliminates unwanted
elements from the survey, it does not address the main issue. Screening would not address the fact that
some numbers are not included in the phone book.
3) Apply a weighting scheme to counterbalance the sampling frame erroraccurate estimates for the
weights must be made to make this an effective tool.
Factors to consider in selecting a sampling technique:
There are three decisions to be made when selecting a sampling technique:
1) Bayesian or traditional approachalthough the Bayesian approach is theoretically more sound, in
practice it is more challenging to implement because of its stringent statistical requirements. Thus,
most research uses the traditional approach, in which the entire sample is selected before the research
begins.
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2) With or without replacementthis is only important if the sampling frame is small compared to thesample size because the potential bias from counting one element twice is proportionately greater.
3) Nonprobability or probability samplingprobability sampling offers greater statistical inference
about the population and is generally recommended for most applications.
Probability and nonprobability sampling techniques:
Nonprobability sampling techniques do not use chance selection procedures. Rather, they rely on the
personal judgment of the researcher. The researcher can arbitrarily or consciously decide the elements
to be included in the sample. Nonprobability samples may yield good estimates of the populationcharacteristics. However, they do not permit an objective evaluation of the precision of the sample
results. As there is no way of determining exactly what the chance is of selecting any particular
element for inclusion in the sample, estimates obtained are not statistically projectable to the
population.
In probability sampling techniques, sampling units are selected by chance. Each sampling unit has anonzero chance of being selected. Furthermore, it is possible to prespecify every potential sample of agiven size that could be drawn from the population as well as the probability of selecting each sample.
There is no requirement that every potential sample have the same probability of selection. However, it
should be possible to specify the probability of selecting any particular sample of a given size. This notonly requires a precise definition of the target population, but also, generally, a specification of the
sampling frame. Given the chance selection procedures employed, it is possible to determine the
precision of the sample estimates of the characteristics of interest. Confidence intervals containing the
true population value with a given level of certainty can be calculated. This permits the researcher tomake inferences or projections to the target population from which the sample was drawn.
Probability techniques differ from nonprobability techniques in the following ways:
a) Probability techniques select sampling units by chance as opposed to the judgment of the researcher.
b) The number of elements to be included in the sample set can be prespecified.
c) It is possible to specify the probability of selecting any particular sample of a given size.
d) Estimates are statistically projectable to the population.
Examples of nonprobability sampling techniques:
Convenience Sampling: Exploratory research
Judgmental Sampling: Test markets selected to determine the potential of a new product
Choice of expert witnesses in a court case
Selection of department stores to test a new merchandising displaysystem
Quota Sampling: Mall intercept interviews
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Snowball Sampling: Interviews with unclassified populations Interviews with very small,
disbursed populations
Advantages and disadvantages of each nonprobability sampling technique:
i) Convenience sampling:
Advantages: Least expensive, Least time consuming, Sampling units are accessible, cooperative, and
easy to measure
Limitations: Many potential sources of bias are present, Not representative of any population, Not able
to generalize findings
ii) Judgmental Sampling:
Advantages: Low cost, Less time consuming than most techniques, Convenient to use
Limitations: No direct generalizations to a specified population, Results entirely dependent on thejudgment of the researcher
iii) Quota Sampling:
Advantages: Lower cost in selecting elements for each quota, Greater convenience in selecting
elements for each quota, With tight controls on interviewers and interviewing, results
can be compared to probability techniques
Limitations: No assurance that a sample is representative, Increasing controls decreases the ease of
conducting the interview, Many sources of bias can be present due to the selection
process
iv) Snowball Sampling:
Advantages: Good at locating and estimating various characteristics that are rare in a population,
Low sample variance and costs when used
Limitations: Difficulty in obtaining the initial sample, Limited to studies of a particular sample
Probability Sampling Techniques-
Simple Random Sampling: The distinguishing features of SRS are:
a) Each element in the population has a known and equal probability of selection.
b) Each possible sample of a given size has a known and equal probability of being the sample actually
selected.
c) A sampling frame must be compiled in which each element has a unique identification number.
d) Random numbers determine which elements are included in the sample.
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Insystematic sampling, the sample is chosen by selecting a random starting point and then pickingevery ith element in succession from the sampling frame. The sampling interval, i, is determined by
dividing the population sizeNby the sample size n and rounding to the nearest integer.
Stratified samplingis a two-step process in which the population is partitioned or stratified into
subpopulations called strata. The strata should be mutually exclusive and collectively exhaustive sothat every population element should be assigned to one and only one stratum and that no population
elements should be omitted. Then, elements are selected from each stratum by a random procedure,usually by SRS.
The criterion for the selection of stratification variables consists of homogeneity, heterogeneity,relatedness, and cost. The stratification variables should be selected so that elements within a stratum
are as homogeneous as possible. However, across strata the elements should be as heterogeneous as
possible. The stratification variables should also be closely related to the characteristic of interest.
Finally, the variables should be selected to decrease the cost of the stratification process, i.e., thestratification variables should be easy to measure and apply.
Proportionate stratified samplinguses strata whose size is proportionate to the relative size of thatstratum in the total population. However, in disproportionate stratified sampling, the size of the sample
from each stratum is proportional to the relative size of that stratum and the standard deviation of the
distribution of the characteristic of interest among all the elements in that stratum. In addition, itrequires that some estimate of the relative variation within the strata be known or estimated.
In cluster sampling, first the target population is divided into mutually exclusive and exhaustive
subpopulations called clusters. Then, a random sample of clusters is selected based on a probabilitysampling technique such as SRS. For each selected cluster, either all the elements are included in the
sample or a sample of elements is drawn probabilistically. If all the elements in each selected cluster
are included in the sample, the procedure is called one-stage cluster sampling. On the other hand, if asample of elements is drawn probabilistically from each selected cluster, the procedure is two-stage
cluster sampling.
In cluster sampling only samples of the subpopulations are chosen, whereas in stratified sampling all of
the subpopulations are chosen. The criteria for forming clusters is the opposite of that for stratification.
Ideally, each cluster should be a representation of the population.
Examples of probability sampling techniques -
Simple Random Sampling: Not widely usedSystematic Sampling: Consumer mail interviews, Telephone interviews, Mall intercept
interviews
Stratified Sampling: Comprehensive, cost effective samplingCluster Sampling: Area sampling, Cost constrained personal interviews
Advantages and disadvantages of each probability sampling technique:
i) Simple Random Sampling :
Advantages: It is easily understood, Sample results may be projected to the target population
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Limitations: Difficult to construct a sample frame which permits a simple random sample to bedrawn. Cost is high because large samples are needed. Results show lower precision with larger
standard errors compared to other techniques. The sample may not be representative
ii) Systematic Sampling :
Advantages: Potential of increased representativeness of the sample versus SRS. Random sampling
is done only once. Can be performed even when knowledge of the composition of the sampling framedoes not exist
Limitations: Ordering of elements is critical. Improper ordering may decrease the representativenessof the sample
iii) Stratified Sampling :
Advantages: Increases the precision of sampling by controlling sources of sample variation. Ensures
all important subpopulations are represented in the sample
Limitations: Disproportionate sampling requires estimates of the population variance to compute
strata size. Extra care must be taken in creating the strata to control for sampling variation
iv) Cluster Sampling:
Advantages: Cost effective sampling method. A sampling frame is needed only for those clusters
selected in the sample
Limitations: Results in samples that have lower precision. Generally difficult to form heterogeneous
clusters. Difficult to compute and interpret statistics based on clusters
Strengths and weaknesses of basic Sampling Techniques
TECHNIQUE STRENGTHS WEAKNESSES
Non Probability Sampling
Convenience Sampling Least expensive, least timeconsuming,
most convenient
Selection bias, sample notrepresentative, not
recommended for descriptive or
causal research
Judgmental Sampling Low cost, convenient, not timeconsuming Does not allow generalization,subjective
Quota Sampling Sample can be controlled for certain
characteristics
Selection bias, no assurance of
representativeness
Snowball Sampling Can estimate rare characteristics Time consuming
Probability Sampling
Simple Random Sampling
(SRS)
Easily understood, result projectable Difficult to construct sampling
frame, expensive, lower
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precision, no assurance ofrepresentativeness
Systematic Sampling Can increase representativeness, easier
to implement than SRS, samplingframe not necessary
Can decrease representativeness
Stratified Sampling Includes all important subpopulations,
precision
Difficult to select relevant
stratification variables, notfeasible to stratify on many
variables, expensive
Cluster Sampling Easy to implement, cost effective Imprecise, difficult to compute
and interpret results
Choice between nonprobability and probability samples:
The nature of the research
relative magnitude of nonsampling versus sampling errors
variability in the population
statistical and operational considerations the homogeneity of the population with respect to the variables of interest
Choosing Nonprobability versus Probability Sampling
CONDITIONS FAVORING USE OF
FACTORS Nonprobabilty Sampling Probability Sampling
Nature of Research Exploratory Conclusive
Relative magnitude of samplingand nonsampling errors
Nonsampling errors are larger Sampling errors are larger
Variability in the population Homogeneous (low) Heterogeneous (high)
Statistical Consideration Unfavorable FavorableOperational Consideration Favorable Unfavorable