CONSUMER RESEARCH PROCESS
Chapter 6
CONSUMER RESEARCH PROCESS
•
Before moving into the consumer
research process, let us first understand a
very key issue in consumer research, i.e.,
the difference between market research
and marketing research.
• Marketing Research vs. Market Research
You will find that these terms often are used inter
changeably, but technically there is a difference.
Market research deals specifically with the
gathering of information about a market’s
size and trends. Marketing research covers a
wider range of activities. While it may involve
market research, marketing research is a more
general systematic process that can be applied
to a variety of marketing problems.
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THE EIGHT-STEP RESEARCH PROCESS
•
We are depicting the consumer research process in eight steps:
1. 1a. Problem/opportunity identification, 1b. Problem/opportunity formulation
2. Create the research design
3. Choosing a basic method of research
4. Selecting the sampling procedure
5. Data collection
6. Data analysis
7. Preparing and writing the report
8. Follow-up
STEP ONE A: PROBLEM/OPPORTUNITY
IDENTIFICATION
• 1. The research process begins with the recognition of a
business problem or opportunity.
2. Problem/opportunity emerges when: Environment change.
3. Examples: Technological breakthrough, new legal policy,
social change, high unemployment rate
4. How to know there is an environmental change?
Continuous information collection/search, internal data,
managerial experience, or even gut feeling may help.
5. Two fundamental questions that is asked: (1) should we alter
our marketing mix in order to perform better? (2) If so, what
should we do?
6. Another important question could be: Can we predict possible
environmental change? This can be done by using historical
data and trying to find trend and factors that
affect the emergence of such trend.
STEP TWO: CREATING THE RESEARCH DESIGN
• 1. A plan that researchers follow to answer the research
objectives and/or test the hypotheses.
2. Whether the design will be Descriptive and/or Causal
(diagnostic and predictive)?
3. Descriptive design: Answer the questions who, what,
when, and how.
4. In quantitative research, we may calculate the mean,
median, mode or S.D. of the data collected. For example:
35% of the respondents said they like classical music.
5. Causal design: Examine whether one variable causes or
determine the value of another variable (two variables at
least).
6. Independent variable (The cause, example demographic
variables) and dependent variable (the outcome, musical
preference). 7. In quantitative research, you may use regression analysis to
analyze the association between two (or more) variables.
For example, the older the respondent, the more he likes
classical music.
STEP THREE: CHOOSING A BASIC METHOD OF
RESEARCH
•
1. Analysis of secondary data.
2. Survey. Obtain factual (e.g., age) and attitudinal (e.g.,
musical preference) data.
3. Observation. Obtain behavioral data, researchers and
subjects do not have direct interaction.
4. Experiment. The researchers deliberately change the
independent variable(s) and record the effects of that
(those) variable(s) on other dependent variable(s).
Experiments are frequently used in testing causality.
STEP FOUR: SELECTING THE SAMPLING
PROCEDURE
• 1. Sample is a subset of the whole population.
2. Why sampling? May be…Population is too
big, population unknown, insufficient resources
to conduct a census.
3. Sample should be “representative” – should
help the researchers to make inference about
the population.
STEP FIVE: DATA COLLECTION
•
1. Under a natural or controlled environment?
Especially important for experimental designs.
2. Survey: Mall intercept, telephone, mail,
Internet…each method has different advantages
and disadvantages. For example, response time,
response rate, structure of questions, costs, etc.
STEP SIX: DATA ANALYSIS
• 1. It’s a process that interprets the observed
data into meaningful information.
2. In this module, I will teach you how to use ttest, analysis of variance (ANOVA) and bivariate
regression analysis to analyze the data.