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MARKETING RESEARCH:

FROM INFORMATION

TO ACTION

CHAPTER

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AFTER READING THIS CHAPTERYOU SHOULD BE ABLE TO:

1. Identify the reason for doing marketing research and describe the five-step marketing research approach leading to marketing actions.

2. Describe how secondary and primary data are used in marketing, including the uses of questionnaires, observations, experiments, and panels.

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AFTER READING THIS CHAPTERYOU SHOULD BE ABLE TO:

3. Explain how information technology and data mining link massive amounts of marketing information to meaningful marketing actions.

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TEST SCREENINGS: LISTENING TO CONSUMERS TO REDUCE MOVIE RISKS

• What’s in aMovie Name?

• The Risks inToday’sBlockbusterMovies

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TEST SCREENINGS: LISTENING TO CONSUMERS TO REDUCE MOVIE RISKS

• UsingMarketingResearch toReduce MovieRisk

Test Screenings

Tracking Studies

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FIGURE 8-1FIGURE 8-1 Marketing research questions asked in test screenings of movies, and how they are used

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THE ROLE OFMARKETING RESEARCH

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• What is Marketing Research?

Decision

• Why Good Marketing Research is Difficult

• Five-Step Marketing Research Approach to Make Better Decisions

Decision Making

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FIGURE 8-2FIGURE 8-2 Five-step marketing research approach leading to better marketing actions

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STEP 1: DEFINE THE PROBLEM

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• Set the Research Objectives

• Descriptive Research

Objectives

Three Kinds of Research

• Causal Research

• Exploratory Research

• Identify Possible Marketing Actions

Measures of Success

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Fisher-Price How do you define the problem?

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Fisher-Price How do you discover “hot toys” andwhy are good forecasts important?

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STEP 2: DEVELOP THERESEARCH PLAN

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• Determine How to Collect Data

Methods

• New-Product Concept

Concepts

• Sampling

• Probability Sampling

• Nonprobability Sampling

• Statistical Inference

• Specify Constraints

• Identify Data Needed for Marketing Actions

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STEP 3: COLLECTRELEVANT INFORMATION

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• Data

• Secondary Data

• Primary Data

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FIGURE 8-3 FIGURE 8-3 Types of marketing information

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STEP 3: COLLECTRELEVANT INFORMATION

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Internal Secondary Data

• Census Bureau

• Secondary Data

External Secondary Data

• Periodicals/Journals

• Syndicated

• Data Services

Advantages and Disadvantages of Secondary Data

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WEB LINK

Online Databases and Internet Resources Useful for Marketers

LexisNexis

ProQuest

Bloomberg

STAT-USA

FirstGov

Google

Wall Street Journal

Investor’s Daily

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STEP 3: COLLECTRELEVANT INFORMATION

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Observational Data

• Meter/Diary

• Primary Data

• Mystery Shopper

• Ethnographic Research

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Nielsen Media Research “People Meter”What kind of primary data is collected?

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FIGURE 8-4 FIGURE 8-4 Nielsen ratings of the top 10 national television programs fromSeptember 27, 2004 through October 3, 2004

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FIGURE 8-5 FIGURE 8-5 Nielsen//NetRatings of the top 10 Internet websites for September 2004

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STEP 3: COLLECTRELEVANT INFORMATION

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Questionnaire Data

• Individual Interviews

• Primary Data

• Focus Groups

• “Cool Hunters”

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STEP 3: COLLECTRELEVANT INFORMATION

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Questionnaire Data

• Types of Surveys

• Primary Data

Personal Interview

Mail

Telephone

E-mail/Fax/Internet

Mall Intercept Interview

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FIGURE 8-AFIGURE 8-A Comparison of three kinds of surveys

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FIGURE 8-6 FIGURE 8-6 Typical problems in wording questions

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STEP 3: COLLECTRELEVANT INFORMATION

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• Question Formats

Questionnaire Data

• Primary Data

Open-Ended

Closed-Ended/Fixed Alternative

Dichotomous

Semantic Differential Scale

Likert Scale

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FIGURE 8-7AFIGURE 8-7A Sample questions from Wendy’s survey

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FIGURE 8-7BFIGURE 8-7B Sample questions from Wendy’s survey

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STEP 3: COLLECTRELEVANT INFORMATION

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Panels and Experiments

• Panel

• Experiment

• Drivers

• Test Markets

Advantages and Disadvantages of Primary Data

• Primary Data

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STEP 3: COLLECTRELEVANT INFORMATION

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The Marketing Manager’s View of Sales Drivers

• Data vs. Information

• Using Information Technology to Trigger Marketing Actions

• Information Technology

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STEP 3: COLLECTRELEVANT INFORMATION

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Key Elements of an Information System

• Data Warehouse

• Using Information Technology to Trigger Marketing Actions

• Sensitivity Analysis

Data Mining: A New Approach to Searching the Data Ocean

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FIGURE 8-9 FIGURE 8-9 How marketing researchers and managers use information technology to turn information into action

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STEP 4: DEVELOP FINDINGS

• Set the Research Objectives

Analyze the Data

Present the Findings

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STEP 5: TAKE MARKETING ACTIONS

• Make Action Recommendations

Evaluating the Decision Itself

• Implement the Action Recommendations

• Evaluate the Results

Evaluating the Decision Process Used

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Marketing Research

Marketing research is the processof defining a marketing problem and opportunity, systematically collectingand analyzing information, and recommending actions.

Marketing research is the processof defining a marketing problem and opportunity, systematically collectingand analyzing information, and recommending actions.

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Decision

A decision is a conscious choice from among two or more alternatives.A decision is a conscious choice from among two or more alternatives.

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Measures of Success

Measures of success are criteria or standards used in evaluating proposed solutions to a problem.

Measures of success are criteria or standards used in evaluating proposed solutions to a problem.

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Constraints

Constraints in a decision are the restrictions placed on potential solutions to a problem.

Constraints in a decision are the restrictions placed on potential solutions to a problem.

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Sampling

Sampling involves selecting representative elements from a population.

Sampling involves selecting representative elements from a population.

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Probability Sampling

Probability sampling involves using precise rules to select the sample such that each element of the population has a specific known chance of being selected.

Probability sampling involves using precise rules to select the sample such that each element of the population has a specific known chance of being selected.

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Nonprobability Sampling

Nonprobability sampling involves using arbitrary judgments to select the sample so that the chance of selecting a particular element may be unknown or 0.

Nonprobability sampling involves using arbitrary judgments to select the sample so that the chance of selecting a particular element may be unknown or 0.

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Statistical Inference

Statistical inference involves drawing conclusions about a population from a sample taken from that population.

Statistical inference involves drawing conclusions about a population from a sample taken from that population.

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Data

Data are the facts and figures relatedto the problem, and are divided into two main parts: secondary data and primary data.

Data are the facts and figures relatedto the problem, and are divided into two main parts: secondary data and primary data.

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Secondary Data

Secondary data are facts and figuresthat have already been recorded before the project at hand.

Secondary data are facts and figuresthat have already been recorded before the project at hand.

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Primary Data

Primary data are facts and figuresthat are newly collected for the project.Primary data are facts and figuresthat are newly collected for the project.

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Observational Data

Observational data are the facts and figures obtained by watching, either mechanically or in person, how people actually behave.

Observational data are the facts and figures obtained by watching, either mechanically or in person, how people actually behave.

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Questionnaire Data

Questionnaire data are the facts and figures obtained by asking people about their attitudes, awareness, intentions, and behaviors.

Questionnaire data are the facts and figures obtained by asking people about their attitudes, awareness, intentions, and behaviors.

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Information Technology

Information technology involves a computer and communication system to satisfy an organization’s needs for data storage, processing, and access.

Information technology involves a computer and communication system to satisfy an organization’s needs for data storage, processing, and access.

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Data Mining

Data mining is the extraction of hidden predictive information from large databases.

Data mining is the extraction of hidden predictive information from large databases.