Test Bank Marketing Research 12th Edition by Carl McDaniel

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Test Bank Marketing Research 12th Edition by Carl McDaniel

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Test Bank Marketing Research 12th Edition by Carl McDaniel

Marketing Research: Using Analytics to Develop Market Insights teaches students how to use market research to inform critical business decisions

ISBN: 978-1-119-71631-0

Carl McDaniel Jr., Roger Gates

Table of Contents
Preface vii

Acknowledgments ix

1 Steps in Creating Market Insights and the Growing Role of Marketing Analytics 1

Marketing Research and Developing Market Insights 1

Marketing Research Defined 2

Importance of Marketing Research to Management 2

Understanding the Ever-Changing Marketplace 3

Social Media and User-Generated Content 3

Proactive Role of Marketing Research 4

Marketing Analytics Moves to the Forefront 4

The Research Process 4

Recognize the Problem or Opportunity 5

Find Out Why the Information is Being Sought 6

Understand the Decision-Making Environment with Exploratory Research 6

Use the Symptoms to Clarify the Problem 8

Translate the Management Problem into a Marketing Research Problem 9

Determine Whether the Information Already Exists 9

Determine Whether the Question Can Be Answered 10

State the Research Objectives 10

Research Objectives As Hypotheses 11

Marketing Research Process 11

Creating the Research Design 11

Choosing a Basic Method of Research 11

Selecting the Sampling Procedure 13

Collecting the Data 13

Analyzing the Data 13

Presenting the Report 14

Following Up 14

Managing the Research Process 14

The Research Request 14

Request for Proposal 15

The Marketing Research Proposal 16

What to Look for in a Marketing Research Supplier 17

Modifying the Research Process—Marketing Analytics, Big Data, and Unsupervised Learning 17

A Shifting Paradigm 18

What Motivates Decision Makers to Use Research Information? 18

Summary 19

Key Terms 19

Questions for Review & Critical Thinking 20

Working the Net 20

Real-Life Research 1.1: Can Anyone Be a Market Researcher? 21

2 Secondary Data: A Potential Big Data Input 23

Nature of Secondary Data 23

Advantages of Secondary Data 24

Limitations of Secondary Data 25

Internal Databases 27

Creating an Internal Database 27

First, Second, and Third Party Data 27

Behavioral Targeting 28

Big Data 29

The Big Data Breakthrough 29

Making Big Data Actionable in Traditional Marketing Research Environments 30

Battle over Privacy 31

The Federal Trade Commission 32

State Data Privacy Laws 32

The General Data Protection Regulation 32

Summary 33

Key Terms 34

Questions for Review & Critical Thinking 34

Working the Net 34

Real-Life Research 2.1: The GDPR and American Small Business 34

3 Measurement to Build Marketing Insight 36

Measurement Process 36

Step One: Identify the Concept of Interest 37

Step Two: Develop a Construct 38

Step Three: Define the Concept Constitutively 38

Step Four: Define the Concept Operationally 38

Step Five: Develop a Measurement Scale 40

Nominal Level of Measurement 41

Ordinal Level of Measurement 41

Interval Level of Measurement 42

Ratio Level of Measurement 42

Step Six: Evaluate the Reliability and Validity of the Measurement 43

Reliability 45

Validity 47

Reliability and Validity—A Concluding Comment 51

Attitude Measurement Scales 51

Graphic Rating Scales 52

Itemized Rating Scales 53

Traditional One-Stage Format 55

Two-Stage Format 55

Rank-Order Scales 56

Paired Comparisons 56

Constant Sum Scales 56

Semantic Differential Scales 58

Stapel Scales 59

Likert Scales 60

Purchase-Intent Scales 62

Scale Conversions 64

Net Promoter Score (NPS) 65

Considerations in Selecting a Scale 66

The Nature of the Construct Being Measured 66

Type of Scale 67

Balanced versus Nonbalanced Scale 67

Number of Scale Categories 67

Forced versus Nonforced Choice 68

Summary 68

Key Terms 69

Questions for Review & Critical Thinking 70

Working the Net 70

Real-Life Research 3.1: PNC Bank Considers Changing Its Customer Satisfaction Measurement Scale 71

4 Acquiring Data Via a Questionnaire 73

Role of a Questionnaire 73

Criteria for a Good Questionnaire 74

Does It Provide the Necessary Decision-Making Information? 74

Does It Consider the Respondent? 75

Does It Meet Editing Requirements? 75

Does It Solicit Information in an Unbiased Manner: Questionnaire Design Process 76

Step One: Determine Survey Objectives, Resources, and Constraints 77

Step Two: Determine the Data-Collection Method 78

Step Three: Determine the Question Response Format 78

Step Four: Decide on the Question Wording 81

Step Five: Establish Questionnaire Flow and Layout 84

Step Six: Evaluate the Questionnaire 87

Step Seven: Obtain Approval of All Relevant Parties 88

Step Eight: Pretest and Revise 88

Step Nine: Prepare Final Questionnaire Copy 88

Step Ten: Implement the Survey 88

Field Management Companies 89

Avoiding Respondent Fatigue 89

Intelligence Moves Into Questionnaire Coding 90

Conducting Surveys on Smartphones and Tablets 91

The Rapid Growth of Do-It-Yourself (DIY) Surveys 92

Summary 93

Key Terms 94

Questions for Review & Critical Thinking 94

Working the Net 95

Real-Life Research 4.1: Arrow Cleaners 95

5 Sample Design 99

Concept of Sampling 100

Population 100

Sample versus Census 101

Developing a Sampling Plan 101

Step One: Define the Population of Interest 101

Step Two: Choose a Data-Collection Method 104

Step Three: Identify a Sampling Frame 104

Step Four: Select a Sampling Method 104

Step Five: Determine Sample Size 106

Step Six: Develop Operational Procedures for Selecting Sample Elements 106

Step Seven: Execute the Operational Sampling Plan 106

Sampling and Nonsampling Errors 106

Probability Sampling Methods 107

Simple Random Sampling 107

Systematic Sampling 108

Stratified Sampling 109

Cluster Sampling 110

Nonprobability Sampling Methods 111

Convenience Samples 111

Judgment Samples 111

Quota Samples 112

Snowball Samples 112

Internet Sampling 112

Determining Sample Size 113

Determining Sample Size for Probability Samples 113

Budget Available 113

Rule of Thumb 114

Number of Subgroups Analyzed 114

Traditional Statistical Methods 115

Normal Distribution 115

General Properties 115

Basic Concepts 116

Making Inferences on the Basis of a Single Sample 118

Point and Interval Estimates 118

Sampling Distribution of the Proportion 119

Determining Sample Size 120

Problems Involving Means 120

Problems Involving Proportions 122

Determining Sample Size for Stratified and Cluster Samples 123

Sample Size for Qualitative Research 123

Population Size and Sample Size 124

Summary 125

Key Terms 126

Questions for Review & Critical Thinking 126

Working the Net 127

Real-Life Research 5.1: Insights Research Group (IRG) 127

6 Traditional Survey Research 129

Why Decision Makers Like Survey Research 129

Types of Errors in Survey Research 130

Sampling Error 130

Systematic Error 131

Types of Surveys 135

Door-to-Door Interviews 135

Executive Interviews 136

Mall-Intercept Interviews 136

Telephone Interviews 137

Self-Administered Questionnaires 138

Mail Surveys 139

Determination of the Survey Method 141

Sampling Precision 141

Budget 141

Requirements for Respondent Reactions 142

Quality of Data 142

Length of the Questionnaire 142

Incidence Rate 143

Structure of the Questionnaire 143

Time Available to Complete the Survey 143

Summary 144

Key Terms 144

Questions for Review & Critical Thinking 145

Real-Life Research 6.1: Do Consumers Like Chatbots? 145

7 Qualitative Research 146

Nature of Qualitative Research 146

Qualitative Research versus Quantitative Research 147

The Use of Qualitative Research 147

Limitations of Qualitative Research 148

Focus Groups 149

Popularity of Focus Groups 149

Conducting Focus Groups 150

Focus Group Trends 157

Benefits and Drawbacks of Focus Groups 158

Other Qualitative Methodologies 159