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

Individual Depth Interviews 159

Projective Tests 163

Summary 167

Key Terms 167

Questions for Review & Critical Thinking 167

Working the Net 168

Real-Life Research 7.1: A Sound Approach for the Sound 168

8 Online Marketing Research: The Growth of Mobile and Social Media Research 171

Using the Internet for Secondary Data 172

Online Qualitative Research 172

Online Bulletin Boards 172

Webcam and Streaming Technology Focus Groups 173

Using the Internet to Find Online Participants 174

Online Individual Depth Interviews (IDIs) 175

Online Survey Research 175

Advantages of Online Surveys 175

Disadvantages of Online Surveys 176

Tools for Conducting Online Surveys 177

Commercial Online Panels 178

Panel Recruitment 178

Open Recruitment 178

Closed Recruitment 179

Respondent Participation 179

Panel Management 180

Mobile Internet Research—The Future is Now 180

Advantages of Mobile 181

Designing a Mobile Survey 181

Social Media Marketing Research 182

Summary 182

Key Terms 183

Questions for Review & Critical Thinking 183

Working the Net 183

Real-Life Research 8.1: Shoppers Spending More In-Store Than Online 183

9 Primary Data Collection: Observation 185

Nature of Observation Research 185

Conditions for Using Observation 186

Approaches to Observation Research 186

Advantages of Observation Research 188

Disadvantages of Observation Research 189

Human Observation 189

Ethnographic Research 189

Mobile Ethnography 192

Mystery Shoppers 192

One-Way Mirror Observations 194

Machine Observation 194

Neuromarketing 194

Facial Action Coding Services (FACS) 197

Gender and Age Recognition Systems 199

In-Store Tracking 199

Television and Video Audience Measurement and Tracking 200

Symphony IRI Consumer Network 200

Tracking 201

Magazines Track Online Readers and Apply It Also to Print 201

Social Media Tracking 202

Virtual Reality and Augmented Reality Marketing Research 204

Summary 204

Key Terms 205

Questions for Review & Critical Thinking 205

Working the Net 206

Real-Life Research 9.1: Bausch & Lomb Fine-Tune the Details 206

10 Marketing Analytics 208

What is Marketing Analytics? 209

The Marketing Analytics Process 210

Getting the Data 210

Big Data Sources 210

Data from Traditional Sources 211

Organizing, Merging, and Using Big Data 212

Acting on Results of Analysis 212

Big Data 212

Background on Big Data Issues 212

How Does It Work? 213

Analyzing Data: Descriptive, Predictive, and Prescriptive Analytics 214

Descriptive Analytics 214

Predictive Analytics 214

Prescriptive Analytics 215

Advanced Analytical Methods 216

Data Mining 216

Machine and Deep Learning 219

Artificial Intelligence or AI 220

Data Visualization 224

Infographics 225

Marketing Dashboards 225

Privacy Issues 226

Privacy versus Customization 226

Summary 228

Key Terms 229

Questions for Review & Critical Thinking 229

Working the Net 230

Real-Life Research 10.1: Affiliated Parking Systems Looks to New Pricing Approach 230

11 Primary Data: Experimentation and Test Markets 231

What is an Experiment? 232

Demonstrating Causation 232

Concomitant Variation 233

Appropriate Time Order of Occurrence 233

Elimination of Other Possible Causal Factors 233

Experimental Setting 234

Laboratory Experiments 234

Field Experiments 234

Experimental Validity 234

Experimental Notation 235

Extraneous Variables 235

Examples of Extraneous Variables 236

Controlling Extraneous Variables 237

Experimental Design, Treatment, and Effects 238

Limitations of Experimental Research 239

High Cost 239

Security Issues 239

Implementation Problems 239

Selected Experimental Designs 240

Preexperimental Designs 240

True Experimental Designs 241

Quasi-Experiments 242

Test Markets 244

Types of Test Markets 245

Decision to Conduct Test Marketing 248

Steps in a Test Market Study 249

Summary 252

Key Terms 252

Questions for Review & Critical Thinking 253

Working the Net 254

Real-Life Research 11.1: Los Lobos Beer 254

12 Data Processing and Basic Data Analysis 255

Overview of Data Analysis Procedure for Survey Research 256

Step One: Validation and Editing of Paper Surveys 256

Validation 256

Quality Assurance for Internet Panels 257

Quality Assurance—Respondent Cooperation and Attention Issues 258

Special Issues with Big Data 260

Editing 260

Step Two: Coding 264

Coding Process 265

Automated Coding Systems and Text Processing 266

Intelligent Capture Systems 267

The Data Capture Process 268

Scanning 268

Step Four: Logical Cleaning of Data 269

Step Five: Tabulation and Statistical Analysis 269

One-Way Frequency Tables 269

Cross Tabulations 272

Death of Crosstabs? 274

Graphic Representations of Data 274

Line Charts 275

Pie Charts 275

Bar Charts 275

Descriptive Statistics 278

Measures of Central Tendency 278

Measures of Dispersion 279

Percentages and Statistical Tests 280

Summary 281

Key Terms 281

Questions for Review & Critical Thinking 282

Working the Net 284

Real-Life Research 12.1: Buzzy’s Tacos 284

13 Statistical Testing of Differences and Relationships 285

Evaluating Differences and Changes 286

Statistical Significance 286

Hypothesis Testing 287

Steps in Hypothesis Testing 288

Types of Errors in Hypothesis Testing 290

Accepting H0 versus Failing to Reject (FTR) H0 292

One-Tailed versus Two-Tailed Test 292

Example of Performing a Statistical Test 292

Commonly Used Statistical Hypothesis Tests 295

Independent versus Related Samples 295

Degrees of Freedom 295

Goodness of Fit 296

Chi-Square Test 296

Hypotheses about One Mean 299

t Test 299

Hypotheses about Two Means 300

Hypotheses about Proportions 302

Proportion in One Sample 302

Two Proportions in Independent Samples 303

Analysis of Variance (ANOVA) 305

p Values and Significance Testing 308

Summary 309

Key Terms 309

Questions for Review & Critical Thinking 310

Working the Net 311

Real-Life Research 13.1: Analyzing William D. Scott (WDS) Segmentation Results 312

14 More Powerful Statistical Methods 313

Data Scientist—Hot New Career 313

Bivariate Statistical Analysis 314

Bivariate Analysis of Relationships 314

Bivariate Regression 314

Nature of the Relationship 315

Example of Bivariate Regression 316

Correlation for Metric Data: Pearson’s Product–Moment Correlation 322

Multivariate Analysis Procedures 323

Multivariate Software 324

Multiple Regression Analysis 324

Applications of Multiple Regression Analysis 325

Multiple Regression Analysis Measures 326

Dummy Variables 327

Potential Use and Interpretation Problems 327

Multiple Discriminant Analysis 328

Applications of Multiple Discriminant Analysis 329

Cluster Analysis 330

Procedures for Clustering 330

Applications of Cluster Analysis 331

Factor Analysis 332

Factor Scores 332

Factor Loadings 334

Naming Factors 334

Number of Factors to Retain 335

Conjoint Analysis 335

Simulating Buyer Choice 335

Limitations of Conjoint Analysis 336

Neural Networks 337

Description of a Neural Network 337

How Neural Networks “Learn” 338

When Neural Networks Are Appropriate 338

Limitations of Neural Networks 338

Predictive Analytics 339

Using Predictive Analytics 339

Privacy Concerns and Ethics 341

Commercial Predictive Modeling Software and Applications 341

Summary 341

Key Terms 342

Questions for Review & Critical Thinking 343

Working the Net 345

Real-Life Research 14.1: Satisfaction Research for Pizza Pronto 345

15 Communicating Analytics and Research Insights 347

The Research Report 347

Organizing the Report 348

Format of the Report 349

Formulating Recommendations 349

Presenting the Results 355

Making a Presentation 356

Infographics 356

Presentations by Internet 358

Summary 358

Key Terms 359

Questions for Review & Critical Thinking 359

Working the Net 359

Real-Life Research 15.1: TouchWell Storefront Concept and Naming Research 359

Appendix A A-1

[Appendix B and C are available online at www.wiley.com/go/mcdaniel/marketingresearch12e]

Endnotes N-1

Glossary G-1

QSR Survey QS-1

Index I-1

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