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Introduction 1 About This Book 1 Foolish Assumptions 2 Icons Used in This Book 2 Beyond the Book 3 Where to Go from Here 3
Part I: Getting Started with Customer Analytics 5
Chapter 1: Introducing Customer Analytics 7 Defining Customer Analytics 7 The benefits of customer analytics 8 Using customer analytics 11 Compiling Big and Small Data 12
Chapter 2: Embracing the Science and Art of Metrics 15 Adding up Quantitative Data 15 Discrete and continuous data 16 Levels of data 16 Variables 19 Quantifying Qualitative Data 20 Determining the Sample Size You Need 22 Estimating a confidence interval 24 Computing a 95% confidence interval 25 Determining What Data to Collect 27 Managing the Right Measure 28
Chapter 3: Planning a Customer Analytics Initiative 31 A Customer Analytics Initiative Overview 31 Defining the Scope and Outcome 33 Identifying the Metrics, Methods, and Tools 34 Setting a Budget 35 Determining the Correct Sample Size 36 Analyzing and Improving 37 Controlling the Results 38
Part II: Identifying Your Customers 41
Chapter 4: Segmenting Customers 43 Why Segment Customers 43 Segmenting by the Five W''s 47 Who 47 Where 48 What 49 When 52 Why 52 How 52 Analyzing the Data to Segment Your Customers 53 Step
1: Tabulate your data 53 Step
2: Cross-Tabbing 54 Step
3: Cluster Analysis 56 Step
4: Estimate the size of each segment 57 Step 5 Estimate the value of each segment 57
Chapter 5: Creating Customer Personas 61 Recognizing the Importance of Personas 61 Working with personas 64 Getting More Personal with Customer Data 66 Step
1: Collecting the appropriate data 66 Step
2: Dividing data 68 Step
3: Identifying and refining personas 68 Answering Questions with Personas 71
Chapter 6: Determining Customer Lifetime Value 75 Why your CLV is important 76 Applying CLV in Business 77 Calculating Lifetime Value 77 Estimating revenue 78 Calculating the CLV 80 Identifying profitable customers 82 Marketing to profitable customers 82
Part III: Analytics for the Customer Journey 85
Chapter 7: Mapping the Customer Journey 87 Working with the Traditional Marketing Funnel 87 What Is a Customer Journey Map? 91 Define the Customer Journey 93 Finding the data 93 Sketching the journey 94 Making the map more useful 101
Chapter 8: Determining Brand Awareness and Attitudes 103 Measuring Brand Awareness 103 Unaided awareness 104 Aided awareness 105 Measuring product or service knowledge 106 Measuring Brand Attitude 107 Identifying brand pillars 108 Checking brand affinity 108 Measuring Usage and Intent 110 Finding out past usage 110 Measuring future intent 110 Understanding the Key Drivers of Attitude 111 Structuring a Brand Assessment Survey 111
Chapter 9: Measuring Customer Attitudes 113 Gauging Customer Satisfaction 113 General satisfaction 114 Attitude versus satisfaction 115 Rating Usability with the SUS and SUPR-Q 117 System Usability Scale (SUS) 117 Standardized User Experience Percentile Rank Questionnaire (SUPR-Q) 120 Measuring task difficulty with SEQ 122 Scoring Brand Affection 123 Finding Expectations: Desirability and Luxury 125 Desirability 125 Luxury 125 Measuring Attitude Lift 126 Asking for Preferences 128 Finding Your Key Drivers of Customer Attitudes 129 Writing Effective Customer Attitude Questions 131
Chapter 10: Quantifying the Consideration and Purchase Phases 133 Identifying the Consideration Touchpoints 133 Company-driven touchpoints 134 Customer-driven touchpoints 134 Measuring the Customer-Driven Touchpoints 135 Measuring the Three R''s of Company-Driven Touchpoints 137 Reach 137 Resonance 137 Reaction 138 Measuring resonance and reaction 139 Tracking Conversions and Purchases 139 Tracking micro conversions 140 Creating micro-conversion opportunities 141 Setting up conversion tracking 142 Measuring conversion rates 142 Measuring Changes through A/ B Testing 143 Offline A/B testing 144 Online A/B testing 144 Testing multiple variables 148 Making the Most of Website Analytics 148
Chapter 11: Tracking Post-Purchase Behavior 151 Dealing with Cognitive Dissonance 152 Reducing dissonance 152 Turning dissonance into satisfaction 153 Tracking return rates 153 Measuring the Post-Purchase Touchpoints 154 Digging into the post-purchase touchpoints 155 Assessing post-purchase satisfaction ratings 158 Finding Problems Using Call Center Analysis 159 Finding the Root Cause with Cause-and-Effect Diagrams 160 Creating a cause-and-effect diagram 161
Chapter 12: Measuring Customer Loyalty 163 Measuring Customer Loyalty 164 Repurchase rate 164 Net Promoter Score 166 Bad profits 174 Finding Key Drivers of Loyalty 177 Valuing positive word of mouth 178 Valuing negative word of mouth 182
Part IV: Analytics for Product Development 185
Chapter 13: Developing Products That Customers Want 187 Gathering Input on Product Features 187 Finding Customers'' Top Tasks 188 Listing the tasks 189 Finding customers 189 Selecting five tasks 190 Graphing and analyzing 190 Taking an internal view 191 Conducting a Gap Analysis 193 Mapping Business Needs to Customer Requirements 194 Identifying customers'' wants and needs 195 Identifying the voice of the customer 196 Identifying the how''s (the voice of the company) 196 Building the relationship between the customer and company voices 197 Generating priorities 197 Examining priorities 198 Measuring Customer Delight with the Kano Model 199 Assessing the Value of Each Combination of Features 200 Finding Out Why Problems Occur 202
Chapter 14: Gaining Insights through a Usability Study 207 Recognizing the Principles of Usability 207 Conducting a Usability Test 208 Determining what you want to test 209 Identifying the goals 209 Outlining task scenarios 209 Recruiting users 212 Testing your users 215 Collecting metrics 216 Coding and analyzing your data 218 Summarizing and presenting the results 218 Considering the Different Types of Usability Tests 218 Finding and Reporting Usability Problems 221 Facilitating a Usability Study 225
Chapter 15: Measuring Findability and Navigation 231 Finding Your Areas of Findability 232 Identifying What Customers Want 233 Prepping for a Findability Test 235 Finding your baseline 235 Designing the study 235 Looking at your findability metrics 237 Conducting Your Findability Study 240 Determining sample size 240 Recruiting users 241 Analyzing the results 242 Improving Findability 244 Cross-linking products 244 Regrouping categories 245 Rephrasing the tasks 245 Measuring findability after changes 246
Chapter 16: Considering the Ethics of Customer Analytics 249 Getting Informed Consent 249 Facebook 250 OKCupid 251 Amazon and Orbitz 251 Mintcom 252 Deciding to Experiment 252
Part V: The
Part of Tens 255
Chapter 17: Ten Customer Metrics You Should Collect 257
Chapter 18: Ten Methods to Improve the Customer Experience 263
Chapter 19: Ten Common Analytic Mistakes 267
Chapter 20: Ten Methods for Identifying Customer Needs 271 Appendix: Predicting with Customer Analytics 277 Finding Similarities and Associations 278 Visualizing associations 279 Quantifying the strength of a relationship 280 Associations between binary variables 284 Determining Causation 288 Randomized experimental study 288 Quasi-experimental design 289 Correlational study 290 Single-subjects study 290 Anecdotes 291 Predicting with Regression 291 Predicting with the regression line 293 Creating a regression equation in Excel 294 Multiple regression analysis 296 Predicting with binary data 300 Predicting Trends with Time Series Analysis 301 Exponential (non-linear) growth 304 Training and validation periods 306 Detecting Differences 308 Index 311