1: Exploring the Terminology 2: The Hierarchy of Goals and Measurements 3: Distinguishing Between Business and Marketing KPIs 4: Choosing the Right Marketing Metrics 5: Single-Channel vs. Multi-Channel Measurement 6: A Brief Overview of Statistics for Marketers 7: Measurement of AI Implementation and AI Model Quality 8: Investing in a Marketing Measurement Framework 9: Components of the Marketing Measurement Framework 10: Incorporating AI-Based Tools and Methods 11: Determining What Data Is Needed 12: Single- and Multi-Channel Data Collection 13: Creating a Sustainable Data Collection Plan 14: Collecting Data in an AI-Driven Marketing Environment 15: Creating a Marketing Dashboard 16: Beginning with a Strong Hypothesis 17: AI-Based Approaches to Prediction and Hypothesis Development 18: Statistical Considerations for Testing 19: Constructing and Running a Single-Channel Test 20: Single-Channel Tests in a Multi-Channel World 21: Multi-Channel Measurement 22: Introduction to Analysis and Improvement 23: Analyzing Your Results 24: Using Generative AI for Analysis 25: Interpreting Results 26: Experimenting, Refining, and Continuous Improvement Epilogue Appendices Index.