Behavioral AI

ROGAYEH TABRIZI, PHD, is the founder and CEO of Theory+Practice, a technology company with deep expertise in AI and data and specializes in helping large CPG and Retail enterprises utilize their data to radically enhance revenue ­optimization decisions. She has a PhD in Economics and a MSc in Particle Physics and worked on the ATLAS detector at CERN.

Preface xi 

Chapter 1 Magic Happens at the Intersections 1 

Asking the Right Questions: Data, Intuition, and Strategy 3 

Simplifying the Complexity 6 

Connecting the Dots 8 

Uncovering Hidden Patterns: Models and Algorithms in Action 10 

Decoding Consumer Behavior: The Interplay of Psychology and Economics 11 

Empowering Behavioral Economics: The Synergy of Data Analytics, ML, and AI 14 

Crafting a Customer- Centric Paradigm: The Fusion of Technology and Behavioral Insights 17 

Chapter 2 It Is All Connected: Behavioral Economics, Decision-Making, Biases, and Heuristics 19 

History and Origins of Behavioral Economics 20 

Early Days 21 

Entering Mainstream Economics 23 

Current Research and Practical Applications 26 

Back to the Beginning 30 

Psychology of Decision- Making 33 

Dual- Process Theories 33 

Heuristics and Biases 35 

Noise 39 

Prospect Theory 40 

Nudging 42 

Experimentation 46 

How It Works 47 

Uber and Experimentation 49 

Chapter 3 Minimal Data, Maximal Impact: From Big Data to Minimum Viable Data 53 

How Much Data Are We Talking About? Lots and Lots 55 

You Do Not Need a Lot of Data to Get Started, You Need the MVD 58 

Asking the Right Questions, Again! 59 

Synthetic Data: What It Is and What It Isn’t 63 

Survey Data to the Rescue 67 

Chapter 4 Building Intelligence: AI and ML Essentials, Transforming Data into Intelligence 73 

Classical AI 76 

ML 78 

Deep Learning 82 

Generative AI 86 

Machine Intelligence and Biologically Inspired Models 90 

Chapter 5 Real-World Impact: Harnessing AI and ml for Practical Solutions 95 

Unleashing the Full Potential of AI: Beyond the Hype 96 

Rethinking Segmentation: Beyond Demographics and Life Stages 97 

Uncovering Unexpected Customer Patterns 101 

Predicting Intent and Mapping Customer Journeys 104 

Overcoming Challenges in Predicting Customer Intent 106 

Predicting and Managing Returns 108 

The Power and Nuances of Recommendation Models 111 

Broadening Horizons: Beyond Category Killers 114 

Enhancing In- Store Experience with Recommendation Models 116 

Leveraging Propensity Models for Targeted Campaigns 118 

Personalized Pricing: Influencing Behaviors and Financial Outcomes 121 

Behavioral Economics in Personalized Pricing Strategies 124 

Forecasting: Understanding the Dynamics of Demand 127 

The Power of Forecasting and Optimization 131 

Transparent MMMs 132 

Ensembling Models for Enhanced Forecasting 133 

The Interplay of Demand Forecasting and Inventory Optimization 133 

Conclusion 135 

Chapter 6 Decoding Complexity: Leveraging Systems Thinking in Modern Organizations 137 

Only a Wet Baby Likes Change: Loss Aversion + Status Quo Bias 140 

It Gets Better! Commitment Device, Peer Effect, and Sunk Cost Fallacy 145 

Conclusion 151 

Chapter 7 Unlocking Scale: Overcoming Operational and Organizational Complexity in Scaling AI Projects 155 

Enablers of Success 156 

Communication and Intellectual Diversity 159 

Building Trust, Experimentation, and Adoption 164 

Interpretation Layers 166 

The Power of Experimentation 169 

Measuring ROI Through Experimentation 171 

Conclusion 173 

Epilogue 175 

Notes 179 

Additional Reading 189 

Bibliography 197 

Acknowledgments 205 

About the Author 207 

Index 209