• Develop complex, testable theories for understanding individual and social behavior in web products
• Think like a social scientist and contextualize individual behavior in today’s social environments
• Build more effective metrics and KPIs for any web product or system
• Conduct more informative and actionable A/B tests
• Explore causal effects, reflecting a deeper understanding of the differences between correlation and causation
• Alter user behavior in a complex web product
• Understand how relevant human behaviors develop, and the prerequisites for changing them
• Choose the right statistical techniques for common tasks such as multistate and uplift modeling
• Use advanced statistical techniques to model multidimensional systems
• Do all of this in R (with sample code available in a separate code manual)

• Build better theories and metrics, and drive more of the behaviors you want
• Model, understand, and alter customer behavior to increase revenue and retention
• Construct better frameworks for examining why your customers do what they do
• Develop core metrics for user analytics, and conduct more effective A/B tests
• Master key techniques that most books ignore, including statistical matching and uplift modeling
• Use R and this book’s many R examples to implement these techniques yourself

Use data science and social science to generate real changes in customer behavior

• Build better theories and metrics, and drive more of the behaviors you want
• Model, understand, and alter customer behavior to increase revenue and retention
• Construct better frameworks for examining why your customers do what they do
• Develop core metrics for user analytics, and conduct more effective A/B tests
• Master key techniques that most books ignore, including statistical matching and uplift modeling
• Use R and this book’s many R examples to implement these techniques yourself