This guide shows how to combine data science with social science to gain unprecedented insight into customer behaviour, so you can change it. Joanne Rodrigues bridges the gap between predictive data science and statistical techniques that reveal why important things happen -- why customers buy more, or why they immediately leave your site -- so you can get more behaviours you want and less you don't. Drawing on extensive enterprise experience and deep knowledge of demographics and sociology, Rodrigues shows how to create better theories and metrics, so you can accelerate the process of gaining insight, altering behaviour, and earning business value. You'll learn how to:

Develop complex, testable theories for understanding individual and social behaviour in web products
Think like a social scientist and contextualise 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 behaviour in a complex web product
Understand how relevant human behaviours 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)