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This guide shows how to combine data science with social science to
gain unprecedented insight into customer behavior, so you can
change it. Joanne Rodrigues-Craig 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 behaviors you
want and less you don't. Drawing on extensive enterprise experience
and deep knowledge of demographics and sociology, Rodrigues-Craig
shows how to create better theories and metrics, so you can
accelerate the process of gaining insight, altering behavior, and
earning business value. You'll learn how to: 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)
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