Product Analytics: Applied Data Science Techniques for Actionable Consumer Insights
Product Analytics: Applied Data Science Techniques for Actionable Consumer Insights
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)
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Artikelbeschreibung
Product Analytics is a complete, hands-on guide to generating actionable business insights from customer data. Experienced data scientist and enterprise manager Joanne Rodrigues introduces practical statistical techniques for determining why things happen and how to change what people do at scale. She complements these with powerful social science techniques for creating better theories, designing better metrics, and driving more rapid and sustained behavior change.
Writing for entrepreneurs, product managers/marketers, and other business practitioners, Rodrigues teaches through intuitive examples from both web and offline environments. Avoiding math-heavy explanations, she guides you step by step through choosing the right techniques and algorithms for each application, running analyses in R, and getting answers you can trust.
- Develop core metrics and effective KPIs for user analytics in any web product
- Truly understand statistical inference, and the differences between correlation and causation
- Conduct more effective A/B tests
- Build intuitive predictive models to capture user behavior in products
- Use modern, quasi-experimental designs and statistical matching to tease out causal effects from observational data
- Improve response through uplift modeling and other sophisticated targeting methods
- Project business costs/subgroup population changes via advanced demographic projection
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