Product Analytics : Applied Data Science Techniques for Actionable Consumer Insights
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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)
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
- Whatever your product or service, this guide can help you create precision-targeted marketing campaigns, improve consumer satisfaction and engagement, and grow revenue and profits.
Get Product Analytics by at the best price and quality guaranteed only at Werezi Africa's largest book ecommerce store. The book was published by Pearson Education (US) and it has pages.
