9780135258521

Applied Data Science Transforming User Data into Actionable Insights

by
  • ISBN13:

    9780135258521

  • ISBN10:

    0135258529

  • Edition: 1st
  • Format: Paperback
  • Copyright: 2019-01-16
  • Publisher: Addison-Wesley Professional
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Supplemental Materials

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  • The New copy of this book will include any supplemental materials advertised. Please check the title of the book to determine if it should include any access cards, study guides, lab manuals, CDs, etc.

Summary

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)

Table of Contents

Part I: The Basics
1 Data in Action
2. Building a Theory of the Universe
3. No Effect? Missteps in Metric Creation and Interpretation
4. Why Are My Users Leaving?
5. The Coveted Goal Post: How to Change Human Behavior

Part II: Advanced Analytics Tools
6. What Groups Should We Target?
7. Generating Insight
8. Which users will leave?
9. The Life of a Web Product
Part III: Applying R Statistical Tools

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