Product Analytics: Applied Data Science Techniques for Actionable Consumer Insights (Paperback) (產品分析:可行的消費者洞察應用數據科學技術)

Rodrigues-Craig, Joanne

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商品描述

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)

商品描述(中文翻譯)

本指南展示了如何將數據科學與社會科學相結合,以獲得對客戶行為的前所未有的洞察力,從而改變它。Joanne Rodrigues-Craig彌合了預測性數據科學和揭示重要事件原因的統計技術之間的差距,例如為什麼客戶購買更多,或者為什麼他們立即離開您的網站,以便您可以獲得更多您想要的行為,減少您不想要的行為。

Rodrigues-Craig基於豐富的企業經驗和對人口統計學和社會學的深入了解,展示了如何創建更好的理論和指標,以加速獲取洞察力、改變行為並獲得商業價值的過程。您將學習以下內容:

- 為理解網絡產品中的個體和社會行為開發複雜且可測試的理論
- 以社會科學家的思維方式,將個體行為置於當今社會環境中
- 為任何網絡產品或系統建立更有效的指標和關鍵績效指標(KPI)
- 進行更具信息性和可操作性的A/B測試
- 探索因果效應,反映對相關性和因果關係之間差異的更深入理解
- 在複雜的網絡產品中改變用戶行為
- 理解相關的人類行為如何發展,以及改變它們的先決條件
- 選擇適合常見任務(如多狀態和提升建模)的統計技術
- 使用高級統計技術對多維系統進行建模
- 在R中完成所有這些(附有樣本代碼,可在單獨的代碼手冊中獲得)