Marketing Analytics and Data Science

Xiaojing Dong ()
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Xiaojing Dong: Santa Clara University, Leavey School of Business

in Springer Books from Springer

Date: 2026
ISBN: 978-3-032-11130-2
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Chapters in this book:

Ch Chapter 1 Getting Ready for Data Analytics with R and Python

Xiaojing Dong

Ch Chapter 10 Bayesian Updating and Experimental Design

Xiaojing Dong

Ch Chapter 11 Causal Analysis with Randomized Field Experiment

Xiaojing Dong

Ch Chapter 12 Artificial Intelligence in Marketing Analytics

Xiaojing Dong

Ch Chapter 2 The Marketing Questions and Data Science Tools

Xiaojing Dong

Ch Chapter 3 Unlocking Marketing Insights with Free Data

Xiaojing Dong

Ch Chapter 4 Media Mix Modeling

Xiaojing Dong

Ch Chapter 5 Market Segmentation and Clustering Analysis

Xiaojing Dong

Ch Chapter 6 Targeting and Propensity Score Model (Part I)

Xiaojing Dong

Ch Chapter 7 Targeting and Propensity Score Model (Part II)

Xiaojing Dong

Ch Chapter 8 Forecasting and Bass Model

Xiaojing Dong

Ch Chapter 9 Bayes’ Theorem and Marketing Attribution

Xiaojing Dong

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DOI: 10.1007/978-3-032-11130-2

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