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Preface

Part I Introduction to Marketing Analytics

Chapter 1 The Role of Data Science in Marketing
Chapter 2 Data Preprocessing and Exploratory Data Analysis
Chapter 3 Feature Engineering for Marketing Data

Part II Predictive Analytics for Marketing

Chapter 4 Regression Analysis for Marketing
Chapter 5 Classification Models for Customer Segmentation
Chapter 6 Time Series Forecasting
Chapter 7 Price Elasticity and Optimizaton

Part III Advanced Marketing Analytics

Chapter 8 Marketing Channel Attribution Models
Chapter 9 Marketing Media Mix Models
Chapter 10 Next Best Action (NBA) Models
Chapter 11 Natural Language Processing for Sentiment Analysis
Chapter 12 Recommender Systems for Personalized Marketing
Chapter 13 A/B Testing and Experimentation
Chapter 14 Customer Lifetime Value Prediction

Part IV Case Studies and Applications

Chapter 15 Churn Prediction and Retention Strategies
Chapter 16 Optimizing Marketing Campaigns with Machine Learning
Chapter 17 Social Media Analytics for Marketing Insights

Part V Conclusion

Chapter 18 Future Trends in Marketing Analytics
Chapter 19 Best Practices and Pitfalls to Avoid

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Chapter 15 Churn Prediction and Retention Strategies

Chapter 15 Churn Prediction and Retention Strategies#

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Chapter 14 Customer Lifetime Value Prediction

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Chapter 16 Optimizing Marketing Campaigns with Machine Learning

By Phillip Peng

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