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Hands-On Data Science for Marketing

You're reading from   Hands-On Data Science for Marketing Improve your marketing strategies with machine learning using Python and R

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Product type Paperback
Published in Mar 2019
Publisher Packt
ISBN-13 9781789346343
Length 464 pages
Edition 1st Edition
Languages
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Author (1):
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Yoon Hyup Hwang Yoon Hyup Hwang
Author Profile Icon Yoon Hyup Hwang
Yoon Hyup Hwang
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Table of Contents (20) Chapters Close

Preface 1. Section 1: Introduction and Environment Setup FREE CHAPTER
2. Data Science and Marketing 3. Section 2: Descriptive Versus Explanatory Analysis
4. Key Performance Indicators and Visualizations 5. Drivers behind Marketing Engagement 6. From Engagement to Conversion 7. Section 3: Product Visibility and Marketing
8. Product Analytics 9. Recommending the Right Products 10. Section 4: Personalized Marketing
11. Exploratory Analysis for Customer Behavior 12. Predicting the Likelihood of Marketing Engagement 13. Customer Lifetime Value 14. Data-Driven Customer Segmentation 15. Retaining Customers 16. Section 5: Better Decision Making
17. A/B Testing for Better Marketing Strategy 18. What's Next? 19. Other Books You May Enjoy

Retaining Customers

As customers have more options for similar content to consume or similar products and services to shop for, it has become more difficult for many businesses to retain their customers and not lose them to other competitors. As the cost of acquiring new customers is typically higher than that of retaining and keeping existing customers, customer churn is becoming more and more of a concern than ever before. In order to retain existing customers and not lose them to competitors, businesses should not only try to understand their customers and their customers' needs and interests, but they should also be able to identify which customers are highly likely to churn and how to retain these customers at churn risk.

In this chapter, we are going to dive deeper into customer churn and how it hurts businesses, as well as how to retain existing customers. We will...

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