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Data Science for Marketing Analytics

You're reading from   Data Science for Marketing Analytics A practical guide to forming a killer marketing strategy through data analysis with Python

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Product type Paperback
Published in Sep 2021
Publisher Packt
ISBN-13 9781800560475
Length 636 pages
Edition 2nd Edition
Languages
Tools
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Authors (3):
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Vishwesh Ravi Shrimali Vishwesh Ravi Shrimali
Author Profile Icon Vishwesh Ravi Shrimali
Vishwesh Ravi Shrimali
Mirza Rahim Baig Mirza Rahim Baig
Author Profile Icon Mirza Rahim Baig
Mirza Rahim Baig
Gururajan Govindan Gururajan Govindan
Author Profile Icon Gururajan Govindan
Gururajan Govindan
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Toc

Table of Contents (11) Chapters Close

Preface
1. Data Preparation and Cleaning 2. Data Exploration and Visualization FREE CHAPTER 3. Unsupervised Learning and Customer Segmentation 4. Evaluating and Choosing the Best Segmentation Approach 5. Predicting Customer Revenue Using Linear Regression 6. More Tools and Techniques for Evaluating Regression Models 7. Supervised Learning: Predicting Customer Churn 8. Fine-Tuning Classification Algorithms 9. Multiclass Classification Algorithms Appendix

Introduction

Put yourself in the shoes of the marketing head of an e-commerce company with a base of 1 million transacting customers. You want to make the marketing campaigns more effective, reaching the right customer with the right messaging. You know that by understanding the customer and their needs better, marketing campaigns could provide a significant boost to the business. As you begin solving this problem, you think about the customer experience. An average customer receives several communications from your platform about the latest offers and programs. These are relayed via email, push notifications, and social media campaigns. This may not be a great experience for them, especially if these communications are generic/mass campaigns. If the company understood the customers' needs better and sent them the relevant content, they would shop much more frequently.

Several examples like this show that a deep understanding of customers and their needs is beneficial not only...

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