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Data Science for Marketing Analytics - Second Edition

You're reading from  Data Science for Marketing Analytics - Second Edition

Product type Book
Published in Sep 2021
Publisher Packt
ISBN-13 9781800560475
Pages 636 pages
Edition 2nd Edition
Languages
Authors (3):
Mirza Rahim Baig Mirza Rahim Baig
Profile icon Mirza Rahim Baig
Gururajan Govindan Gururajan Govindan
Profile icon Gururajan Govindan
Vishwesh Ravi Shrimali Vishwesh Ravi Shrimali
Profile icon Vishwesh Ravi Shrimali
View More author details

Table of Contents (11) Chapters

Preface
1. Data Preparation and Cleaning 2. Data Exploration and Visualization 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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