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Data Science for Marketing Analytics

Data Science for Marketing Analytics - Second Edition

By : Mirza Rahim Baig , Gururajan Govindan , Vishwesh Ravi Shrimali
4.3 (203)
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Data Science for Marketing Analytics

Data Science for Marketing Analytics

4.3 (203)
By: Mirza Rahim Baig , Gururajan Govindan , Vishwesh Ravi Shrimali

Overview of this book

Unleash the power of data to reach your marketing goals with this practical guide to data science for business. This book will help you get started on your journey to becoming a master of marketing analytics with Python. You'll work with relevant datasets and build your practical skills by tackling engaging exercises and activities that simulate real-world market analysis projects. You'll learn to think like a data scientist, build your problem-solving skills, and discover how to look at data in new ways to deliver business insights and make intelligent data-driven decisions. As well as learning how to clean, explore, and visualize data, you'll implement machine learning algorithms and build models to make predictions. As you work through the book, you'll use Python tools to analyze sales, visualize advertising data, predict revenue, address customer churn, and implement customer segmentation to understand behavior. By the end of this book, you'll have the knowledge, skills, and confidence to implement data science and machine learning techniques to better understand your marketing data and improve your decision-making.
Table of Contents (11 chapters)
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Preface

Introduction

Azra, a large, high-end, fast-fashion retailer that has operations all over the world, has approved its marketing budget for the latest campaign in a particular country. The marketing team is now looking to allocate the budget to each marketing channel, but they have many questions:

  • How much should they spend on email? Read rates are low, but the quality of conversions is high.
  • How about social media? It seems to be an effective channel in general.
  • Should they do any offline promotions? If so, to what extent?
  • How about paid search as a channel?

The company understands that each channel provides a different return on investment (ROI) – that is, some channels are more effective than others. However, all channels should be considered, nonetheless. Naturally, different distributions of allocation to these channels would provide different results. Incredibly low spending on a channel with great ROI is missed potential and high spending on an extremely...

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