Mirza Rahim Baig - Data Science for Marketing Analytics: A practical guide to forming a killer marketing strategy through data analysis with Python, 2nd Edition

A practical guide to forming a killer marketing strategy through data analysis with Python

Mirza Rahim Baig, Gururajan Govindan, and Vishwesh Ravi Shrimali

Copyright 2021 Packt Publishing

All rights reserved. No part of this course may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

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Authors: Mirza Rahim Baig, Gururajan Govindan, and Vishwesh Ravi Shrimali

Reviewers: Cara Davies and Subhranil Roy

Managing Editors: Prachi Jain and Abhishek Rane

Acquisitions Editors: Royluis Rodrigues, Kunal Sawant, and Sneha Shinde

Production Editor: Salma Patel

Editorial Board: Megan Carlisle, Mahesh Dhyani, Heather Gopsill, Manasa Kumar, Alex Mazonowicz, Monesh Mirpuri, Bridget Neale, Abhishek Rane, Brendan Rodrigues, Ankita Thakur, Nitesh Thakur, and Jonathan Wray

First published: March 2019

First edition authors: Tommy Blanchard, Debasish Behera, and Pranshu Bhatnagar

Second edition: September 2021

Production reference: 1060921

ISBN: 978-1-80056-047-5

Published by Packt Publishing Ltd.

Livery Place, 35 Livery Street

Birmingham B3 2PB, UK

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.

This second edition has been updated to include new case studies that bring a more application-oriented approach to your marketing analytics journey. The code has also been updated to support the latest versions of Python and the popular data science libraries that have been used in the book. The practical exercises and activities have been revamped to prepare you for the real-world problems that marketing analysts need to solve. This will show you how to create a measurable impact on businesses large and small.