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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

Product type Paperback

Published in Sep 2021

Publisher Packt

ISBN-13 9781800560475

Length 636 pages

Edition 2nd Edition

Languages

Python

Tools

GDI

Concepts

Data Analysis

Authors (3):

Vishwesh Ravi Shrimali

Mirza Rahim Baig

Gururajan Govindan

View More author details

Table of Contents (11) Chapters

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

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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Authors (3)

Mirza Rahim Baig

Mirza Rahim Baig

Mirza Rahim Baig is a Data Science and Artificial Intelligence leader with over 13 years of experience across e-commerce, healthcare, and marketing. He currently holds the position of leading Product Analytics at Marketing Services for Zalando, Europe's largest online fashion platform. In addition, he serves as a Subject Matter Expert and faculty member for MS level programs at prominent Ed-Tech platforms and institutes in India. He is also the lead author of two books, 'Data Science for Marketing Analytics' and 'The Deep Learning Workshop,' both published by Packt. He is recognized as a thought leader in my field and frequently participates as a guest speaker at various forums.

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Vishwesh Ravi Shrimali

Vishwesh Ravi Shrimali

Vishwesh Ravi Shrimali graduated from BITS Pilani, where he studied mechanical engineering, in 2018. He also completed his Masters in Machine Learning and AI from LJMU in 2021. He has authored - Machine learning for OpenCV (2nd edition), Computer Vision Workshop and Data Science for Marketing Analytics (2nd edition) by Packt. When he is not writing blogs or working on projects, he likes to go on long walks or play his acoustic guitar.

See other products by Vishwesh Ravi Shrimali

Gururajan Govindan

Gururajan Govindan

Gururajan Govindan is a data scientist, intrapreneur, and trainer with more than seven years of experience working across domains such as finance and insurance. He is also an author of The Data Analysis Workshop, a book focusing on data analytics. He is well known for his expertise in data-driven decision-making and machine learning with Python.

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