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Data Analytics for Marketing

You're reading from Data Analytics for Marketing A practical guide to analyzing marketing data using Python

Product type Paperback

Published in May 2024

Publisher Packt

ISBN-13 9781803241609

Length 452 pages

Edition 1st Edition

Languages

Python

Tools

Pandas

Concepts

Data Analysis

Author (1):

Guilherme Diaz-Bérrio

View More author details

Table of Contents (20) Chapters

Preface

1. Part 1: Fundamentals of Analytics

2. Chapter 1: What is Marketing Analytics? FREE CHAPTER

3. Chapter 2: Extracting and Exploring Data with Singer and pandas

4. Chapter 3: Design Principles and Presenting Results with Streamlit

5. Chapter 4: Econometrics and Causal Inference with Statsmodels and PyMC

6. Part 2: Planning Ahead

7. Chapter 5: Forecasting with Prophet, ARIMA, and Other Models Using StatsForecast

8. Chapter 6: Anomaly Detection with StatsForecast and PyMC

9. Part 3: Who and What to Target

10. Chapter 7: Customer Insights – Segmentation and RFM

11. Chapter 8: Customer Lifetime Value with PyMC Marketing

12. Chapter 9: Customer Survey Analysis

13. Chapter 10: Conjoint Analysis with pandas and Statsmodels

14. Part 4: Measuring Effectiveness

15. Chapter 11: Multi-Touch Digital Attribution

16. Chapter 12: Media Mix Modeling with PyMC Marketing

17. Chapter 13: Running Experiments with PyMC

18. Index

Why subscribe?

19. Other Books You May Enjoy

Technical requirements

The code files for this chapter are available on GitHub: https://github.com/PacktPublishing/Data-Analytics-for-Marketing/tree/main/Chapter12.

The code in this chapter was tested on PyMC-Marketing version 0.3.1. Version 0.4.0 introduced some breaking changes that were still being addressed by the library maintainers at the time of publishing.

The rest of the chapter is locked

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Authors (1)

Guilherme Diaz-Bérrio

Guilherme Diaz-Bérrio

Guilherme Diaz-Bérrio is the Head of Marketing Analytics at Kindred Group, one of the 10 largest gambling operators. He helps improve marketing efforts across various platforms. His career started in finance at a hedge fund and moved through the automotive industry at BMW Group and BMW Financial Services, before coming to Kindred Group. He graduated with a degree in economics from ISEG, University of Lisbon, and has additional training in data science and econometrics. He is also the co-founder of Pinemarsh, a data analytics and digital marketing consulting firm.

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