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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

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Product type Paperback
Published in May 2024
Publisher Packt
ISBN-13 9781803241609
Length 452 pages
Edition 1st Edition
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Author (1):
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Guilherme Diaz-Bérrio Guilherme Diaz-Bérrio
Author Profile Icon Guilherme Diaz-Bérrio
Guilherme Diaz-Bérrio
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Toc

Table of Contents (20) Chapters Close

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 19. Other Books You May Enjoy

Summary

In this chapter, we delved into what we mean by marketing analytics. We broke down the types of analytics—from descriptive to prescriptive— discussed the value they add to businesses, and learned what questions each of them answers.

We investigated the fundamental questions you are trying to answer—what happened, when did it happen, how did it happen, what will happen in the future, and how can I make something happen. We also covered how they relate to each sub-domain of analytics, and we can now distinguish clearly between descriptive, predictive, diagnostic, and prescriptive analytics.

First, analytics is a complex field that can be summarized as the intersection between statistics, computer science, and analysis. You need to understand that marketing analytics distills those tools and techniques to the efforts of marketing to better optimize spending and obtain a return on investment.

Analytics can be split into question categories that map...

You have been reading a chapter from
Data Analytics for Marketing
Published in: May 2024
Publisher: Packt
ISBN-13: 9781803241609
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