Diaz-Bérrio Data Analytics for Marketing

A practical guide to analyzing marketing data using Python
1. Auflage 2024
ISBN: 978-1-80181-383-9
Verlag: De Gruyter
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 452 Seiten

Most marketing professionals are familiar with various sources of customer data that promise insights for success. There are extensive sources of data, from customer surveys to digital marketing data. Moreover, there is an increasing variety of tools and techniques to shape data, from small to big data. However, having the right knowledge and understanding the context of how to use data and tools is crucial.
In this book, you'll learn how to give context to your data and turn it into useful information. You'll understand how and where to use a tool or dataset for a specific question, exploring the 'what and why questions' to provide real value to your stakeholders. Using Python, this book will delve into the basics of analytics and causal inference. Then, you'll focus on visualization and presentation, followed by understanding guidelines on how to present and condense large amounts of information into KPIs. After learning how to plan ahead and forecast, you'll delve into customer analytics and insights. Finally, you'll measure the effectiveness of your marketing efforts and derive insights for data-driven decision-making.
By the end of this book, you'll understand the tools you need to use on specific datasets to provide context and shape your data, as well as to gain information to boost your marketing efforts.

Autoren/Hrsg.

Diaz-Bérrio, Guilherme

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse

Inhaltsverzeichnis

Table of Contents - What is Marketing Analytics?

- Extracting and Exploring Data with Singer and pandas

- Design Principles and Presenting Results with Streamlit
- Econometrics and Causal Inference with Statsmodels and PyMC
- Forecasting with Prophet, ARIMA, and Other Models Using StatsForecast
- Anomaly Detection with StatsForecast and PyMC
- Customer Insights – Segmentation and RFM
- Customer Lifetime Value with PyMC Marketing
- Customer Survey Analysis
- Conjoint Analysis with pandas and Statsmodels

- Multi-Touch Digital Attribution
- Media Mix Modeling with PyMC Marketing
- Running Experiments with PyMC

Über Autor(innen)

Diaz-Bérrio Guilherme :

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.