Here is a list of books I can recommend. They require different technical skills though.

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MARKETING ANALYTICS, Strategic Models and Metrics

by Stephan Sorger

Nice intro book that requires basically zero math or technical skills. Is used as a text book at University of Berkeley.

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MARKETING ANALYTICS

by Mike Grigsby

Requires a lot of math and data science know-how BUT it talks about the most advanced methods. He uses the R language in the examples. The data sets can be found in Github.

He says it is a practical guide too and I would agree.

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Principles of Marketing Engineering and Analytics
by Garry Lilien, Arvind Rangaswamy, Arnaud de Bruyn

The book is somehow between the two mentioned above. Although it says "Engineering" it can be read without such a degree. The models are also used in Enginius a commercial software that they market to universities.

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Data Science for Marketing Analytics

by Mirza Rahim Baig et al.

This book in the Python series of Packt gives a nice intro how to use Python for data science projects in Marketing Analytics.

It is indeed an intro book that will provide you with the Python basics. There are 2-3 other books on the same topic in the Packt series that I have not yet studied.

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Marketing Data Science

by Thomas W. Miller

Covers marketing topics with R and Python solutions. The datasets can be found online. The problems are described nicely. The solutions require R and/or Python know-how and also math and statistics is required often. Author is professor at Northwestern University.

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Marketing Analytics - Based on First Principles

by Robert Palmatier, J. Andrew Petersen, Frank Germann

One of my favourite books that uses both R and also Tableau. It categories the marketing analytics topics nicely into 4 categories. There is a video for each chapter where Frank Germann goes through the R code and also step by step through the use of Tableau.

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