Data Analytics for Marketing : A practical guide to analyzing marketing data using Python

Conduct data-driven marketing research and analysis with hands-on examples using Python by leveraging open-source tools and libraries Key FeaturesAnalyze marketing data using proper statistical techniquesUse data modeling and analytics to understand customer preferences and enhance strategies withou...

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Bibliographic Details
Main Author: Diaz-Bérrio, Guilherme
Format: Livre numérique
Language:Anglais
Published: Birmingham : Packt Publishing 2024.
Paris : Cyberlibris
Online Access:Accès Université d'Orléans et IFPM
Note: Couverture. https://static2.cyberlibris.com/books_upload/136pix/9781801813839.jpg
Cyberlibris (ScholarVox) corpus Informatique
Autres localisations: Voir dans le Sudoc
Edition sous un autre format:• Data Analytics for Marketing, A practical guide to analyzing marketing data using Python, Guilherme Diaz-Bérrio, Birmingham, Packt Publishing, 2024, 1 vol. (452 p.), 978-18-0324-160-9
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245 1 0 |a Data Analytics for Marketing :  |b A practical guide to analyzing marketing data using Python   |c Guilherme Diaz-Bérrio. 
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520 |a Conduct data-driven marketing research and analysis with hands-on examples using Python by leveraging open-source tools and libraries Key FeaturesAnalyze marketing data using proper statistical techniquesUse data modeling and analytics to understand customer preferences and enhance strategies without complex mathImplement Python libraries like DoWhy, Pandas, and Prophet in a business setting with examples and use casesPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionMost 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 
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