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Hands-On Data Science for Marketing

You're reading from   Hands-On Data Science for Marketing Improve your marketing strategies with machine learning using Python and R

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Product type Paperback
Published in Mar 2019
Publisher Packt
ISBN-13 9781789346343
Length 464 pages
Edition 1st Edition
Languages
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Author (1):
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Yoon Hyup Hwang Yoon Hyup Hwang
Author Profile Icon Yoon Hyup Hwang
Yoon Hyup Hwang
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Table of Contents (20) Chapters Close

Preface 1. Section 1: Introduction and Environment Setup FREE CHAPTER
2. Data Science and Marketing 3. Section 2: Descriptive Versus Explanatory Analysis
4. Key Performance Indicators and Visualizations 5. Drivers behind Marketing Engagement 6. From Engagement to Conversion 7. Section 3: Product Visibility and Marketing
8. Product Analytics 9. Recommending the Right Products 10. Section 4: Personalized Marketing
11. Exploratory Analysis for Customer Behavior 12. Predicting the Likelihood of Marketing Engagement 13. Customer Lifetime Value 14. Data-Driven Customer Segmentation 15. Retaining Customers 16. Section 5: Better Decision Making
17. A/B Testing for Better Marketing Strategy 18. What's Next? 19. Other Books You May Enjoy

Applications of data science in marketing

We have discussed the trends in marketing and how the trend has been toward more data-driven and quantitative marketing, often using data science and machine learning. There are various ways to apply data science and machine learning in the marketing industry and it will be beneficial for us to discuss the typical tasks and usage of data science and machine learning.

In this section, we will cover the basics of machine learning, the different types of learning algorithms, and, typical data science workflow and process.

Descriptive versus explanatory versus predictive analyses

As we work through the exercises and projects in the upcoming chapters, there are mainly three different...

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