Hands-On Data Science for Marketing: Improve your marketing strategies with machine learning using Python and R
by: Yoon Hyup Hwang
Print Length 页数: 464 pages
Publisher finelybook 出版社: Packt Publishing (March 29,2019)
Language 语言: English
ISBN-10: 1789346347
ISBN-13: 9781789346343
Book Description
Optimize your marketing strategies through analytics and machine learning
Regardless of company size,the adoption of data science and machine learning for marketing has been rising in the industry. With this book,you will learn to implement data science techniques to understand the drivers behind the successes and failures of marketing campaigns. This book is a comprehensive guide to help you understand and predict customer behaviors and create more effectively targeted and personalized marketing strategies.
This is a practical guide to performing simple-to-advanced tasks,to extract hidden insights from the data and use them to make smart business decisions. You will understand what drives sales and increases customer engagements for your products. You will learn to implement machine learning to forecast which customers are more likely to engage with the products and have high lifetime value. This book will also show you how to use machine learning techniques to understand different customer segments and recommend the right products for each customer. Apart from learning to gain insights into consumer behavior using exploratory analysis,you will also learn the concept of A/B testing and implement it using Python and R.
By the end of this book,you will be experienced enough with various data science and machine learning techniques to run and manage successful marketing campaigns for your business.
What you will learn
Learn how to compute and visualize marketing KPIs in Python and R
Master what drives successful marketing campaigns with data science
Use machine learning to predict customer engagement and lifetime value
Make product recommendations that customers are most likely to buy
Learn how to use A/B testing for better marketing decision making
Implement machine learning to understand different customer segments
Contents
Preface
Section 1: Introduction and Environment Setup
Chapter 1: Data Science and Marketing
Section 2: Descriptive Versus Explanatory Analysis
Chapter 2: Key Performance Indicators and Visualizations
Chapter 3: Drivers behind Marketing Engagement
Chapter 4: From Engagement to Conversion
Section 3: Product Visibility and Marketing
Chapter 5: Product Analytics
Chapter 6: Recommending the Right Products
Section 4: Personalized Marketing
Chapter 7: Exploratory Analysis for Customer Behavior
Chapter 8: Predicting the Likelihood of Marketing Engagement
Chapter 9: Customer Lifetime Value
Chapter 10: Data-Driven Customer Segmentation
Chapter 11: Retaining Customers
Section 5: Better Decision Making
Chapter 12: A/B Testing for Better Marketing Strategy
Chapter 13: What’s Next?
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Index
