Book Image

Hands-On Data Science for Marketing

By : Yoon Hyup Hwang
Book Image

Hands-On Data Science for Marketing

By: Yoon Hyup Hwang

Overview of this book

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.
Table of Contents (20 chapters)
Free Chapter
1
Section 1: Introduction and Environment Setup
3
Section 2: Descriptive Versus Explanatory Analysis
7
Section 3: Product Visibility and Marketing
10
Section 4: Personalized Marketing
16
Section 5: Better Decision Making

Customer analytics – understanding customer behavior

Customer analytics is a process of understanding and gaining insights into customer behavior through analyzing customer behavior data. It ranges from simple data analysis and visualization to more advanced customer segmentation and predictive analytics. The information and insights gained through customer analytics can then be utilized in forming marketing strategies, optimizing sales channels, and making other key business decisions.

The importance of customer analytics is rising. Because access to customer data became easier for many businesses and also because customers now have easier access to data and information on similar products and contents provided by other competitors, it is critical to many businesses to be able to understand and predict what their customers are likely to purchase or view. The deeper the...