The adoption of data science and machine learning for marketing has been on the rise, from small to large organizations. With data science, you can better understand the drivers behind the successes and failures of previous marketing strategies and you can better understand customer behavior and interaction with your products. With data science, you can also predict customer behavior and create better targeted and personalized marketing strategies for better cost per acquisition, higher conversion rates, and higher net sales. With this book, you will be able to apply various data science techniques to create data-driven marketing strategies.
This book serves as a practical guide to performing simple-to-advanced tasks in marketing. You will use data science to understand what drives sales and customer engagement. You will use machine learning to forecast which customer is likely to engage with products more and has the highest expected lifetime value. You will also use machine learning to understand what data tells you about different customer segments and recommend the right products for individual customers that they are most likely to purchase. By the end of this book, you will be well-versed with various data science and machine learning techniques and how they can be utilized for different marketing goals.
Personally, I would have benefited from books such as this. When I was embarking on my career in data science and marketing, there were abundant resources on theories and details of different data science and machine learning techniques, but not so much on how to use these technologies and techniques for marketing specifically. Learning about the theories was vastly different from actually utilizing and applying them to real-world business use cases in marketing. In this book, I hope to share my experience and the knowledge acquired through significant instances of trial and error in applying data science and machine learning to different marketing goals. By the end of this book, you will have a good understanding of what types of technologies and techniques are used for different marketing use cases, where to find additional resources, and what to study next after this book.
In this book, Python and R will be used for data science and machine learning exercises. As you may already be aware, Python and R are two of the most frequently used programming languages for data scientists, data analysts, and machine learning engineers on account of their ease of use, the abundant resources that are available in relation to data science and machine learning, and the broad community of users. In each chapter, we will guide you through the different packages and libraries used and how to install them, so you do not need to worry about what to install on your computer before you start this book.
