Introduction

How can Amazon recommend the right product whilst the customers are buying? How can an organization know which customers are interested in leaving their services? Why do we receive fair deals when we are interested in buying a product? The key behind these questions is the effective deployment of Customer Analytics by these organizations, that means the efficient and effective use of customer data.

With the advent of social media and the democratization of the Internet, it has emerged a new type of customer: more informed, instrumented and connected. A customer that interacts with a company using all the available channels (offline, online, mobile and social). A new customer that is eager to feel personalized experiences.

As a result, intuition is no longer enough to understand the customer, data is needed. Organizations are being forced to focus on the client and transform their marketing, communication and sales experiences that must be grounded in the needs and preferences of customers.

This book aims to train professionals in the context of the analysis of customer data, also known as Customer Analytics, with the goal to start developing efficient strategies within its own organization.

The efficiency is achieved through the combination of multiple technologies (from Business Intelligence to Big Data) and the use of algorithms to understand and predict customers’ behaviour and their future interactions.

This book complements professor Curto's Customer Analytics course at IE Business School, UOC and KSchool. The course, that consists of several sessions, is designed to introduce Customer Analytics from the perspective of the data scientist. That means, it is a practical and quantitative course.

The reader will learn the concept of Customer Analytics and some of the more relevant techniques used in the real world by companies around the world. Basic knowledge in statistics, mathematics, programming, R and RStudio is expected to be able to follow this book.