Mastering Marketing Data Science

CHAPTER 5Predictive Analytics and Machine Learning

5.1 INTRODUCTION

5.1.1 Overview of Predictive Analytics

Predictive analytics is a branch of advanced analytics that uses data, statistical algorithms, and machine learning techniques to predict future outcomes. Its aim is to go beyond knowing what has happened to provide the best estimation of what will happen in the future. This is achieved by leveraging a variety of techniques, including data mining, statistics, modeling, machine learning, and artificial intelligence.

Predictive analytics is predicated on the capture of relationships between explanatory variables and the predicted variables from past occurrences and using this to predict future outcomes (Provost & Fawcett, 2013). It exploits patterns found in historical and transactional data to identify risks and opportunities, thus providing insights that guide decision-making across various sectors.

In marketing, predictive analytics is used to analyze current data and historical facts in order to better understand customers, products, and partners, and to identify potential risks and opportunities. It can be used to forecast customer behavior, detect, and prevent fraud, optimize marketing campaigns, improve operations, reduce risk, meet customer's needs more effectively, and increase profitability (Sharda et al., 2018).

The ability of predictive analytics to provide actionable insights provides a competitive advantage and helps organizations make informed, forward-looking ...