Predictive Analytics in Customer Relationship Management in the USA

Abstract

Several researchers have focused on the conceptual and empirical aspects of customer relationship management (CRM). A few studies on a particular sector provide an overview of CRM research output. However, a dearth of literature summarizes CRM research output compared to data mining-based CRM. This paper uses historical consumer purchase data to create a trend for introducing desktops and laptops in a range of configurations for clients of different ages and genders. Additionally, the efficacy of loyalty programs is investigated, showing how Big Data can customize rewards to increase client loyalty. The conclusion emphasizes the need for greater study into cutting-edge machine learning methods, moral issues, and creating more complex real-time analytics tools. This paper aims to develop a theory and methodology that enables any computer vendor to identify a new market and introduce a new line of computers based on "survival of the fittest" and customer past transactions.