Predictive Analytics in Customer Relationship Management in the
USA
Affiliations
1
Department of Business Administration, International American University, Los Angeles, CA 90010, USA
2
Lecturer & Course Coordinator of Business Faculty, National University, Dhaka
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.
Keywords:
Predictive Analysis, Customer
relationship management,
Classification scheme, Data Privacy
and Security, Customer Engagement
and Retention