Journal Section

Journal of Business Venturing, AI and Data Analytics

Open Access
Cite Score: 0.5 Impact Factor: 0.6
Predictive Analytics in Customer Relationship Management in the USA
Author's Details

Name: Rabeya Khatoon

Email: popyrabeya858@gmail.com

Department: Department of Business Administration

Affiliation Number: 1

Address: Los Angeles, CA 90010, 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

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This article is Open Access CC BY-NC
Article Information
Article Type
Research Paper
Submitted
02 July, 2024
Revised
27 July, 2024
Accepted
11 August, 2024
Online First
20 August, 2024
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