Predictive Analytics in Customer Relationship Management in the USA

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 realtime 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.

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Publication Details

Journal
Journal of Business Venturing AI and Data Analytics
Published
2024-08-20
DOI
https://doi.org/10.63471/bv24005
Primary Topic
Customer Service Quality and Loyalty
Type
article
Field-Weighted Citation Impact
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article

Predictive Analytics in Customer Relationship Management in the USA

Shahariar Chowdhury, Rabeya Khatoon
Journal of Business Venturing AI and Data Analytics
Customer Service Quality and Loyalty
article

Predictive Analytics in Customer Relationship Management in the USA

Shahariar Chowdhury, Rabeya Khatoon
article en

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 realtime 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.

Journal of Business Venturing AI and Data Analytics
University of Dhaka (BD), International American University (LC)
Openalex Percentile: Top 61%
Customer Service Quality and Loyalty
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