Unveiling Customer Traits, RFM Segmentation, and CLTV Insight

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Authors: U. V. V. R. M. Krishna Sai
Cited by: 0

Abstract

Unlocking Customer Attributes: RFM Segmentation and CLTV Insights. The application aims to identify valuable patterns in behavior and preferences through this strategic combination of RFM (recency, frequency, monetary) segmentation and CLTV (lifetime value) analysis. This progressive approach gives complete insights into current patron purchase habits, transaction frequency, and the economic performance of the business. Through RFM segmentation, this system seeks to become aware of distinct consumer businesses, allowing corporations to design their marketing strategies more effectively. Additionally, the use of CLTV evaluation affords a comprehensive view of each consumer's long-term price, helping organizations prioritize and expand valuable relationships. Ultimately, this system promises to offer corporations actionable insights to be able to enhance their advertising efforts, improve consumer pride, and increase ordinary profitability.

Fields of Study & Subjects

Customer churn and segmentation Data Mining and Machine Learning Applications Customer Service Quality and Loyalty

Publication details

Journal / source
International Journal for Research in Applied Science and Engineering Technology
Volume
14
Issue
1
Pages
721–726
Publication date
14 January 2026