IMPROVING MARKETING STRATEGIES WITH LRFS BASED CUSTOMER SEGMENTATION FOR ONLINE PLATFORMS

Authors

  • PENDYALA ANUSHA Author
  • Mrs.Y SUSHEELA Author

Keywords:

Behavior-Based Segmentation, Online Shoppers, LRFS Model, Lifestyle, Recency, Frequency, Spending, E-commerce

Abstract

In order to enhance online marketing strategies, this study uses client segmentation based on LRFS. The LRFS model examines lifetime value and consumer behavior using the Length, Recency, Frequency, and Spending variables. Transactional data is used in the study to classify clients for targeted promotions, personalized marketing, and successful customer retention. The findings demonstrate that LRFS-based segmentation improves profitability, resource allocation, marketing effectiveness, and customer engagement. According to the study, data-driven segmentation is essential for competitive advantage and the expansion of the digital market.

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Author Biographies

  • PENDYALA ANUSHA

    Dept of CSE,

    Vaageswari College of Engineering(Autonomous), Karimnagar, TG.

  • Mrs.Y SUSHEELA

    Associate Professor , Dept of CSE,

    Vaageswari College of Engineering(Autonomous), Karimnagar, TG.

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Published

2026-06-04

Issue

Vol. 2 No. 2 (2026): Volume 2, Issue 2, April-June, 2026

Section

Articles

License

Copyright (c) 2026 Journal of Science and Technology Excellence

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