Fitri Marisa, Fitri Marisa and Fachrudin, Fachrudin and Syed Ahmad, Sharifah Sakinah and Mohd Yusoh, Zeratul Izzah and Aziz, Tubagus Mohammad Akhriza (2019) Segmentation Model Of Customer Lifetime Value In Small And Medium Enterprise (SMEs) Using K-Means Clustering And LRFM Model. The International Journal of Integrated Engineering, 11 (3). pp. 169-180. ISSN 2600-7916
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2019 SEGMENTATION MODEL OF CUSTOMER LIFETIME VALUE IN SMALL AND MEDIUM ENTERPRISE (SMES) USING K-MEANS CLUSTERING AND LRFM MODEL.PDF Download (553kB) |
Abstract
The CLV mode l is a measure of customer profit fo r a co mpany that can be usedto evaluate the future value of a customer.The CLV model is a measure of customer profit fo r a co mpany that can be used to evaluate the future value of a customer. This study aims to obtain Customer Lifetime Va lue (CLV) in each customer segment. Groupinguses the K-Means Clustering method based on the LRFM model (Length, Recency, Frequency, Monetary). The cluster formation process uses the Elbow Method and SSE with the best number of c lusters = 2 clusters. CLV values are generated fro m the mu ltip lication of the results of norma lizat ion of LRFM and the LFRM weight values are then summed, and carried out on each cluster that has been formed. The highest ranking among the 2 clusters is at the second cluster with the CLV va lue being far the h ighest from the other c luster average of 0.362. Based on LRFM matrix, this cluster has a high loyalty value with the symbol LRFM L ↑ R ↑F ↑ M ↑ which is a loyal customer (the best segment that has high customer loyalty value).Based on the LRFM symbol, the company can ma ke a strategy to retain customers and acquire customers to become loyal customers with high profitability.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | CLV, LRFM, K-Means, Clustering, SMEs |
| Divisions: | Faculty of Information and Communication Technology |
| Depositing User: | Sabariah Ismail |
| Date Deposited: | 08 Dec 2020 15:04 |
| Last Modified: | 08 Dec 2020 15:04 |
| URI: | http://eprints.utem.edu.my/id/eprint/24633 |
| Statistic Details: | View Download Statistic |
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