Customer segment model with the purchase recency, frequency and monetary amount
This paper utilizes customer transaction data to segment customers based on their purchase recency, frequency, and monetary amount. By employing an empirical approach, a stochastic model is proposed to predict customer segmentation into categories such as new, active, potential, and lost. The model...
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| Format: | Article |
| Language: | English |
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Srpsko udruženje za marketing
2025-01-01
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| Series: | Marketing (Beograd. 1991) |
| Subjects: | |
| Online Access: | https://scindeks-clanci.ceon.rs/data/pdf/0354-3471/2025/0354-34712502113H.pdf |
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| _version_ | 1849696494486028288 |
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| author | Huang Hui-Hsin |
| author_facet | Huang Hui-Hsin |
| author_sort | Huang Hui-Hsin |
| collection | DOAJ |
| description | This paper utilizes customer transaction data to segment customers based on their purchase recency, frequency, and monetary amount. By employing an empirical approach, a stochastic model is proposed to predict customer segmentation into categories such as new, active, potential, and lost. The model also constructs indices for customer equity and loyalty. This approach allows companies to practically analyze and categorize their customers, calculating the probability of segment characteristics. The study highlights the importance of customer segmentation in strategic planning, emphasizing the role of RFM (recency, frequency, monetary amount) analysis in identifying high-value customers and optimizing marketing strategies. The proposed model integrates customer equity and loyalty metrics, providing a comprehensive framework for businesses to enhance customer relationship management and targeted marketing efforts. The empirical data from a credit card customer database in Taiwan demonstrates the model's effectiveness in segmenting customers and predicting their behavior, offering valuable insights for businesses to allocate resources strategically and maximize revenue potential. This research contributes to the field by presenting a robust method for dynamic customer segmentation, applicable across various industries. |
| format | Article |
| id | doaj-art-166a8862123b451c8f5952ceb5cc6212 |
| institution | DOAJ |
| issn | 0354-3471 2334-8364 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Srpsko udruženje za marketing |
| record_format | Article |
| series | Marketing (Beograd. 1991) |
| spelling | doaj-art-166a8862123b451c8f5952ceb5cc62122025-08-20T03:19:27ZengSrpsko udruženje za marketingMarketing (Beograd. 1991)0354-34712334-83642025-01-0156211312010.5937/mkng2502113H0354-34712502113HCustomer segment model with the purchase recency, frequency and monetary amountHuang Hui-Hsin0Fu Jen Catholic University, Department of Advertising & Public Relations, TaiwanThis paper utilizes customer transaction data to segment customers based on their purchase recency, frequency, and monetary amount. By employing an empirical approach, a stochastic model is proposed to predict customer segmentation into categories such as new, active, potential, and lost. The model also constructs indices for customer equity and loyalty. This approach allows companies to practically analyze and categorize their customers, calculating the probability of segment characteristics. The study highlights the importance of customer segmentation in strategic planning, emphasizing the role of RFM (recency, frequency, monetary amount) analysis in identifying high-value customers and optimizing marketing strategies. The proposed model integrates customer equity and loyalty metrics, providing a comprehensive framework for businesses to enhance customer relationship management and targeted marketing efforts. The empirical data from a credit card customer database in Taiwan demonstrates the model's effectiveness in segmenting customers and predicting their behavior, offering valuable insights for businesses to allocate resources strategically and maximize revenue potential. This research contributes to the field by presenting a robust method for dynamic customer segmentation, applicable across various industries.https://scindeks-clanci.ceon.rs/data/pdf/0354-3471/2025/0354-34712502113H.pdfpurchase frequencyrecencymonetary amountrfmcustomer loyalty |
| spellingShingle | Huang Hui-Hsin Customer segment model with the purchase recency, frequency and monetary amount Marketing (Beograd. 1991) purchase frequency recency monetary amount rfm customer loyalty |
| title | Customer segment model with the purchase recency, frequency and monetary amount |
| title_full | Customer segment model with the purchase recency, frequency and monetary amount |
| title_fullStr | Customer segment model with the purchase recency, frequency and monetary amount |
| title_full_unstemmed | Customer segment model with the purchase recency, frequency and monetary amount |
| title_short | Customer segment model with the purchase recency, frequency and monetary amount |
| title_sort | customer segment model with the purchase recency frequency and monetary amount |
| topic | purchase frequency recency monetary amount rfm customer loyalty |
| url | https://scindeks-clanci.ceon.rs/data/pdf/0354-3471/2025/0354-34712502113H.pdf |
| work_keys_str_mv | AT huanghuihsin customersegmentmodelwiththepurchaserecencyfrequencyandmonetaryamount |