To recognize customers, organizations use a scale to measure the importance of different customers. In the present study, the customer segmentation is done in the aesthetic and dermatology center in an Islamic country based on the extended LRFMP model. For attaining the purpose, this study used clustering by Two-Step SOM and data gathered from 220 patients of aesthetic and dermatology center in an Islamic country. Due to selecting the optimal number of clusters, is adopted the Davies-Bouldin index. In the first step, the number of clusters is calculated by Lehman's rule, and then by the SOM method, the analysis was repeated for three, four, and five clusters and through the Dunn index compared the results. Also, for more understanding, the type of patients has selected the label for the clusters by using Marcus's customer value matrix as the foundation. Considering the value of the Dunn index, the triple cluster is the favorite cluster. The status of LRFMP indices was shown in the triple cluster, and selected the labels for each cluster as "Loyal customers", "Potential loyal customers" and "Uncertain customers". Regarding the nature of the labels and the literature, this study recommended marketing strategies. The investigation of the kinds of the literature showed that segmentation in the aesthetic and dermatology center in an Islamic country was not performed with LRFMP indices by SOM in an aesthetic and dermatology center. |
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