دانلود رایگان مقاله انگلیسی رتبه بندی RFM - یک رویکرد موثر برای تقسیم بندی مشتری - الزویر 2018

Abstract

The efficient segmentation of customers of an enterprise is categorized into groups of similar behavior based on the RFM (Recency, Frequency and Monetary) values of the customers. The transactional data of a company over is analyzed over a specific period. Segmentation gives a good understanding of the need of the customers and helps in identifying the potential customers of the company. Dividing the customers into segments also increases the revenue of the company. It is believed that retaining the customers is more important than finding new customers. For instance, the company can deploy marketing strategies that are specific to an individual segment to retain the customers. This study initially performs an RFM analysis on the transactional data and then extends to cluster the same using traditional K-means and Fuzzy C- Means algorithms. In this paper, a novel idea for choosing the initial centroids in K- Means is proposed. The results obtained from the methodologies are compared with one another by their iterations, cluster compactness and execution time.

CONCLUSION

Segmenting the customers will deepen the relationships with customers. Finding new customers for the enterprise is vital, meanwhile retaining the existing clients [8] is even more important. In this paper, segmentation is done using RFM analysis and then is extended to other algorithms like K –Means clustering, Fuzzy C – Means and a new algorithm RM K-Means by making a minor modification in the existing K – Means clustering. The working of these approaches is analyzed. The time taken by each algorithm to execute is analyzed, and it is observed that the proposed K –Means approach consumes lesser time and also reduces the number of iterations. The proposed algorithm is more effective because the centroids are more meaningful and are calculated at the beginning based on the effective medians of data distribution. Since segmentation is done based on the values of recency, frequency, and monetary values, the company can customize their marketing strategies to the customers based on their buying behavior. Future work includes studying the performance of the customers in each segment such as the products which are bought frequently by the members of each segment. This would help better in providing better promotional offers to specific products.