Customer Segmentation Using Hybrid Clustering...

Customer Segmentation Using Hybrid Clustering RFM Approach

Author Name : Paladugu Krishna Chaitanya, Parth Kansara

ABSTRACT

Several consumers buy through e-commerce and many businesses advertise and distribute their goods via e-commerce. This means that the customer's side is overwhelmed with knowledge. Knowledge is overwhelmed once consumers receive too much product information, so they get frustrated. The solution to the overload dilemma would be the personalization. In advertisements, personalization can be used to improve revenue for prospective buyers. The prospective buyer is extracted from the segmentation of the customer or industry. We focus our analysis in this paper on a challenge by utilizing a unique statistical approach. The online sales data is used to perform custom segmentation and value analysis on RFM (Recency, Frequency and Monetary) models and the K-means algorithm. Based on their buying actions, consumers are grouped into categories. On this basis, multiple techniques are formulated to ensure a high degree of customer satisfaction.

Keywords: Customer segmentation, clustering, data mining, RFM model, market analysis