Classification and identification of loyal customers Using machine learning

B. Siva Rama Krishna., P. Sai Krishna, P. V. K. Priya, M. Gopi Sainath, G. Sai Kumar

The issue looked by the organization is the way to use CRMand to finalize profitable clients so as they play out correct promoting procedure, therefore they would bring the best strategies to increase the marketing. The procedure examine means to carry out clustering based on RFM (Recency, Frequency and Monetary) model in-order to establish the customers and classify customers with the help of supervised classification technique. This strategy utilized now for information gathering that contains customer transactions. With the help of RFM, K-means algorithm using selection techniques like Silhouette Coefficient, Gap Statistic and Elbow Method. Based on results, the accuracy of which selection technique is better that will be going to finalize the best value of k to assign customers into k clusters. After clustering, the classification of customers done with the help of classification technique Decision Tree. Based on evaluations are verified, to predict the loyalty of the customer and classify the customers into various categories such as Loyal Customer, Partial Loyal Customer, Irregular Customer and One Time Buyer.

Volume 12 | Issue 2

Pages: 859-866

DOI: 10.5373/JARDCS/V12I2/S20201106