Customer segmentation approach for efficient targeting in retail
Authors
Dunaboina, Bhanuprakash
Issue Date
2024
Degree
MSc in Business Analytics
Publisher
Dublin Business School
Rights holder
Rights
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Abstract
Customer segmentation is becoming popular nowadays, with companies increasing their product base. It is very tough to reach out to each customer in the company portfolio; hence, one can introduce segmentation to target the customers in the best possible way. This will help in reaching out to the customers in the best possible manner and the targeting can be done very quickly. The study performs stats-based and ML-based analyses on the dataset to provide a profile report to segment the customers. The study has used the RFM model and K-means clustering using a standard Data Mining Approach to get the analysis done on the retail dataset. Concluding that based on Purchase behavior, 3-4 cluster solutions are made, and for the K-means model, the following can be done only with 2 cluster solutions. Also, at the end, the profile report is generated to validate the clusters as per business.