Customer segmentation using various machine learning techniques
by Samyuktha Palangad Othayoth; Raja Muthalagu
International Journal of Business Intelligence and Data Mining (IJBIDM), Vol. 20, No. 4, 2022

Abstract: In the field of retail industry and marketing, customer segmentation is one of the most important tasks. A proper customer segmentation can help the managers to enhance the quality of products and provide better services for the targeting segments. Various machine learning algorithms-based customer segmentation techniques are used to get an insight about the customer's behaviour and the potential customers that could be targeted to maximise profit. Based on the previous studies, this paper proposes improved machine learning models for customer segmentation in e-commerce. The agglomerative clustering algorithms have been implemented to segment the customers with the new metric for customer behaviour. Also, we have proposed a systematic approach for combining agglomerative clustering algorithm and filtering-based recommender system to improve customer experience and customer retention. In the experiment, the results were compared with K-means clustering model, and it was found that BLS greatly reduced training time while guaranteeing accuracy.

Online publication date: Fri, 03-Jun-2022

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