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A Case Study on Customer Segmentation by using Machine Learning Methods

33 citations0/0 files storedInternational Artificial Intelligence and Data Processing Symposium (IDAP)

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Customer churn and segmentation Data Mining and Machine Learning Applications Financial Distress and Bankruptcy Prediction

Abstract

Customer segmentation is important both in customer relationship management literature and softwares. The most common way to separate one customer from another is to promote a group of customers as premium and the remaining customers as standard. In this work, a company's manually segmented customer data is analyzed. The study aims to solve the company's data segmentation problem by using its real data regarding its customers' payments. Since, machine learning methods are useful to solve problems about data management, the solution is searched within machine learning methods. Different classification methods which are used to discriminate between premium and standard customers belonging to a company's database are compared. Two dimensional payment information of customers are used as input variables (features) and the methods are compared according to their separation performances.

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2016Customer portfolio management (CPM) for improved customer relationship management (CRM): Are your customers platinum, gold, silver, or bronze?

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2019Artificial Neural Networks in Customer Segmentation 2020Case studies on using natural language processing techniques in customer relationship management software 2023Customer Segmentation in Retailing using Machine Learning Techniques 2023Mall Customer Segmentation Engine Through Clustering Analysis 2020Machine Learning for Customer Segmentation Through Bibliometric Approach 2024Will they stay or will they go? application of machine learning classifiers of purchase and churn prediction to a digital journalistic platform 2024Importance-Induced Customer Segmentation Using Explainable Machine Learning

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