Customer Segmentation Using Machine Learning

Nikhil Subhash Patankar · Soham Dixit · Akshay Bhamare · Ashutosh Darpel · Ritik Raina

45 citations0/0 files storedAdvances in parallel computing

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Customer churn and segmentation Advanced Clustering Algorithms Research Data Mining and Machine Learning Applications

Abstract

Nowadays Customer segmentation became very popular method for dividing company’s customers for retaining customers and making profit out of them, in the following study customers of different of organizations are classified on the basis of their behavioral characteristics such as spending and income, by taking behavioral aspects into consideration makes these methods an efficient one as compares to others. For this classification a machine algorithm named as k-means clustering algorithm is used and based on the behavioral characteristic’s customers are classified. Formed clusters help the company to target individual customer and advertise the content to them through marketing campaign and social media sites which they are really interested in.

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References

2016Customer portfolio management (CPM) for improved customer relationship management (CRM): Are your customers platinum, gold, silver, or bronze?2015Application of K-Means Algorithm for Efficient Customer Segmentation: A Strategy for Targeted Customer Services

Cited by

2023Hyper-Personalization for Enhancing Customer Loyalty and Satisfaction in Customer Relationship Management (CRM) Systems 2023Customer Analysis Using Machine Learning-Based Classification Algorithms for Effective Segmentation Using Recency, Frequency, Monetary, and Time 2024A Novel 3D Clustering Algorithm for Customer Segmentation 2022Behavioral Segmentation with Product Estimation using K-Means Clustering and Seasonal ARIMA 2023Demographic and Psychographic Customer Segmentation for Ecommerce Applications 2021Customer Segmentation Using Machine Learning

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