Customer Segmentation Using Clustering and Data Mining Techniques

Kishana Ram Kashwan · C. M. Velu

75 citations0/0 files storedInternational Journal of Computer Theory and Engineering

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

Abstract

Clustering technique is critically important step in data mining process.It is a multivariate procedure quite suitable for segmentation applications in the market forecasting and planning research.This research paper is a comprehensive report of k-means clustering technique and SPSS Tool to develop a real time and online system for a particular super market to predict sales in various annual seasonal cycles.The model developed was an intelligent tool which received inputs directly from sales data records and automatically updated segmentation statistics at the end of day's business.The model was successfully implemented and tested over a period of three months.A total of n = 2138, customer, were tested for observations which were then divided into k = 4 similar groups.The classification was based on nearest mean.An ANOVA analysis was also carried out to test the stability of the clusters.The actual day to day sales statistics were compared with predicted statistics by the model.Results were quite encouraging and had shown high accuracy.

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1999Comparing performance of feedforward neural nets and K-means for cluster-based market segmentation

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2018Customer Segmentation in XYZ Bank Using K-Means and K-Medoids Clustering 2020The impact of big data market segmentation using data mining and clustering techniques 2018Forecast of individual customer’s demand from a large and noisy dataset 2023How can algorithms help in segmenting users and customers? A systematic review and research agenda for algorithmic customer segmentation 2022Cluster-based demand forecasting using Bayesian model averaging: An ensemble learning approach 2015Forecasting Supply Chain Demand by Clustering Customers 2017Market segmentation through data mining: A method to extract behaviors from a noisy data set 2022Analysis of Unsupervised Machine Learning Techniques for an Efficient Customer Segmentation using Clustering Ensemble and Spectral Clustering

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