Churn analysis and customer segmentation of a cosmetics brand using data mining techniques

Data minig is the process of finding hidden and unknown patterns in hugeamounts of data. Data mining has a wide application area such as marketing,banking and finance, medicine and manufacturing.Churn analysis and customer segmentation are two common application areasof data mining. Churn modeling is predicting which customers will leave thecompany. This allows companies to increase customer loyalty by producingspecial campaigns. Customer segmentation is the process of dividing customersinto mutually exclusive groups. Segmenting customers enables companies todevelop customized marketing programs for them.This thesis aims to determine the customer profile who likely to leave and thecustomer segments of a cosmetic brand and develop customized campaigns andmarketing strategies. Clustering techniques used for segmentation andclassification techniques used for determining the churners.