Rapid Identification of Fresh Milk Customer Segmentation

Authors

  • Fadhila Hijryani Department of statistics, IPB
  • Bagus Sartono Department of statistics, IPB
  • Utami Dyah Syafitri Department of statistics, IPB

DOI:

https://doi.org/10.29244/xplore.v7i3.128

Keywords:

CART, classification, consumer segmentation, decision tree, K-Means

Abstract

Consumer segmentation is the process of grouping customers into some segments based on some shared similar characteristics. Consumer segmentation allows companies to understand the customer's characteristics in each segment, thus make them easier to establish suitable marketing strategies for each segment's characteristics.Companies tend to use marketing strategies with demographical and consumer behavioural based scheme of consumer segmentation therefore make them easier to identify customer as the characteristics are easily measured. This research uses k-means method for segmenting 419 customers of packaged liquid milk. The life style pattern of the customers are used as the basis of the segmentation. Furthermore, this research uses decision tree algorithm to classify characteristics of the new customer. According to Hartigan index alteration (26.2433), ideal number of segments is 4. After tree pruning step, classification modelling with CART method yielded 54.61% accuracy.

Published

2019-01-02

How to Cite

Hijryani, F., Sartono, B., & Syafitri, U. D. (2019). Rapid Identification of Fresh Milk Customer Segmentation. Xplore: Journal of Statistics, 7(3). https://doi.org/10.29244/xplore.v7i3.128

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