Customer segmentation using RFM analysis

Title

Customer segmentation using RFM analysis

 Author

van Burg, J.M. (TU Delft Electrical Engineering, Mathematics and Computer Science)

Contributor

Cai, J. (mentor)
van der Woude, J.W. (graduation committee)

Degree granting institution

Delft University of Technology

 Programme

Applied Mathematics

 Date

2020-07-06

 Abstract

This paper is a research on the segmentation of customers. The clustering of customers is done based on the variables recency, frequency and monetary value. Such a clustering is called an RFM-model. The clustering is done using the K-means clustering method. To find the optimal number of clusters the following performance metrics are used: Elbow method, Silhouette Analysis, and Davies-Bouldin Index. The RFM-model is extended by introducing the loyalty variable. This model is called an RFML-model. Lastly, further clustering is done within one of the clusters.


 Subject

Segmentation of customers
RFML-model
K-means method
Elbow method
Silhouette Analysis
Davies-Bouldin Index

 To reference this document use:

http://resolver.tudelft.nl/uuid:50c70e92-0d0f-4c85-8bfc-9aba11706df8

 Part of collection

Student theses

 Document type

bachelor thesis

 Rights

© 2020 J.M. van Burg
Files
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