Log in to save to my catalogue

Customer Analysis Using Machine Learning-Based Classification Algorithms for Effective Segmentation...

Customer Analysis Using Machine Learning-Based Classification Algorithms for Effective Segmentation...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_295676f271e84842a7de81b26a243699

Customer Analysis Using Machine Learning-Based Classification Algorithms for Effective Segmentation Using Recency, Frequency, Monetary, and Time

About this item

Full title

Customer Analysis Using Machine Learning-Based Classification Algorithms for Effective Segmentation Using Recency, Frequency, Monetary, and Time

Publisher

Switzerland: MDPI AG

Journal title

Sensors (Basel, Switzerland), 2023-03, Vol.23 (6), p.3180

Language

English

Formats

Publication information

Publisher

Switzerland: MDPI AG

More information

Scope and Contents

Contents

Customer segmentation has been a hot topic for decades, and the competition among businesses makes it more challenging. The recently introduced Recency, Frequency, Monetary, and Time (RFMT) model used an agglomerative algorithm for segmentation and a dendrogram for clustering, which solved the problem. However, there is still room for a single algo...

Alternative Titles

Full title

Customer Analysis Using Machine Learning-Based Classification Algorithms for Effective Segmentation Using Recency, Frequency, Monetary, and Time

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_295676f271e84842a7de81b26a243699

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_295676f271e84842a7de81b26a243699

Other Identifiers

ISSN

1424-8220

E-ISSN

1424-8220

DOI

10.3390/s23063180

How to access this item