Tracking the evolution of customer purchase behavior segmentation via a fragmentation-coagulation process

Ling Luo, Bin Li, Irena Koprinska, Shlomo Berkovsky, Fang Chen

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

5 Citations (Scopus)

Abstract

Customer behavior modeling is important for businesses in order to understand, attract and retain customers. It is critical that the models are able to track the dynamics of customer behavior over time. We propose FC-CSM, a Customer Segmentation Model based on a Fragmentation-Coagulation process, which can track the evolution of customer segmentation, including the splitting and merging of customer groups. We conduct a case study using transaction data from a major Australian supermarket chain, where we: 1) show that our model achieves high fitness of purchase rate, outperforming models using mixture of Poisson processes; 2) compare the impact of promotions on customers for different products; and 3) track how customer groups evolve over time and how individual customers shift across groups. Our model provides valuable information to stakeholders about the different types of customers, how they change purchase behavior, and which customers are more receptive to promotion campaigns.
Original languageEnglish
Title of host publicationProceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence
EditorsCarles Sierra
PublisherInternational Joint Conferences on Artificial Intelligence
Pages2414-2420
Number of pages7
ISBN (Electronic)9780999241103
DOIs
Publication statusPublished - 2017
Externally publishedYes
Event26th International Joint Conference on Artificial Intelligence, IJCAI 2017 - Melbourne, Australia
Duration: 19 Aug 201725 Aug 2017

Conference

Conference26th International Joint Conference on Artificial Intelligence, IJCAI 2017
CountryAustralia
CityMelbourne
Period19/08/1725/08/17

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