Who will be affected by supermarket health programs?

Tracking customer behavior changes via preference modeling

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

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

3 Citations (Scopus)

Abstract

As obesity has become a worldwide problem, a number of health programs have been designed to encourage participants to maintain a healthier lifestyle. The stakeholders often desire to know how effective the programs are and how to target the right participants. Motivated by a real-life health program conducted by an Australian supermarket chain, we propose a novel method to track customer behavior changes induced by the program and investigate the program’s effect on different segments of customers, split according to demographic factors like age and gender. The method: (1) derives customer preferences from the transaction data, (2) captures the customer behavior changes via a temporal model, (3) analyzes the program effectiveness on different customer segments, and (4) evaluates the program influence using a one-year data set obtained from a major Australian supermarket. Our results indicate that while overall the program had positive effect in encouraging customers to buy healthy food, its impact varied for the different customer segments. These results can inform the design of personalized health programs that target specific customers in the future and benefit more people. Our method can also be applied to other programs that use transaction data and customer profiles.
Original languageEnglish
Title of host publicationAdvances in Knowledge Discovery and Data Mining
Subtitle of host publication20th Pacific-Asia Conference, PAKDD 2016. Proceedings, Part I
EditorsJames Bailey, Latifur Khan, Takashi Washio, Gillian Dobbie, Joshua Zhexue Huang, Ruili Wang
Place of PublicationCham
PublisherSpringer, Springer Nature
Pages527-539
Number of pages13
ISBN (Electronic)9783319317533
ISBN (Print)9783319317526
DOIs
Publication statusPublished - 2016
Externally publishedYes
Event20th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2016 - Auckland, New Zealand
Duration: 19 Apr 201622 Apr 2016

Publication series

NameLecture Notes in Artificial Intelligence
PublisherSpringer
Volume9651
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference20th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2016
CountryNew Zealand
CityAuckland
Period19/04/1622/04/16

Keywords

  • Customer behaviors
  • Temporal preference modeling
  • Health programs
  • Shopping data analysis
  • Customer behaviours
  • Temporal preference modelling

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  • Cite this

    Luo, L., Li, B., Berkovsky, S., Koprinska, I., & Chen, F. (2016). Who will be affected by supermarket health programs? Tracking customer behavior changes via preference modeling. In J. Bailey, L. Khan, T. Washio, G. Dobbie, J. Z. Huang, & R. Wang (Eds.), Advances in Knowledge Discovery and Data Mining: 20th Pacific-Asia Conference, PAKDD 2016. Proceedings, Part I (pp. 527-539). (Lecture Notes in Artificial Intelligence; Vol. 9651). Cham: Springer, Springer Nature. https://doi.org/10.1007/978-3-319-31753-3_42