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.
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Notes
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Although this manual labeling may be simplistic and coarse-grained, we posit that it generally reflects the accepted health perception of food categories.
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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: Bailey, J., Khan, L., Washio, T., Dobbie, G., Huang, J., Wang, R. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2016. Lecture Notes in Computer Science(), vol 9651. Springer, Cham. https://doi.org/10.1007/978-3-319-31753-3_42
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DOI: https://doi.org/10.1007/978-3-319-31753-3_42
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