The analysis of customer service choices and promotion preferences using hierarchical clustering

Charles V. Trappey, Amy J.C. Trappey, Ai Che Chang, Ashley Y.L. Huang

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


Many factors influence customers' menu preferences and influence the promotional strategies used to improve a restaurant competitiveness and long term sustainability. This research uses preference variables to form distinctive clusters of consumers that are loyal to a gourmet Japanese style chain restaurant. Using customers' menu selections over time, demographic attributes, and historical sales data, the store manager hierarchically groups customers. For the first level of segmentation, customers are clustered based on frequency of visits and dining expenditures. Secondly, K-means clustering is used to analyze each sub-segment based on menu choice preferences. Given these results, the restaurant provides customized coupons and price discounts for each customer based on their previous preferences and behaviors. The study demonstrates an effective means to better manage and promote complex menu selections in a chain store or franchise restaurant environment.

Original languageEnglish
Pages (from-to)367-376
Number of pages10
JournalJournal of the Chinese Institute of Industrial Engineers
Issue number5
StatePublished - 1 Sep 2009


  • Consumer preferences
  • Customer clustering
  • Customer relationship management
  • Data mining
  • Market segmentation

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