A consumer behavior analytics model for commercial district marketing using network-structured stamp rally data

Marketing strategies should target entire commercial areas, not just individual stores. This study highlights the data collected from stamp rally events as cross-sectional consumer behavior data. Although stamp rally data have been analyzed as tabular data, this approach should capture the complexity of consumer behavior observed during such events. This study focused on the co-occurrence relationships between the pairs of stores identified through data. Moreover, the study proposed a novel method to analyze consumer behavior by representing these relationships in a network structure to address this challenge. Two events were held in 2023. In one event, data were collected from 621 participants in one event, and in the other event, data were collected from 1040 participants. The collected data were analyzed using conventional frequent pattern mining methods applied to tabular data and the proposed network-based method. Consequently, the proposed method identified community hub stores that could be used as catalysts for marketing to new consumer groups beyond the community. • Propose a consumer behavior analysis method by using stamp rally data and networks. • Analyze stamp rally data to explore marketing potential in commercial districts. • Identify key traffic builder stores that function as hubs connecting communities. • Reveal co-occurrence and usage patterns to expand marketing to new customers. • Investigate the differences between stamp rally data and everyday consumer behavior.