M.S. Applied Data Science - Capstone Chronicles 2025

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Mapping the Market: Uncovering Brand Alliances from Consumer Cross-Shopping Networks In today’s interconnected retail landscape, understanding how customers interact across brands has become essential for businesses seeking to optimize marketing strategies, partnerships, and competitive positioning. This project explores customer overlap among local brands in San Diego using a graph-based network model, where nodes represent brand locations, and edges represent the percentage of shared customers. By analyzing these relationships, the study aims to uncover latent structures of brand competition and collaboration in a local market ecosystem. Such insights are valuable in a time where consumers exhibit complex, cross shopping behaviors that defy classic market segmentation assumptions. Through the perspective of network analysis, we hypothesized that brands serving similar customer demographics or geographies will cluster closely together in the network, and certain larger brands will emerge as “bridges” connecting otherwise distinct customer communities, revealing opportunities for cross promotions. Background Community engagement is vital for local businesses to sustain lasting relationships with their customers. However, in a post-COVID retail environment, driving local interactions can be challenging, as purchase habits have changed. Furthermore, identifying economic patterns for outside partnerships in the market is increasingly difficult. While retail activity has largely recovered, businesses still face challenges in uncovering meaningful cross-brand relationships that can strengthen community ties and revenue growth. When viewed alongside these environmental factors, the emergence of new consumer spending data sources presents an

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