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Systematically and quantitatively determining patterns in consumer flow is an important problem in marketing research. Identifying these patterns can facilitate an understanding of where and when consumers purchase products and services at physical retail shops. Collecting data on real consumers who shop at retail stores is one of the most challenging and expensive aspects of these studies. This article introduces ConvenienceProbe, a phone-based data collection system for retail trade-area analysis. The proposed method targets local residents shopping at neighborhood convenience stores. This study deploys and tests the system by collecting real customer flow data in neighborhood convenience stores. Results show that the consumer flow data collected from the ConvenienceProbe system is comparable to that from a traditional face-to-face interview method.
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Stored only when both papers are in the corpus — 10 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.