Branded consumer foot traffic insights in the US

What is PassBy?

PassBy is a geospatial intelligence platform that tracks real world foot traffic and visitor behavior across U.S. retail locations. On Dewey, PassBy publishes anonymized and aggregated visit counts for more than 3 million points of interest across 7,000 plus brands, drawn from a panel of tens of millions of devices. A companion dataset adds visitor demographic and psychographic profiles, built in partnership with TransUnion, so researchers can see who is showing up, not just how many.

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What academic researchers should know about PassBy foot traffic data

Retail Store Visits covers weekly, daily, and hourly visitor volume for individual U.S. retail points of interest back to 2019, with a daily level version added in February 2026 for finer grained analysis. Retail Store Visitors adds monthly visitor characteristic and psychographic distributions, including income, education, and other brands visited, using TransUnion's CAMEO classification system. Both datasets share a Store ID key, and PassBy also provides a Placekey crosswalk, so foot traffic and visitor profiles can be joined to each other and to other point of interest data on Dewey.

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Why academic researchers choose PassBy on Dewey

PassBy's foot traffic counts go through ground truth validation, checked against real world data to keep the numbers anchored in what is actually happening at a store rather than a model's best guess. The visitor profile data is what sets PassBy apart from most foot traffic providers: pairing anonymized psychographic and demographic distributions with visit counts lets researchers ask not just how much traffic a location gets but who that traffic is. That pairs well with other data on Dewey. SafeGraph adds global point of interest coverage and transaction level spend, Advan Research offers a second foot traffic methodology drawn from mobile panel data for cross validation, Consumer Edge adds transaction data that can be compared against visit volume, and Similarweb extends the same brands into online traffic for omnichannel research.

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PassBy academic research ideas and use cases

Foot traffic at the store level is the backbone of retail and real estate research. Researchers can compare visit volume across similar brands and markets to study how store performance responds to new competition, a road closure, or a change in nearby foot traffic generators, using PassBy's point of interest level detail rather than a market wide average.

The demographic and psychographic layer opens up brand loyalty questions that visit counts alone cannot answer. By joining Retail Store Visitors to Retail Store Visits through the shared Store ID, researchers can study whether stores drawing similar traffic volumes are drawing different types of customers, and how that shifts after a rebrand, a new store format, or a change in nearby demographics.

Urban planning and mobility researchers can use PassBy alongside other point of interest data on Dewey to study how retail foot traffic shifts across neighborhoods over time, comparing patterns before and after a transit change, a new development, or a public health event.

Because PassBy and Advan Research measure foot traffic through different methodologies, pairing them opens up a natural robustness check: do two independently derived foot traffic panels agree on the direction and size of an effect. That kind of comparison gives researchers a genuine check when building new mobility metrics or validating existing ones.

Marketing researchers can use the psychographic distributions to study how retail visit patterns line up with seasonal promotions, advertising exposure, or new store openings, using PassBy's brand level detail across more than 7,000 brands to compare campaigns or store formats at scale.

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