Store traffic data is an estimate of how many people visited a place, built from a sample of mobile devices rather than counted at the door. Busy hours are free, around $200 a month buys visit estimates inside a site evaluation, and raw files license for five figures a year. Price changes what you may do with the number, not how true it is.
That distinction is the one that trips up most buyers. A door sensor counts. A mobile panel estimates, by watching a sample of phones and scaling up. Both get called foot traffic data, and they answer different questions.
I'm Clyde Christian Anderson, Founder and CEO of GrowthFactor.ai. I grew up working in family retail warehouses and now spend my days helping retail teams decide where to open next. This guide is about which source to buy for which decision, what each tier costs in 2026, and the one question none of them can answer.
What store traffic data actually measures
There are two kinds of store traffic data, and they are not substitutes. Counted data comes from a device at your own door: a beam sensor, a camera, or transactions per hour from the register. Modeled data comes from a provider that watches a panel of mobile phones, matches pings to known addresses, and scales the sample up to a population estimate.
The first kind is precise and covers only stores you operate. The second covers everywhere, including your competitors, and carries error at every step. If you need to know how many people walked into your own shop last Tuesday, the sensor wins. If you need to know how a competitor's location three towns over is performing, a panel is the only option you have.
The practical difference shows up in what you can say out loud. A door count supports "we had 412 visitors." A panel estimate supports "this location looks busier than that one," which is a comparison, not a measurement. We cover the five ways to measure traffic at your own stores separately, including what the hardware costs.
Which source answers which question
Match the source to the question before you look at pricing. Three questions get sold the same product, and only two of them are a counting problem at all.
How busy is my own store? Your own instrumentation answers this best, and Google Business Profile gives you busy hours, live busyness, and average visit duration for nothing. It reports busyness relative to that location's own typical peak rather than as an absolute count, and it only sees people who use Google.
How busy is a competitor's store? Only a mobile panel can tell you, because you cannot put a sensor in someone else's doorway. Popular Times on any public Maps listing gives you the shape of a competitor's week for free. It will not give you history, trade area, or a number you can put into a model.
How busy will this empty site be? Nothing measures it, at any price. A site with no store has no visitors to count. This is the question most retail teams are actually asking when they go shopping for foot traffic data, and it is the one that gets answered with a forecast rather than a measurement. You define the trade area, measure its demand, and compare it against stores you already understand.
Where to get foot traffic data for free
Four free sources are worth your time, and each one has a hard ceiling. Together they will tell you about places that already have stores in them, and nothing about a vacant one.
Google Business Profile and Popular Times. Covered above, and the ceiling is the thing to remember: relative busyness only, no export, no history you can chart.
Placer.ai's free point-of-interest tool. Placer publishes a free lookup that returns monthly visits, unique visitors, dwell time, and year-over-year change for a single property, plus zip and county rankings. Trade area demographics, visitor journeys, and any multi-location comparison sit behind the paywall. Useful as a sanity check on one address, not as a screening tool.
Census OnTheMap. The Census Bureau's LEHD program publishes block-level commute flows showing where workers live against where they work. It is not consumer visitation, but it is the best free proxy for daytime population, which matters for lunch trade and commuter-driven concepts.
State pedestrian counts. Texas, Washington, Colorado, and Minnesota all run public bicycle and pedestrian count programs with downloadable data, such as TxDOT's count program. These are permanent and short-term counters at fixed infrastructure points, built for transportation planning. Good for judging whether a specific corner has people walking past it, useless for comparing two shopping centers across town.
One correction, because it costs people weeks: OpenStreetMap has no pedestrian volume data. It carries sidewalk and pedestrian-zone geometry you can use to build a walkability network, which is a map, not a count.
What store traffic data costs in 2026
Cost tracks coverage and licensing rights. Every paid tier is estimating visits from the same kind of mobile sample, so paying more does not buy a truer number. It buys more places to look and more freedom in what you do with the result.
The tier that fits you follows from one question: are you evaluating sites, or building a model? Most retail real estate teams are doing the first and get quoted for the fourth. A raw mobility license decides nothing on its own. It is an input for a data science team that intends to build something with it, and if you do not have that team, the files will sit in a bucket.
For evaluating sites, the useful unit is a platform where visit estimates arrive next to demographics, competitor locations, and a score, so the traffic number is already in context. GrowthFactor Pro is $200 per month for a single seat, self-serve and month to month. Annual contracts add seats for the whole team, onboarding, and integrations, priced to the organization.
How accurate is store traffic data
Accurate enough to rank locations against each other, not accurate enough to quote as a count. The strongest public evidence on this is a PLOS ONE study of SafeGraph mobile location data covering 2018 to 2022, which found an average device sampling rate of 7.5% of the population. Device counts tracked population closely at the county level and much less closely at census tract and block-group level, and Hispanic, lower-income, and lower-education populations were consistently underrepresented.
Read that as a scale rule. The bigger the geography, the more you can trust the number. A metro-level comparison is meaningful; a single inline tenant in a large center is directional at best. We go deeper on how the providers differ in the foot traffic provider comparison, including which of them publish a validation figure at all.
Here is the position we take at GrowthFactor, and it is not the flattering one for a company that sells foot traffic in its product: the number is reliable for ranking a corner against the corner across the street, comparing cotenant draw within one trade area, and sizing competitive overlap. It is not reliable as the basis for an absolute sales forecast, and it degrades badly in vertical malls and dense strip centers where GPS drift and polygon misattribution put visits in the wrong tenant. Absolute forecasting belongs to your own store performance data.
That leads to four practices worth adopting before you underwrite anything on panel data:
- Check POI fidelity. Confirm the store polygon fits the real footprint, including multi-tenant parcels and stacked levels, and that visit rules exclude drive-bys.
- Demand the weighting method. Ask how the panel is post-stratified to local demographics and device penetration. If the vendor will not describe it, that is your answer.
- Calibrate against ground truth. Line up mobile-derived visits with door counters and POS for stores you already operate, then carry that correction factor into new markets.
- Set a minimum sample. Thin device counts at a location produce numbers that look precise and mean nothing.
This is also why our scoring is transparent by design. Every site score shows the inputs that moved it, from foot traffic to demographic fit to competition, across whatever lenses your workspace runs, so a number you cannot defend never leaves the room.
The same difference shows up against GIS tooling. Esri ArcGIS is the most powerful GIS platform available, offering maximum flexibility for teams with dedicated GIS analysts who can build custom spatial analyses. GrowthFactor is purpose-built for retail site selection teams that need answers without GIS expertise. Where Esri requires specialized knowledge to configure layers, run queries, and interpret spatial data, GrowthFactor delivers a scored site report in seconds from any address. Both platforms serve real estate teams, but the key difference is who does the work: with Esri, your analyst builds the analysis; with GrowthFactor, the platform builds it and your team interrogates the results. Cavender's Western Wear tripled their new store openings from 9 to 27 per year after switching to this self-serve scoring approach.
Two questions to put to any vendor before you sign: what is your panel density in this specific market, and what did you validate against? Rural and secondary markets are where panels thin out, and they are often exactly where the expansion plan is headed.
The rule change that is shrinking the panels
This is new since this article first published, and most buying guides have not caught up. A growing set of states now prohibit selling precise geolocation data outright. Oregon and Maryland already do, and Virginia became the third with a ban effective July 1, 2026, defining precise geolocation as accuracy within a 1,750-foot radius. Other states are weighing the same move.
For a retailer buying store traffic data, this is not a legal problem so much as a data quality one. Panels are assembled from consented app users, and every state that closes off a sales channel narrows the sample a provider can build from and sell into. Coverage in affected states gets thinner or gets modeled harder, and neither shows up on the invoice.
Add a third question to the vendor list: what is your consent basis, and how has your coverage changed in states that restricted geolocation sales? A provider who can answer cleanly is a provider who has done the work.
Retail foot traffic statistics for 2026
U.S. retail foot traffic rose 2.0% year over year in June 2026 while retail sales grew 8.4%, the fastest annual sales growth since 2022, per Colliers Retail Market Intelligence (published July 20, 2026). Visits are growing far slower than dollars, which means most of the sales gain is price and basket size rather than more people walking in.
Where those visits went in June 2026, per the same Colliers report:
| Category | Year-over-year visit change |
|---|---|
| Discount and dollar stores | +9.2% |
| Clothing stores | +4.9% |
| Hobbies, gifts, and crafts | +28% |
| Theaters and music venues | +27.4% |
Shopping center formats tell a similar story. Placer.ai's June 2026 Mall Index reported first-half 2026 visit growth of 4.7% for open-air shopping centers, 1.9% for indoor malls, and 1.0% for outlet malls, with June marking the third consecutive month of growth across all three formats. Placer.ai also found the median household income of the captured market slipped slightly year over year, a sign that the gains come from a broader mix of shoppers rather than a higher-income surge.
Two practical readings for a real estate team. First, open-air convenience-driven centers are the format with momentum, and they have set the pace every month of 2026. Second, a category that grows visits while the market grows 2.0% is taking share from somewhere, so category benchmarks matter more than market averages when you underwrite a site. For longer-run pattern context, see our guide to retail foot traffic trends.
What retail teams do with the number
Foot traffic earns its keep as one input among several, weighted against demographics, competition, and what your own stores already tell you. In-store retail is still where the money is. E-commerce reached 16.9% of total US retail sales in the first quarter of 2026, up from 16.0% a year earlier, per the Census Bureau, which leaves roughly 83% of retail spending happening in person. Opening the right ones still moves the whole business: the most recent ICSC halo effect study, published in December 2023, found that opening a store lifts online sales in its trade area by 6.9%, while closing one cuts them by 11.5%.
Precision matters more than it used to because the largest chains keep taking share. Walmart, Target, Costco, and Dollar General grew their combined share of physical retail visits from 16.8% in 2019 to 17.5% in the first quarter of 2026, according to Placer.ai. There is less slack in a trade area than there was, so a site that is merely acceptable is a more expensive mistake. For the trend picture across categories, see our retail traffic trends guide.
In practice, the traffic number does three jobs on our platform. It helps define a real trade area instead of a radius drawn on a map. It feeds cannibalization analysis, where the question is how much of a new store's volume comes out of an existing one. And it becomes one variable in sales forecasting, alongside the demographic and competitive inputs that determine whether visits convert.
The results come from that combination rather than the traffic feed alone. Cavender's Western Wear went from 9 new stores in 2024 to 27 in 2025, with every new location performing at or better than expected. Books-A-Million, the #2 book retailer in the US with 260 stores, saves 25 hours per analyst per week. TNT Fireworks screens sites 60% faster and reviews ten times more of them per committee meeting. GrowthFactor opens up every input behind a score so you can argue with it. The judgment stays where it belongs, because the landlord, the local politics, and the deal you can actually get are things no panel will ever see.
Frequently Asked Questions about Retail Foot Traffic Data
Where can I get foot traffic data for free?
Three places give you something real for nothing. Google Business Profile shows busy hours and visit duration for any listing, including your competitors'. Placer.ai's free point-of-interest tool returns monthly visits and dwell time for one property at a time. The Census Bureau's OnTheMap gives block-level commute flows, the closest free substitute for daytime population. None of them will price a site you do not already operate, and none export the history you would need to model on.
How much does store traffic data cost?
Free for relative busy hours from Google, or a single-property lookup from a vendor's lead-generation tool. Around $200 a month for visit estimates inside a platform that also carries demographics, competitors, and site scoring, which is where GrowthFactor Pro sits. Annual contracts priced to the organization once a whole real estate team needs seats. Five figures a year and up to license raw visit files into your own warehouse. Price buys coverage and licensing rights, not better accuracy.
What is the best retail foot traffic data provider in 2026?
It depends on what you plan to do with the number. Placer.ai is the most recognizable name in visit analytics and publishes a free single-property lookup. Unacast, which supplies GrowthFactor's foot traffic layer, and SafeGraph both sell mobility and point-of-interest files for teams that want the raw data. For deciding where to open next, the provider matters less than what sits around the data: GrowthFactor combines visit estimates with demographics, competition, cannibalization, and site scoring, starting at $200 per month for a single seat.
Can foot traffic data tell me how busy a new store will be before it opens?
No. Every foot traffic source measures visits that already happened at places that already exist, so a vacant site has nothing to count. What you can do is measure the trade area's demand and compare it against stores you already understand, then forecast from that analogue. Treat foot traffic as one input to that forecast rather than the answer itself.
What is the difference between GrowthFactor and Yardi for retail foot traffic and location data?
Yardi's commercial suite is built around lease management, property accounting, and portfolio operations for landlords and property managers. GrowthFactor covers the demand side that retail expansion teams need, combining foot traffic with site scoring, trade area demographics, competition mapping, and a deal pipeline in one place. TNT Fireworks used GrowthFactor to screen locations 60% faster while holding quality across more than 150 new sites.
Where to start
If you run stores and want to understand them better, start free: Google Business Profile for your own locations, and Popular Times to see which days and hours your competitors are busiest. If you are deciding where to open next, the traffic number on its own will not get you there, and a raw data license will get you further from the answer rather than closer.
What moves a real estate decision is traffic sitting beside demographics, competition, and a score you can open up and argue with. That is what our platform is built to do, and you can start on a single seat for $200 a month.