Know exactly how many people walked into each location last month — and which marketing dollar brought them
Mobile data, in-store sensors, and ad-platform store visits — pulled into one per-location view that ties to your customer records.
The problem
You want to know how many people walked into the Denver location last month, what the trade-area capture rate was, and how Denver stacks up against Austin and Tampa. The data exists, but it lives in pieces. Placer.ai costs around $80,000 a year and takes six weeks to implement. SafeGraph charges by the record. Foursquare Places, Cuebiq, and Veraset price in the $1,000 to $50,000-plus monthly range. In-store sensor systems (RetailNext, V-Count, Sensormatic ShopperTrak, Density.io) want $25 to $500 per location per month plus install costs. Google Ads Store Visits and Meta Offline Conversions show signal inside the ad platform but do not connect to your customer records. None of these tools alone answers the questions the CFO and the franchisees both care about — and stitching the data together in-house takes a data engineer four to eight weeks per source plus ongoing maintenance. Regulated verticals (HIPAA, GDPR, California consumer-data) add another layer that most of these platforms do not gate cleanly.
What success looks like
Every location continuously pulls foot-traffic data from the sources you use — mobile-derived (Placer.ai, SafeGraph, Foursquare, Cuebiq), in-store sensors (RetailNext, V-Count, Sensormatic, Density.io), and ad-platform attribution (Google Ads Store Visits, Meta Offline Conversions). The data joins to your actual customer records, so a foot visit can be linked to a call, a POS purchase, or an email click for the same person. Per-location trade-area capture rate calculates automatically. Compliance rules for each state and vertical apply on the way in. Multi-banner operators see foot traffic across banners from one view, with the right privacy gates in place. Every record and every source refresh is preserved with provenance so an auditor or a privacy review can ask where a number came from and get a clean answer.
How most operators solve this today
Five categories of tools touch foot traffic. None of them do all of it for a multi-location operator.
Mobile-derived foot-traffic specialists (Placer.ai, SafeGraph, Foursquare Places, Cuebiq, Skyhook, Veraset, Reveal Mobile, Near, Pitney Bowes Foot Traffic, AnalyticsIQ)
$1,000 to $150,000+ per year, plus per-record pricing
Strong brand-level visit estimates. They do not connect to your customer records or to your call, POS, and email data.
Location intelligence platforms (Buxton, Tango eSite Analytics, SiteZeus, ESRI Business Analyst, CARTO, Targomo, Pitney Bowes Spectrum)
$10,000 to $150,000+ per year
Built for one-off site-selection studies. Not continuous per-location ingestion.
In-store sensors (RetailNext, V-Count, Hella Aglaia, Brickstream, Sensormatic ShopperTrak, Density.io, Aislelabs)
$25 to $500 per location per month, plus install costs
Counts people once they are already inside the store. Does not measure trade-area or capture rate.
Ad-platform store visit attribution (Google Ads Store Visits, Meta Offline Conversions, Foursquare Attribution, GroundTruth, AdTheorent, Reveal Mobile)
Free inside the ad platforms, $1,000 to $10,000+ per month for specialists
Locked inside each ad platform. Cannot join to your customer records across sources.
Build it in-house
$130,000 to $220,000 per year per engineer, plus four to eight weeks per source integration
Custom integration per source. Ongoing maintenance burden grows with every new source.
What changes when this is an agent skill
The system continuously ingests foot-traffic data from every source you choose — mobile-derived providers, in-store sensors, and ad-platform store-visit attribution — into one per-location view that ties to your customer records. Per-location trade-area capture rate calculates automatically from the drive-time and demographic data you have on the territory. A foot visit can be linked to a call from the same caller, a POS purchase from the same shopper, an email click from the same person, or a paid-ad impression that ran in the same trade area — across every source you connect. State and vertical compliance rules apply on the way in. HIPAA dental, GDPR EU, and California consumer-data ingestion are gated separately. Multi-banner operators see foot traffic across banners with the right privacy boundaries. Every record and every source refresh is preserved with timestamp, source, and provenance, so when an auditor or privacy review asks where a number came from, the answer is on file. Placer.ai, SafeGraph, and Foursquare remain useful for brand-level mobile-derived visits. RetailNext and V-Count remain useful for sensor-based in-store counting. This is the layer that combines them into one view tied to your customers.
Agents that include this skill
Skills live inside agent rentals. To get this skill in production, hire any of the agents below — context-tuning at onboarding is included in the first month.
Offline Attribution Intelligence Agent
Surface-as-foundation hybrid — answers which marketing dollar generated which revenue dollar at which store.
FAQ
- How is this different from Placer.ai, SafeGraph, or Foursquare Places alone?
- Those are excellent mobile-derived foot-traffic sources at the brand level. They do not connect a visit to a specific customer's call, purchase, or email click. This pulls that data in and joins it to your customer records.
- How is this different from Buxton or SiteZeus?
- Buxton and SiteZeus are built for one-off site-selection studies. This is continuous per-location ingestion for the locations you already have.
- How is this different from RetailNext or V-Count sensors?
- Sensors count people once they are in the store. This combines sensor data with mobile-derived trade-area data so you also know who came close and did not enter.
- How is this different from Google Ads Store Visits or Meta Offline Conversions?
- Those are locked inside their ad platforms and only see signal that ran through their platform. This combines store-visit signal from every ad platform plus your other sources and joins to your customers.
- Which sources can it ingest?
- Mobile-derived providers (Placer.ai, SafeGraph, Foursquare, Cuebiq, Skyhook, Veraset), in-store sensors (RetailNext, V-Count, Sensormatic ShopperTrak, Density.io), and ad-platform attribution (Google Ads Store Visits, Meta Offline Conversions). You pick which ones you want.
- How does it connect a foot visit to a specific customer?
- Through your customer records. When a visit lands and a customer is present in the same trade area in your data, the visit is linked. If the visit cannot be tied to a known customer, it stays in the unknown pool and contributes to your aggregate metrics.
- How does this handle HIPAA, GDPR, and California consumer-data rules?
- Compliance rules are configured per state and per vertical. HIPAA dental patient visits get gated separately. GDPR EU PII-adjacent data gets gated separately. California consumer-data rules apply where they should.
- What does the audit trail look like?
- Every foot-traffic record is preserved with timestamp, source, provenance, and the privacy policy that was in force when it was ingested. Searchable when an auditor or privacy review asks where a number came from.