Choosing a foot traffic data provider is one of the more consequential data purchasing decisions a retail or real estate team will make. The provider you select determines the accuracy of your site selection models, the reliability of your competitive benchmarks, and whether your team can trust the numbers enough to act on them.
The market has matured significantly over the past few years. There are now several credible providers, each with different strengths, data sources, and pricing models. This guide compares the major platforms on what actually matters: accuracy, coverage, the data they deliver, how you access it, and what it costs.
For background on what foot traffic data includes and how it is produced, see our foot traffic data guide. For a comparison of hardware-based counting methods vs data platforms, see how to measure foot traffic.
What to compare when evaluating providers
Before looking at individual companies, it helps to know what dimensions matter most. Every provider will tell you their data is accurate and comprehensive. The differences emerge when you ask specific questions:
Accuracy and validation. How does the provider validate their data? Against what ground truth? How many validation points? Is the correlation figure independently auditable? A provider claiming “high accuracy” without disclosing methodology is asking you to take their word for it.
Data coverage. How many locations are covered? Is coverage consistent across urban, suburban, and rural areas? Does the provider cover your entire portfolio and your competitors?
Data depth. Does the provider offer just visit counts, or also trade area analysis, demographics, psychographics, competitive benchmarking, spend data, and predictive forecasts? The breadth of the dataset determines how many business questions you can answer from a single source.
Access methods. Can you access the data through a self-serve platform, via API, or through cloud delivery to your data warehouse? Most teams need a platform for business users and an API for data teams.
Historical depth. How far back does the data go? You need at least 3-5 years for meaningful trend analysis and seasonality modelling.
Pricing model. Is pricing transparent? Is there a trial or entry-level option? Does pricing scale with the number of users, locations, or data volume?
Provider comparison table
| Provider | Best for | Accuracy | US coverage | Data depth | Access methods | Historical depth | Pricing |
|---|---|---|---|---|---|---|---|
| PassBy | US retail intelligence across store ops, real estate, and marketing | 94% correlation to ground truth, validated against in-store sensors + sales data, 15+ data inputs | 1.5m+ store locations, 1m+ trade areas | Foot traffic, spend, demographics, psychographics, trade areas, competitive benchmarking, 90-day predictive feeds | Almanac platform, API, cloud delivery (Snowflake, AWS, GCP), AI assistant integrations (ChatGPT, Copilot, Gemini) | 5+ years | 3 tiers: Essential, Premium, Ultimate. Test & Learn (90-day trial) available. See pricing → |
| Placer.ai | Broad location analytics with free tier for exploration | Undisclosed methodology. Limits data for locations with fewer than 50 unique devices | Wide US coverage across retail, CRE, dining, entertainment | Foot traffic, demographics, trade areas, competitive benchmarking, migration trends. No spend data | Platform (UI), API add-on, data marketplace | Varies by plan | Custom annual contracts. Freemium tier available with limited access. Estimated $12k-$50k/year for paid plans |
| SafeGraph (Dewey) | Global POI data and neighbourhood-level patterns | Average geocode deviation of 2.17 meters for POI placement. Visit data accuracy not publicly stated | 80m+ POIs globally across 195+ countries | POI database, building footprints, neighbourhood visit patterns. Stronger on POI data than visit analytics | Data downloads, API, Snowflake marketplace | Varies | Annual subscriptions based on data volume. Free data samples available |
| Unacast | International coverage and GDPR-compliant location data | Aggregated from 15+ data suppliers. Accuracy not publicly benchmarked against ground truth | 1bn+ monthly devices across 180+ countries | Foot traffic, trade areas, cross-visitation. Available as API, data feeds, and SaaS platform | Visitations API, DaaS feeds, Insights SaaS platform | Up to 3 years | Custom pricing by product. Packages available |
| Echo Analytics | Geospatial data for AdTech and market research | 95%+ polygon coverage claimed. Visit accuracy not publicly stated | 80m+ locations globally | Retail performance, AdTech targeting, market research tools | Platform, data feeds | Varies | Custom pricing on request |
| Dataplor | Emerging markets and global brand coverage | Combines AI, machine learning, and human validation for POI accuracy | 370m+ locations, 15k+ brands across 250+ countries | POI data, brand coverage, operating hours, transaction estimates, foot traffic estimates | API, system integrations | Varies | Annual subscriptions with weekly updates. Usage-based pricing available |
Provider-by-provider breakdown
PassBy
PassBy provides market intelligence for US retail, built around Almanac, a self-serve platform that gives store operations, real estate, and marketing teams a shared view of brand performance, market dynamics, and competitive positioning.
What sets it apart: PassBy’s accuracy validation is the most transparent in the market. The 94% correlation to ground truth is achieved by validating against hundreds of thousands of in-store sensors and sales data records using over 15 independent data inputs. Most competitors either do not disclose their validation methodology or validate against a smaller, less diverse set of ground truth sources.
The data goes beyond visits. PassBy indexes over $1 trillion in consumer spend data alongside foot traffic, giving teams the ability to see whether traffic translates into actual purchasing behaviour. The 90-day predictive feed, built in partnership with Stanford’s NeuralProphet team, provides forward-looking visit estimates that enable proactive planning rather than reactive reporting.
PassBy also leads on access flexibility. Beyond the Almanac platform and standard API/cloud delivery, PassBy integrates with AI assistants including ChatGPT, Microsoft Copilot, and Google Gemini, allowing teams to query market intelligence conversationally inside their existing workflow.
Pricing: Three tiers (Essential, Premium, Ultimate) with a Test & Learn option offering 90 days of Almanac access for teams evaluating the platform. See pricing →
Best for: Retail teams that need validated, accurate US foot traffic and spend intelligence with a self-serve platform, predictive capabilities, and flexible data delivery.
Placer.ai
Placer.ai is the most widely known name in foot traffic analytics, with a broad platform covering retail, commercial real estate, dining, entertainment, civic, and finance use cases.
Strengths: Wide brand recognition. Extensive free tier that lets users explore basic visit data before committing. Strong content marketing and industry reports that have built credibility in the CRE and retail sectors. Their data marketplace offers supplementary datasets (crime, planned development, psychographics) that can be layered on top of visit data.
Limitations: Placer does not publicly disclose their accuracy validation methodology in the way PassBy does. Their documentation notes that data reliability is limited for locations receiving fewer than 50 unique devices, which can affect smaller or rural locations. Placer does not offer spend data, which means teams that need to connect visits to purchasing behaviour require a second data source. Pricing is custom and not published, which makes budgeting harder for teams evaluating options.
Best for: Teams that want a broad location analytics platform with strong brand recognition and are comfortable with custom pricing discussions. The free tier makes it a reasonable starting point for teams exploring foot traffic data for the first time.
For a detailed comparison, see PassBy vs Placer.ai.
SafeGraph (Dewey)
SafeGraph, now part of Dewey, built its reputation on the quality of its global POI database. Their core strength is point-of-interest data: accurate store boundaries, category tags, brand attribution, and building footprints across 195+ countries.
Strengths: Best-in-class global POI coverage and geocoding precision (2.17m average deviation). The POI database is the foundation that other analytics are built on, and SafeGraph’s is among the most comprehensive available. They also offer free data samples and open census datasets, which have made them popular in the academic research community.
Limitations: SafeGraph is stronger on POI data than on visit analytics. Their visit patterns data operates at the neighbourhood (census block group) level rather than the individual store level in many cases, which limits its usefulness for store-specific competitive benchmarking. The acquisition by Dewey has shifted the product direction, and the current offering may differ from what long-time users expect.
Best for: Teams that need high-quality global POI data as a foundation, particularly for international coverage. Less suited as a primary foot traffic analytics platform for US retail teams who need store-level visit data and competitive benchmarking.
Unacast
Unacast provides location intelligence with a strong emphasis on international coverage and GDPR compliance. With data from 15+ suppliers covering 180+ countries, they offer one of the broadest geographic footprints in the market.
Strengths: Genuine global coverage across 180+ countries, which is essential for multinational retailers. Strong privacy-first positioning with GDPR compliance built into the product. Flexible access through API, data feeds, and a SaaS platform, letting teams choose the delivery method that fits their infrastructure.
Limitations: Up to 3 years of historical data is less than some competitors offer. Accuracy is not publicly benchmarked against ground truth in the way PassBy reports it. The product is split across separate offerings (Visitations API, Visitations DaaS, Insights SaaS) which can make it harder to get a single unified view.
Best for: Multinational retailers and brands that need location intelligence across multiple countries with strong privacy compliance. Teams focused exclusively on the US market may find more depth from US-specialist providers.
Echo Analytics
Echo Analytics focuses on geospatial data for retail performance analysis, AdTech targeting, and market research.
Strengths: Specific tooling for AdTech use cases, which sets it apart from providers focused primarily on retail operations or real estate. 80m+ global locations with strong polygon coverage.
Limitations: Data sources are not fully transparent. For niche or highly localised B2B sectors, coverage may be less complete. Less established track record in the retail intelligence space compared to larger providers.
Best for: Teams with AdTech or programmatic advertising use cases where location-based audience targeting is the primary need.
Dataplor
Dataplor specialises in global POI data with a particular strength in emerging markets and international brand coverage.
Strengths: The broadest geographic coverage of any provider listed here: 370m+ locations across 250+ countries. Strong on brand-level data including operating hours and transaction estimates. Combines AI, machine learning, and human validation for POI accuracy.
Limitations: Primarily a POI and brand data company rather than a visit analytics platform. Foot traffic estimates are available but are not the core product in the way they are for PassBy or Placer.ai.
Best for: Companies that need global POI data across emerging and developed markets, particularly for brand mapping, store location databases, and international expansion planning.
How to choose the right provider
The right provider depends on three things: your primary use case, your geographic focus, and how your team needs to access the data.
If your primary need is US retail intelligence (store ops, real estate, marketing, competitive benchmarking) and you need validated accuracy you can trust for high-stakes decisions: PassBy. The accuracy validation, spend data, predictive feeds, and AI integrations are purpose-built for this.
If you need a broad platform with a free tier to explore first and your use cases span retail, CRE, dining, and civic: Placer.ai offers wide coverage and the freemium model lets you test before buying.
If you need high-quality global POI data as a foundational dataset for international analysis: SafeGraph for structured POI coverage, or Dataplor for emerging market depth.
If you operate internationally and need GDPR-compliant location data across 100+ countries: Unacast provides the broadest privacy-compliant international coverage.
If your primary use case is AdTech and audience targeting: Echo Analytics has specific tooling for this.
Many enterprise teams use more than one provider, combining a US-focused platform like PassBy for domestic retail intelligence with a global POI provider like SafeGraph or Dataplor for international coverage.
Ready to see how PassBy compares for your specific use case? Book a 15-minute walkthrough →
FAQ
What is the best foot traffic data provider? It depends on your use case. For US retail intelligence with validated accuracy, PassBy provides the strongest combination of foot traffic, spend data, predictive feeds, and a self-serve platform. For broad exploration with a free tier, Placer.ai is a reasonable starting point. For global POI data, SafeGraph or Dataplor. For international location intelligence, Unacast. See the comparison table above for a full breakdown.
How much do foot traffic data providers cost? Pricing ranges from free (Placer.ai freemium, SafeGraph samples) to thousands per year for full platform access. PassBy offers a Test & Learn tier (90-day trial) and three ongoing plans: Essential, Premium, and Ultimate. Most other providers offer custom pricing on request. See PassBy pricing →
What is the most accurate foot traffic data? PassBy achieves 94% correlation to ground truth by validating against in-store sensors and sales data across hundreds of thousands of locations using over 15 independent data inputs. Most other providers do not publicly disclose equivalent validation figures, making direct accuracy comparisons difficult. Always ask a provider how they validate and what their stated accuracy means.
Can I get foot traffic data for free? Some providers offer free tiers or data samples (Placer.ai freemium, SafeGraph open datasets). Google Business Profile and Google Maps Popular Times provide basic directional data at no cost. These free sources have significant limitations for professional use. For a full breakdown, see our guide to free foot traffic data.
What data do foot traffic providers actually give you? Most providers offer visit counts, trade area analysis, and competitive benchmarking. Some also include demographics, psychographics, spend data, and predictive estimates. The depth varies significantly by provider. PassBy offers the widest dataset including visits, spend, demographics, psychographics, trade areas, competitive benchmarking, and 90-day predictive feeds. See our foot traffic data guide for details on what each data type includes.
Do I need a platform or just the data? Most teams start with a platform (like Almanac) for business users who need to explore data and generate reports, then add API or cloud delivery for data teams who want to integrate foot traffic into internal models and dashboards. See our guide to foot traffic APIs for details on programmatic access.