pass_by
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pass_by Data Products: APIs & Datasets
pass_by Pricing & Cost
pass_by’s data is made available on an annual subscription depending on whether you want platform access, data delivered via API or data feed, or a combination. Testing is available before purchasing.
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About pass_by
pass_by in a Nutshell
pass_by leverages groundbreaking AI to analyze the customer journey in the $4tn brick-and-mortar commerce market. pass_by enables retailers and those with a vested interest in retail to measure, analyze and predict the entire customer journey—from discovery to purchase.
Country Coverage
Data Offering
pass_by gives you a complete view of the brick and mortar customer journey: who they are, where they come from, where they go, and where they spend.
Our platform, APIs, and data feeds combine over six years of history with a 90-day predictive outlook, so you can measure past behavior and see what’s coming next. From visit patterns to purchase paths, pass_by helps you spot shifts early and act with confidence.
Use Cases
Our core focus is helping retailers improve decisions across store operations, marketing, and real estate.
For store operations teams, we align inventory and staffing with real-world demand by showing how local market trends impact individual store performance. We also help benchmark store performance against nearby competitors and peers.
For marketing teams, we quantify how campaigns drive visits and spend, and help brands understand who their customers are, where they come from, and where they convert. We also help identify incremental in-market customers.
For real estate teams, we support lease evaluation and site selection by benchmarking stores against local competitors and mapping trade areas based on actual behavior.
This visibility into real-world customer behavior also creates value in several adjacent industries; including financial services, real estate, marketing and market research.
Related Searches
Data Sources & Collection
pass_by leverages a unique breadth of data sources. This includes mobility data from 200+ million devices, 80 billion annual transactions from 210 million unique cards, physical in-store hardware assets from 500k+ stores, event data and a lot more. This is all mapped to 7,000 retail brands in order to make sense of the brick-and-mortar commerce world.
Key Differentiators
Most companies trying to measure in-store consumer behavior are built on a single, shaky foundation: mobile location data. It’s a narrow, error-prone signal with serious blind spots, especially in dense urban areas, multi-level malls, and enclosed retail formats. The result is missed visits, misattributed traffic, and models that fall apart the moment they are tested in the real world.
pass_by was built to solve this problem.
We don’t rely on one data source, and we don’t treat foot traffic as the final metric. Instead, we combine multiple high-scale datasets, including mobility, spend, and demographic signals, to deliver a precise and comprehensive view of real-world customer behavior. That means we can measure store performance accurately, even in the most complex locations, and give you visibility far beyond just visit counts.
With pass_by, you get answers others cannot provide:
Who is visiting your store, not just how many
Where they came from and how far they traveled
What else they did before and after, including other stores, brands, or neighborhoods
And most importantly, where they actually convert
We track the full journey, from discovery to purchase. That means you see what drives value, not just volume.
It’s not about counting visits. It’s about understanding customer intent, movement, and spend. That’s what drives better decisions in store operations, marketing, real estate, and beyond.
While others make guesses based on limited and siloed data, pass_by gives you clear, consistent visibility into every step of the customer journey. Our data is accurate, explainable, and built for action.
Data Privacy
pass_by does not surface or provide any PII. All data is aggregated at a store level.
All underlying data used to build our product is fully opted-in; through explicit consumer opt in and contractual warranties.
Integrations
Frequently asked questions about pass_by
What does pass_by do?
pass_by leverages groundbreaking AI to analyze the customer journey in the $4tn brick-and-mortar commerce market. pass_by enables retailers and those with a vested interest in retail to measure, analyze and predict the entire customer journey—from discovery to purchase.
How much does pass_by cost?
pass_by’s APIs and datasets range in cost from $10,000 / year to $10,000 / year. Get talking to a member of the pass_by team to receive custom pricing options, information about data subscription fees, and quotes for pass_by’s data offering tailored to your use case.
What kind of data does pass_by have?
Consumer Behavior Data, Audience Data, Store Location Data, Foot Traffic Data, and 6 others
What data does pass_by offer?
pass_by gives you a complete view of the brick and mortar customer journey: who they are, where they come from, where they go, and where they spend. Our platform, APIs, and data feeds combine over six years of history with a 90-day predictive outlook, so you can measure past behavior and see what’s coming next. From visit patterns to purchase paths, pass_by helps you spot shifts early and act with confidence.
How does pass_by collect data?
pass_by leverages a unique breadth of data sources. This includes mobility data from 200+ million devices, 80 billion annual transactions from 210 million unique cards, physical in-store hardware assets from 500k+ stores, event data and a lot more. This is all mapped to 7,000 retail brands in order to make sense of the brick-and-mortar commerce world.
What’s pass_by’s data privacy policy?
pass_by does not surface or provide any PII. All data is aggregated at a store level. All underlying data used to build our product is fully opted-in; through explicit consumer opt in and contractual warranties.
What are the best use cases for pass_by’s data?
Our core focus is helping retailers improve decisions across store operations, marketing, and real estate. For store operations teams, we align inventory and staffing with real-world demand by showing how local market trends impact individual store performance. We also help benchmark store performance against nearby competitors and peers. For marketing teams, we quantify how campaigns drive visits and spend, and help brands understand who their customers are, where they come from, and where they convert. We also help identify incremental in-market customers. For real estate teams, we support lease evaluation and site selection by benchmarking stores against local competitors and mapping trade areas based on actual behavior. This visibility into real-world customer behavior also creates value in several adjacent industries; including financial services, real estate, marketing and market research.
What platforms is pass_by integrated with?
Narrative I/O, BattleFin Ensemble, AWS Data Exchange, Snowflake Data Marketplace, Google Cloud Analytics Hub, SAP Data Marketplace, Cherre, Maiden Century, Databricks Marketplace, and Dewey