RRetailNext provides an IoT-based retail technology platform for shopping centers and stores, covering real-time foot traffic measurement, occupancy control, staff schedule optimization, shopper journey analysis, visual merchandising insights, and asset protection. It works by collecting data from IoT sensors and cameras, delivering dashboards and mobile/video access, and enabling data-driven experiments on store layouts to see how changes affect engagement and purchases. Its all-in-one approach—analytics, merchandising, and security—sets it apart, and it has earned IoT Connected Retail Application of the Year 2023 in the UK and Europe. Its goal is to help retailers reduce labor costs, maximize conversions, and improve safety and shopper experience through actionable insights.
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Industries
Company Size
201-500
Company Stage
Late Stage VC
Total Funding
$226M
Headquarters
Campbell, CA
Founded
2007
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Total Funding
$226M
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Funded Over
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Pine59 + RetailNext: connecting the full retail journey. In-store performance data meets beyond-the-store market intelligence. Alexei Agratchev and Thomas Walle on why connecting both sides of the door changes what retailers can decide. By Thomas Walle Retailers have never had more data about their stores. But much of that data still stops at the front door. At Pine59, Pine59 help retailers understand everything happening beyond the store. Who is in the market, where customers come from, where else they shop, how trade areas are changing, and how competitors are performing. RetailNext has spent years building the other side of that picture, helping retailers understand what happens once a customer walks through the door. Now Pine59 is bringing those two worlds together. The new integration between Pine59 and RetailNext connects beyond-the-store market intelligence with in-store performance data, giving retailers a more complete view of the customer journey and, importantly, a better understanding of why individual stores perform the way they do. The relationship behind the partnership goes back years. RetailNext CEO Alexei Agratchev and Pine59 co-founder Thomas Walle first connected when the company was still known as Unacast. Alexei invited Thomas to RetailNext's Executive Forum to share his vision for location intelligence with a room full of retail leaders. What started as a conversation about where retail intelligence was heading has now become a product integration. Alexei and Thomas recently sat down to talk about how the market has changed, why connecting inside and outside intelligence matters, and what retailers can do when they finally see both sides of the store door. Five minutes with Alexei and Thomas. You and I go back a long way. I remember what this pitch sounded like at Executive Forum, back when it was still just an idea and a few slides. Retail's changed a lot since then. What's changed most about the problem you're solving? Back then, location intelligence basically meant counting bodies. How many people visited and at what time. What's changed is that retailers stopped asking "how many" and started asking "who, and why." They want to know where a visitor came from, where else they shop, what their demographic profile looks like, and what competition is doing. The bar moved from measurement to explanation. And honestly, retailers got more sophisticated faster than most vendors did; they'd already squeezed everything they could out of their own four walls and hit a ceiling. What they were missing wasn't more data. It was context. Pine59 built RetailNext on the idea that the store tells the whole story. Millions of data points, all from inside four walls. But I keep hearing the same question from retailers: the product's right, the staffing's right, so why is this location still underperforming? Why do they need to see what's happening outside the store too? Because in-store data tells you what happened, not why. You can see traffic dipped on a Tuesday, conversion slipped in Q2, one location lags another that looks identical on paper. The store can't tell you why, because the answer usually isn't in the store. It's who's in the trade area, where they're going instead, which competitor just opened two miles away, whether the whole catchment softened or just your part of it. When a retailer tells me "the product's right, the staffing's right, and it's still underperforming," that's almost always a signal the explanation lives outside the store. You can't fix what you can't see, and half the picture is beyond the door. Give me a real example. What decision does a retailer make differently with this combined view that they couldn't make before? Take an underperforming store. The classic question is: do Pine59 fix it or close it? Without outside data, that's a gut call, and usually an expensive one. With the combined view, you can tell the two apart. If foot traffic in the trade area is healthy but your capture rate is low, that's an execution problem - merchandising, staffing, hours - and it's fixable. If the whole catchment is drying up, people leaving the area, a competitor pulling them off, that's a location problem, and no amount of in-store tuning saves it. Same symptom, opposite decision. One keeps a store open and turns it around; the other stops you from pouring money into a location that was never going to work. Or, say a retailer's deciding where to open next. Their instinct is to build near their best-performing stores, clone the winner. But their in-store data only tells them those stores convert well, not why, or whether that magic repeats somewhere new. With the combined view, they can see what actually makes a location work - the visitor profile in the trade area, how people move through it, and which nearby brands pull the same customer. Then they can go find that pattern somewhere they don't have a store yet. Instead of guessing off last year's sales, they're matching real market DNA. That's the difference between expanding by hope and expanding by evidence, and it's the difference between a new store that ramps in months versus one that takes years, or never does. There's no shortage of companies that claim to do location intelligence. Most retailers I talk to are juggling two or three vendors already, and still missing the full picture. What's actually different here? Most retailers are stitching. One vendor for foot traffic, another for demographics, RetailNext for in-store, and a person whose real job becomes reconciling three datasets that don't agree. You lose time, you lose accuracy at every seam, and you still don't fully trust the answer. What's different is that this partnership between RetailNext and Pine59 is integrated. Outside and inside sit in the same view, calibrated to the same stores, so nobody's exporting CSVs and eyeballing whether the numbers line up. The integration removes the seam, and the seam was where most of the error and most of the wasted time lived. Let's say a retail exec only has budget for one of these: in-store or beyond-the-store data. Not both. From your perspective, what do they lose by picking just one? Either way, you're flying with one eye closed. In-store alone, you see execution in perfect detail and miss the market entirely - you'll optimize a store that's underperforming for reasons that might have nothing to do with the store. With beyond-the-store data alone, you understand the market but can't see whether you're actually converting it, so you can't tell a demand problem from a delivery problem. Neither half is wrong. They're just incomplete in opposite directions. The value was never in either dataset on its own. It's in the fact that one explains the other. Where does this go next? What does the retailer five years from now expect that they don't have today? Five years out, no retailer's going to accept the customer journey being split in two - outside data in one system, inside data in another, and a human trying to draw the line between them. They'll expect one continuous view, from the parking lot to the checkout counter, where what pulls someone toward a store and what happens once they're inside are read as a single story. That's the direction, and this integration is the first real piece of it. Pine59 is connecting the two halves that have always been managed separately, and once retailers see the whole journey in one place, they won't want to go back to guessing at the gap. From market potential to store performance. For Pine59 at Pine59, this partnership is about something bigger than combining two datasets. Retailers make decisions across a continuum. Where should Pine59 open? Who actually shops in this market? Which competitors are winning? Why is one store outperforming another? Are Pine59 facing a market problem or an execution problem? And where should Pine59 invest next? Historically, answering those questions meant moving between systems and trying to reconcile different versions of reality. Connecting Pine59's view of the world outside the store with RetailNext's view of what happens inside changes that. * For marketing teams, it means understanding who visits your stores versus your competitors, and identifying the customer segments you're winning or missing. * For real estate and expansion teams, it means evaluating potential markets against the characteristics of the customers and locations already driving performance. * For operations teams, it means separating store-level execution problems from changes happening across the wider market. * For retail leadership, it means having one connected picture of market opportunity and store performance. The interesting part isn't simply having more data. It's being able to connect cause and effect. A store doesn't exist in isolation. Its performance is shaped by the people, competitors, neighborhoods and movement patterns around it, and then by what happens when those customers actually walk through the door. Pine59 and RetailNext can now connect those two halves. From outside the store to inside it. From market potential to actual performance. From seeing what happened to understanding why. That's the retail intelligence Pine59 has been working toward. Turn aggregated location intelligence into competitive advantage. Discover how Pine59 can power your analytics, products and AI with statistical insights about places and populations.
Alpha Modus launches patent infringement suit against RetailNext - targeting use of AI technologies in global retail analytics.
Want additional evidence of the American consumer’s declining confidence? Check out retail foot traffic. Visits to U.S. stores dropped by 4.3% in early March, the Financial Times (FT) reported Sunday (March 16), citing data from RetailNext. That drop was on top of decreases that kicked off with the beginning of the year. And Placer.ai, which tracks signals from consumers’ mobile devices, has notched fewer trips to big box retailers like Walmart and Target in the past few weeks, the report added
RetailNext unveils Traffic 3.0, the next evolution in in-store analytics to drive accuracy, efficiency, and savings for retailers.
Battery Ventures General Partner Russ Fleischer will join RetailNext's board alongside Battery Principal Roland Anderson and VP Dawit Workie, and comments: 'RetailNext stands out for its technology and deep understanding of the challenges retailers face today.
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We're working on gathering enough insights on this company, check back soon!
Industries
Company Size
201-500
Company Stage
Late Stage VC
Total Funding
$226M
Headquarters
Campbell, CA
Founded
2007
Find jobs on Simplify and start your career today
Don't see your dream role? Check out thousands of other roles on Simplify.Browse all jobs