In January 2025, Battery Ventures made a majority growth investment in RetailNext, the smart store analytics platform operating in over 100 countries. The deal was valued between $100 million and $200 million. Battery replaced a complicated cap table with a single partner and earmarked significant capital for acquisitions.
RetailNext's CEO said publicly that the company now has "access to large amounts of capital for investments that make strategic and financial sense" and "complete alignment around building a very profitable business." Three Battery executives joined the board. The mandate is clear: grow the platform, acquire capabilities that extend it, and build a more complete data layer for physical retail.
The question is what they acquire next. The answer is probably sitting in the gap between what RetailNext measures and what a retailer can do about it.
The Pikato Precedent
RetailNext's own acquisition history tells the story. In 2015, they acquired Pikato, a mobile marketing platform that turned RetailNext's traffic and behavior data into triggered, personalized communications delivered to shoppers' phones. The thesis was straightforward: analytics data becomes more valuable when it drives an action. Measurement alone produces a dashboard. Measurement connected to an intervention produces a return.
That acquisition pattern — measurement platform buys action layer — has repeated across retail tech. The platforms that own the data eventually need to own a way to act on it, because the dashboard alone is a cost center. The retailer paying for analytics wants to know what to change, not just what happened.
What's on Battery's Dashboard
RetailNext's platform currently measures: foot traffic, zone dwell time, shopper journey paths, conversion rates, demographic inference, and POS correlation. The sensor infrastructure is mature. The data is continuous. The API exposes it in real time.
The interventions available to a retailer who reads that data are: remerchandise (weeks to execute), retrain staff (days), adjust lighting (capital expense if zone-level control even exists), reprice (margin risk). Every available response is slow, expensive, or both.
There is one environmental variable that changes instantly, costs nothing per adjustment, requires no labor, and reaches every person in the space simultaneously. Audio. And it is the one variable that nobody in the RetailNext ecosystem is measuring, correlating, or acting on.
The Acquisition Logic
Battery's pattern across their portfolio is consistent: invest in a data platform, then acquire capabilities that make the data more actionable or extend the data layer into new dimensions. The Standard AI playbook runs parallel. In January 2026, Standard AI completed its sixth acquisition, buying Pathr.ai to add spatial intelligence to its computer vision platform. The acquirer was not buying software. They were buying a new dimension of data and the operational intelligence embedded in it.
Audio is the next dimension. The in-store analytics platforms have comprehensive coverage of visual behavior — where people go, how long they stay, what they buy. They have zero coverage of the sonic environment those people are moving through. A platform that generates music tagged at the variable level, deploys it in retail environments, and correlates it with the behavioral data these analytics platforms already produce would fill a gap that currently appears as unexplained variance on every dashboard in the industry.
The Timing
Three conditions are true simultaneously, and none of them were true five years ago. The sensor infrastructure is mature and deployed at scale. Music can be generated to precise variable specifications rather than selected from a catalog. And the research linking musical variables to consumer behavior has accumulated for forty years without being operationalized at the store level.
The company that builds the connective layer between music variables and commercial outcomes, and deploys it across enough stores to prove the correlations are real, is building the acquisition target that every platform in this space will eventually need. The data asset compounds with every store-hour of correlated deployment. It cannot be replicated with capital alone. And the window is open now.
Entuned is in that window. We are building the action layer that turns store analytics into store response. If Battery is looking for the next Pikato — the next capability that makes RetailNext's data more valuable — the sound environment is the surface they have not explored. And it is on in every store, all day, every day.
Related reading: $2 Billion in Sensors. No Real-Time Levers., Why the Next Big Retail Tech Acquisition Will Be in Audio, and Closing the Loop on Retail Analytics.
Key Takeaway: Analytics platforms always acquire the action layer that makes their data more valuable — and audio is the only real-time intervention surface their ecosystem has not yet connected to.
Entuned is building the action layer that turns store analytics into store response. If you run retail analytics and want a real-time intervention surface, the pilot is the place to start.
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