Todd James, Founder & CEO of Aurora Insights, is a recognized data and AI expert.
Most companies are sitting on one of their most underused economic assets. It isn’t a new product. It isn’t a new market. It isn’t an acquisition target. It’s the data they already have.
Having led AI and data strategy at 84.51° and Kroger, and now working across industries as an advisor, I keep seeing the same pattern. Executives talk about data as a strategic asset. In practice, most use it to run reports, track KPIs and increasingly activate AI-powered experiences. All of that has value. But it still treats data as an input to the business rather than a product of it.
The Math Most Executives Are Missing
The margin contrast tells the story. Core retail margins typically run 2% to 5%. On-site retail media advertising margins run 50% to 90%, according to BCG at the high end and the ANA at the floor, with scale being the primary driver of where a network lands in that range. That’s a fundamentally different business built on top of the same customer relationships and the same store traffic.
Walmart Connect, Walmart’s U.S. retail media network, grew 41% in fiscal year 2026, according to Walmart’s SEC earnings filing. Kroger’s alternative profit businesses, which include retail media, data analytics and other ventures outside traditional grocery operations, generated $1.5 billion in operating profit in fiscal year 2025, according to Kroger’s earnings release. Both built significant revenue streams on data they were already collecting. The core asset was always there. What changed was the decision to treat it as a product.
What I Saw At 84.51° And Kroger
During my time as chief data and technology officer at 84.51°, Kroger’s data science and retail media subsidiary, the most important lesson wasn’t about data volume. It was about what consumer packaged goods (CPG) brands truly needed to do their jobs.
A brand team planning promotions, assortment and media didn’t need more data. It needed to understand how its shoppers behaved across 2 billion annual transactions, across 62 million households, in ways that could directly inform where to spend, what to stock and how to measure results. Stratum, 84.51°’s self-service analytics platform, gives CPG partners unified access to sales, customer and inventory data. Kroger commercialized what it already knew. The data was always there. What changed was structuring it around the decisions brands needed to make and packaging it as a product they would pay for.
This Isn’t A Retail Story
Retail gets the attention because the numbers are impossible to ignore. But the underlying dynamic isn’t unique to retail. It applies wherever a company sits on information that others can’t replicate and someone else needs to do their job better.
Take media. A publisher knows which content formats, audience segments and contextual moments drive advertiser outcomes. If the publisher structures that knowledge into a product—an audience insights tool, a performance benchmark or a planning service—it’s done exactly what Kroger did. It’s turned operational data into a revenue stream that didn’t exist before.
The same pattern shows up in logistics, where routing and demand data can help shippers reduce cost and improve planning, or in healthcare, where operational data can help systems improve care delivery and resource allocation. In manufacturing, it comes into play where equipment and production data can power benchmarking or predictive maintenance services that customers will pay for.
The industry doesn’t matter. What matters is whether the data improves a decision someone else owns and whether the company has the discipline to build it into something repeatable.
AI Makes This More Urgent, Not Less
As foundation models become more capable and widely available, the tools themselves stop being the differentiator. Everyone will have access to capable AI. What separates companies is what they feed it.
I saw this dynamic early at 84.51°. The models weren’t the advantage. The 62 million households behind them were. That logic applies everywhere now.
AI also makes it more practical to act. Information locked inside systems, transactions and workflows for years can now be organized and activated faster than was possible before. That’s a reason to move, not wait.
The profit stream may already be there. The work is deciding to go find it.
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