You can run a flawless retail media campaign and still waste the budget on it. The ceiling on your return is set long before the bids go live, by how well you understand your own products. Bid perfectly on the wrong claim, or back a SKU shoppers have quietly moved on from, and even efficient spend loses.
The budget is moving to the shelf
US retail media ad spend is on track to hit $69 billion in 2026, up from $58.8 billion in 2025, according to eMarketer. Nearly four in ten CPG ad dollars now run through retail media networks, according to Oliver Wyman.
A lot of that money isn't new. According to eMarketer, much of the growth comes from budgets shifting out of search, social, and trade marketing, with some genuinely new dollars on top. Brands make the move because retail media targets shoppers close to the point of purchase and ties spend more directly to sales.
The growth is also concentrated. eMarketer expects Amazon and Walmart to capture roughly 89% of the incremental retail media spend in 2026. So most brands are pouring more budget into a handful of powerful networks, competing for the same shoppers, on the same shelves.
More spend, less certainty
The money is moving faster than the measurement. In Skai's 2026 State of Retail Media report, only 15% of brands say they have strong confidence in how they measure it, and three-quarters rate their measurement as weak or merely adequate.
So brands face a strange risk. The last-click numbers a network reports tend to overstate what its ads actually drove, so a campaign can look like a winner while funding sales that would have happened anyway. You can spend more and more, with total confidence, and keep pouring it behind the wrong products.
Retail media rewards precision, and precision starts with your products
Product data won't measure your media for you. That's a separate job, and other tools own it. What product data decides is the question that comes before the buy: which products and claims deserve the spend in the first place.
Retail media is a precision channel. You bid on placements down to the individual product, against a retailer's first-party purchase data. That precision is the whole appeal, and it's also why your own product data sets the ceiling on performance.
Think about what a strong retail media plan actually requires. Start with which products in your portfolio are gaining demand and which are fading. Then the claims and attributes shoppers in that category respond to, whether that's high protein, clean label, or a specific format. And the whitespace, so you're not overspending on crowded terms while the quietly growing attribute goes unbid.
If your product data can't answer those questions, no amount of bid optimization closes the gap. You'll run efficient campaigns behind the wrong products.
What product-level intelligence changes
This is where Product Intelligence earns its place in the retail media stack. Enrich product data at the UPC level with the attributes, claims, and consumer signals tied to each item, and the picture changes. Category and brand teams can see which Demand Themes are growing in a category, then match spend to them retailer by retailer.
Take a beverage brand planning its next quarter on Walmart Connect. Rather than bidding on the same generic terms as every competitor, the team sees that "no added sugar" is pulling faster than "natural" in the category. Two of its own SKUs carry that claim but get no media support. A third is being described by shoppers in language the brand never put on the label. That's the difference between spending against a blurry picture and spending against a clear one.
Harmonya builds this layer. It enriches product data across attributes and connects it to consumer feedback, so teams can understand what's driving demand and act on it. It sits between the data the networks hand you and the decisions you still have to make.
Teams that harmonize product data, consumer feedback, and market signals see what's shaping demand faster and with more confidence. Let's talk about how Harmonya turns fragmented data into decision-ready intelligence.
FAQ
Why is retail media spend growing so fast?
Retail media offers first-party shopper data and cleaner, closer-to-purchase attribution than most other channels, so brands are shifting trade and shopper marketing dollars into it. eMarketer expects US spend to reach $69 billion in 2026.
How does product data affect retail media performance?
Retail media targets down to the individual product, so returns depend on knowing which of your products, claims, and attributes are actually driving demand. Weak or inconsistent product data caps performance no matter how well the bids are managed.
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