Retail media has long held a data advantage over most other advertising channels. Purchase signals, household-level transaction history, SKU-level behavior – the raw material for precision targeting has always existed within the channel. What’s taken longer to build is the infrastructure to put that data to work to not only measure performance, but to enhance it.
The signal problem
Delivery pacing, audience reach, and frequency are visible to media teams while campaigns are in flight, and optimizations happen against those signals routinely. Where the channel has historically fallen short is in connecting those in-flight decisions to actual purchase behavior – not just reporting on it, but feeding it directly into the optimization layer in a way that’s automated and continuous.
Marketing mix modeling (MMM) has been the primary workaround, and it has real strengths, particularly in accounting for cross-channel effects that single-channel attribution can’t capture. The technology has also gotten meaningfully faster; monthly model runs represent a real improvement over quarterly ones. But a monthly MMM output is still a modeled estimate.
Whatever activation layer is running against that signal is working from a statistical approximation of purchase behavior, not the transactions themselves, and routing it from a measurement vendor into an activation platform adds delay on top of the modeling lag.
Closing the loop
The shift happens when the purchase signal enters the optimization layer during the campaign rather than after it, allowing the media to learn from actual in-store conversions while it still has time to act on them.
Infillion’s infrastructure makes closing that loop possible by connecting Catalina’s transaction data – drawn from millions of loyalty-linked households at the SKU level – directly into a proprietary measurement platform, which links media exposures to actual in-store purchases. That signal feeds continuously into Infillion’s DSP, powered by The Brain, Infillion’s optimization algorithm, which uses it to refine audience selection and shift spend toward the channels and formats driving the most conversions. Because the measurement and activation layers run on the same stack, the signal moves between them without another intermediary or the latency that typically comes with one.
What counts as a conversion here is a checkout at the register, not an e-commerce purchase. For grocery CPG brands, where over 90% of purchase volume moves through physical stores, that distinction is fundamental. Optimizing toward online transactions means optimizing toward a fraction of how shoppers actually buy these products. The in-store signal best reflects how the category is purchased.
What this means for grocery retailers
Retail media has built a credible attribution story. Connecting a media exposure to an actual purchase has been one of the channel’s defining advantages, and it has brought meaningful budget into RMNs. The next opportunity is to apply that measurement capability from post-campaign reporting into the execution layer itself.
For grocery RMNs, in-flight optimization changes what they can actually deliver to CPG advertisers. Every campaign that runs through the network contributes to a growing model of in-store purchase behavior, providing insight into which audiences convert, at what point in the purchase cycle, across which product categories and creative formats, and more. The intelligence behind it is proprietary to that retailer and compounds over time.
The right question
The industry conversation around outcome-based buying is heading in the right direction. The more important question is what counts as a successful outcome, where that signal comes from, and whether it can be acted on during the campaign. For grocery CPG, that outcome is an in-store purchase, one influenced by a combination of signals and behaviors, but ultimately measured at the register.
As retail media matures, the networks that can optimize toward real purchase behavior, no matter what the path to purchase looks like, will have a meaningful advantage. Infillion determines the parameters that matter for each campaign and drives toward the outcomes that reflect how the retailer’s shoppers actually buy.
If you’re a grocery retailer building out your retail media network or a CPG brand looking to drive more in-store purchases, reach out to learn more about Infillion Catalina retail media solutions.
