We’re pleased to announce a new partnership between Cuebiq and PurePlay
For brick-and-mortar retail, the campaign outcome that matters most is also usually the last one marketers find out about. A campaign can post strong impressions, healthy completion rates, and reach across all the right targets—and still leave the biggest question unanswered: did anyone actually walk through the door?
That’s the gap Cuebiq and PurePlay solve for with their new outcomes-powered media solution. Instead of treating store visits as a lagging metric you check after the campaign wraps, the partnership turns visits into the signal that runs the campaign, in real time, for the length of the flight.
Deploy Campaigns that Learn from Evidence (not Estimates)
It starts with confirmation. Cuebiq measures real people walking into stores—and into competitors’ stores—continuously, using privacy-first, consent-based location data rather than surveys or statistical modeling.
That distinction matters more than it sounds: an outcome built on evidence behaves very differently in a bid model than one built on an estimate, because it’s precise enough to train on. Here’s what happens next…
- Those verified visits feed PurePlay’s model, which scores every CTV bid request for visit propensity before the auction clears—in under 10 milliseconds.
- High-propensity impressions get bid up, while low-propensity ones get bid down or skipped entirely.
- No dashboards to babysit, no budgets to manually reshuffle mid-flight.
Then the loop closes. Each week’s visits sharpen the next week’s buying. So the longer a campaign runs, the smarter and more efficient it gets—with continuous measurement and no changes required to a team’s existing workflow.
Proof of Concept: What this looked like at Sunglass Hut
The proof point comes from a Connected TV summer campaign for Sunglass Hut, where PurePlay’s bid model—trained on Cuebiq-verified store visits—beat the brand’s own holiday cost-per-visit benchmark by 17%, reaching real shoppers at 3.63 times the rate of an untargeted buy.
The more interesting insight is this: What a household was watching predicted a Sunglass Hut visit better than where that household lived. Validated against Cuebiq’s visit data, viewership scored a 0.86 information value, compared to 0.81 for DMA-level geography and 0.63 for fine-grained ZIP code targeting.
It’s a reminder that as CTV attribution matures as a discipline, behavioral signal is increasingly out-predicting geography (which has often been the default proxy for “who’s likely to visit” throughout digital media’s history).
PurePlay x Cuebiq: Built for the seat you’re already in
The best part? None of this requires ripping out an existing tech stack. PurePlay’s scoring container runs inside the exchange…
- Upstream of whatever DSP a team already buys through
- Across all major SSPs
- Under a single deal ID
No new tags, no engineering lift, no new contract—the intelligence just arrives already in place.
For retail, QSR, and dealership marketers, that’s the practical case for outcomes-powered media. It’s not a new platform to learn, it’s a way to make the platforms already in use accountable to the metric that was always the point.
Here’s the truth: As CTV budgets keep shifting toward performance accountability industry-wide, closing the loop between screen and storefront is becoming less of a differentiator and more of a baseline expectation.
To learn more, Contact Cuebiq, reach out to your or contact PurePlay at letsgo@pureplay.ai.
