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 near-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 eligible CTV impression for how likely it is to drive a store visit, before the auction clears.
- That score drives precision bidding: the campaign always targets the next most valuable impression, so every dollar works toward the highest-value inventory available.
- 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.
How Cuebiq-verified visits steer PurePlay’s buying, using the Sunglass Hut campaign.
Proof of Concept: What this looked like at Sunglass Hut
The proof point comes from a Connected TV campaign for Sunglass Hut, where PurePlay’s bid model - trained on Cuebiq-verified store visits - beat the brand’s own 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 Cuebiq account team, or contact PurePlay at letsgo@pureplay.ai.
Want the full Sunglass Hut story? Read the case study →
This article was originally published by Cuebiq and is republished with permission. Read it on cuebiq.com →
