Home Data Privacy Roundup Paapi’s Hybrid Model Tackles Ad Measurement Without Third-Party Cookies

Paapi’s Hybrid Model Tackles Ad Measurement Without Third-Party Cookies

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A UK-based early-stage startup called Paapi, which just closed its pre-seed funding round last month, is building a platform to help advertisers with privacy-safe ad measurement.

If your first thought was, “Wonder if they’re named after the Protected Audience API in the Privacy Sandbox?” then I’m sorry to inform you that your brain is broken. (Welcome to the club.)

But you’re also quite right.

Co-Founders Dan Hesmondhalgh and David Tam – who met a few years ago when they were both working at Relay42, an Amsterdam-based customer data platform – chose the name Paapi because they thought it sounded cool. Tam also spent the past five years deeply involved in Sandbox testing.

“We’re of the opinion that if the Privacy Sandbox does take off, we’ll ride on those coattails,” Tam said.

And even if there are no coattails to ride – the wind’s mostly gone out of Sandbox’s sails since Google reneged on its third-party cookie deprecation plans – that’s okay, too.

Paapi isn’t putting all of its eggs into one Sandbox. (The sentiment is Tam’s; the mixed metaphor is mine.)

‘A hybrid approach’

The platform uses multiple privacy-enhancing technologies, including the Sandbox APIs, to analyze ad performance without relying on third-party cookies.

The idea, Tam explained, is to take a hybrid approach that includes a mix of probabilistic tracking and consented deterministic data when it’s available.

Paapi tracks paid clicks and impressions across channels and links those actions to sales and ad spend through a mix of PETs and direct integrations with ad platform APIs so brands can get a sense of which ads and channels contributed to each conversion – without having to blindly trust an ad platform’s reporting.

“There’s an age-old issue with ad platforms grading their own homework,” Hesmondhalgh said. “I mean, if you were to believe everything you’re told by Google, Meta and other platforms, then you should literally in some cases be seeing double the revenue.”

Most of the data Paapi (the company) collects is on-device, including through PETs like PAAPI (the Sandbox API). But the plan is to embrace as many PETs as possible going forward, including Apple’s AdAttributionKit for apps, Private Click Measurement on Safari and Interoperable Private Attribution, which is a joint proposal for privacy-preserving attribution being developed by Meta and Mozilla.

“It’s not the Wild West anymore for data collection,” Hesmondhalgh said. “We’re collecting data that users have given us permission to use from their actual device.”

Ready for action

Hesmondhalgh acknowledged that Paapi isn’t the only startup developing technology to enable privacy-safe measurement and attribution.

But there’s a unique twist in Paapi’s ability to directly activate audiences based on its understanding of customer behavior. The activation piece was inspired by the time

Hesmondhalgh and Tam spent working at a CDP.

“This is certainly something that’s doable by others, but we’ve architected our platform from the ground up to do that, whereas most other MTA platforms haven’t been focused on activation,” Hesmondhalgh said.

And because Paapi has activation in mind, it helps customers keep to their cost–per-acquisition (CPA) targets and make sure they’re not overspending. The platform calculates clicks and impressions across channels and clocks which audiences have already been exposed.

“We can suppress those audiences on Meta or Google or display so the customer doesn’t exceed their CPA,” Tam said. “That way they can always maintain their KPI threshold.”

ROI and Attribution Analysis with AI abstract concept vector illustration. Marketing and Advertising. Measure the return on investment for marketing campaigns. AI Technology. abstract metaphor.Looking ahead

For now, the Paapi team is staying lean.

Hesmondhalgh and Tam just hired a couple of developers and they’re in the process of onboarding a lead engineer, which will bring the headcount to six people. Next up, the plan is to recruit a few folks to help with business development and marketing.

Meanwhile, the product road map over the next couple of quarters is packed, including developing a method for tracking customer lifetime value, building a trusted execution environment and adding an AI assistant with a conversational interface so clients can query their data.

But is there the same urgency for privacy-enhancing tech as there was before the Privacy Sandbox became a punchline?

Google’s U-turn on third-party cookies in Chrome did “remove some of the urgency around privacy,” Hesmondhalgh said. “That’s the short answer.”

“What hasn’t changed, though, is that brands are still struggling to accurately measure and optimize the returns on their cross-channel spend,” he said. “And we’re not just talking about programmatic – it’s across all spend.”

That’s not to say customers don’t care about privacy anymore, he said. For some, it’s still a top priority. But for others, it’s now a side benefit.

“I’d say it’s become more a sub-header rather than the headline,” Hesmondhalgh said.

🙏 Thanks for reading! Hope you had a good July 4. Stay cool out there and don’t forget to hydrate. As always, feel free to drop me a line at allison@adexchanger.com with any comments or feedback.

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