Shopping app Checkmate launches AI marketing platform for brands as ad tracking fades

Checkmate's AI marketing platform mate is now used by 700+ brands and on track for a $15 million run rate, with zero marketing spend. The profitable company built it on 12 billion intent signals from its shopping app's 100 million shoppers.

Categorized in: AI News Marketing
Published on: Aug 21, 2026
Shopping app Checkmate launches AI marketing platform for brands as ad tracking fades

Checkmate, the shopping app backed by Google Ventures and Paris Hilton, has quietly built an AI marketing platform called mate that more than 700 brands now use. The business is profitable and on track to exit the year at roughly a $15 million run rate, built with zero marketing spend, according to company financials.

The reveal closes the gap between how Checkmate was understood publicly and what it was actually building. When it raised $15 million in 2023, it looked like a consumer story: a shopping app that hit #1 on the U.S. App Store by getting brands to approve real promo codes and cash back for shoppers. The business on the other side of those transactions went unannounced.

The data collapse that made the timing right

The years Checkmate spent building its consumer side are the same years the industry's borrowed data disappeared. Apple's tracking prompt cut off mobile signal. Safari and Firefox blocked third-party cookies by default. Google spent years promising a replacement inside Chrome and then scrapped the plan, leaving marketers with signal loss and no new infrastructure. Media costs kept climbing as more advertisers chased less signal.

Over the same stretch, AI made the software layer trivial. Anyone can generate a campaign now. AI traffic to U.S. retail sites was up 393% year over year in Q1 2026, per Adobe Analytics. What looked like a consumer detour in 2023 turns out to be the one thing that got harder to buy: consented first-party data and a direct line to the shopper.

The consumer app was never just an app. Every offer redeemed, every price tracked, every purchase across app, email, SMS and desktop taught Checkmate how more than 100 million shoppers actually decide. That is more than 12 billion live intent signals, and they are what mate's agents run on.

Results brands are reporting

Everlane attributed $480,000 to mate in under 30 days across 2,450 orders, with a 30% lift in conversion. The roster added Quiksilver, Dickies and Eddie Bauer this month, and has begun expanding beyond ecommerce into travel and financial products.

"Before mate, we were considering turning off Meta ads altogether," said Adam McAreavy, Director of eCommerce at PSA Skincare, which has seen a 150% lift in return on ad spend on the platform. "It surfaced shoppers we could never reach before."

Checkmate's team has stayed lean for the scale: co-founder and CEO Harry Dixon, an Australian who previously worked with architect Frank Gehry, and co-founder Rory Garton-Smith, a former iPhone engineering program manager at Apple.

"We watched a generation of AI marketing tools launch as demos in search of data and distribution," said Dixon. "We did it in the opposite order. We spent years earning the shoppers, the signals and the brand relationships, and only now are we putting a name on it. mate launched today, but it has been compounding for a long time."

Garton-Smith frames the company's advantage in terms of what AI did to software: "The industry keeps asking what happens to startups when AI makes software easy to copy," he said. "Our answer is that the software was never the moat. The moat is a hundred million shoppers who show up for offers, and seven hundred brands whose campaigns get smarter because of each other. That took years of unglamorous work, and it is why the agents work."

Why this matters for marketing professionals

The collapse of third-party tracking has left many marketing teams competing for less signal at higher cost. Checkmate's model suggests one way forward: own the data at the source. For marketers, the practical takeaway is not that you need another AI tool - it's that the tools you use are only as good as the data they run on. If your team is evaluating AI marketing platforms, the question worth asking is what proprietary shopper data the vendor brings to the table, not just what the software can generate.


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