Pinterest announced its intentions to acquire tvScientific last week. But the company may face challenges convincing advertisers to get on board, although the integration is able to use data to scan across all devices connected to one household IP address.

Only 29% of U.S. business owners consider shoppable Pins, which drives engagement on the platform, to improve performance for ad campaigns. This can be compared with the 37% who use Pinterest to research trends to increase audience insights for brands, according to an April 2025 Adobe survey. 

Cross-device attribution is the vision. For the first time through the acquisition, Pinterest will have the ability to bring audiences to connected TV (CTV) for advertisers by integrating tvScientific’s technology directly into its performance ad products supported by artificial intelligence technology.

tvScientific operates through self-managed platforms that enable advertisers to pay by outcome rather than impression volumes.

The platform offers automated media buying, artificial intelligence-powered optimization models, and attribution systems connecting advertisement exposure on television screens to actions taken on mobile devices or desktop computers driven on a household’s IP address.

It can link a CTV ad exposure directly to a conversion that may happen on other devices within that same household and IP address. This provides transparency into how TV ads drive performance results. 

Advertisers set cost-per-outcome targets, with the platform automatically adjusting bidding strategies and inventory selection to achieve specified goals.

It is based on deterministic attribution and outcome-based buying, rather than probabilistic modeling, which is one of the most significant changes this integration offers. 

The pay-by-outcome model enables brands to pay for advertising based on specific results such as conversions, sales, or app installs, rather than just views or impressions.

If Pinterest has trouble gaining credit for its advertising offering, the tvScientific acquisition will allow it to claim credit for the conversions, according to the media outlet Ad Tech Explained.

For example, if Pinterest serves one ad on a TV screen in a household, it will have the ability to track it and take credit any conversion registered from that same household IP address on any other device in the house.

Using IP addresses are not yet completely obsolete, but relying heavily on them for targeting carries a long-term risk of regulatory restriction, which could degrade the effectiveness of the very measurement tools Pinterest buys today. 

The core of this integration means combining consumer interests in Pinterest’s massive repository of data with tvScientific’s specialized performance engine to improve targeting, optimization, and measurement across screens.

Pinterest built what it calls a "Taste Graph” from 600 million monthly active users who save billions of Pins. The Pins reflect what people plan to buy or do next.

Feeding these signals into tvScientific's platform can tell advertisers who to target on CTV. Most of the consumers are in the early stages of their journey to make a purchase.

The CTV performance space has become crowded. Vibe and MNTN are also simplifying TV buying for smaller and medium-sized advertisers, but in different ways. 

In early December, tvScientific began releasing a product it calls "Creative Advisor," a tool that identifies and shows the specific elements in a TV ad that drive performance.

Some advertisers that have tested early versions of the product have seen simple changes. For example, saying the brand name in the first six seconds in a television ad can boost results by more than 20%.

The performance tool analyzes everything in the ad such as tone, visuals, colors, actors and pacing.

It uses AI to predict the choices that can change outcomes, pulling measurements of the creative against a database of more than 7.5 billion performance data points and 5.3 million unique creative elements analyzed across tvScientific's network.