Eyeota & ShareThis Tackle Signal Loss with Predictive AI Audiences

NEW YORK, NY – April 21, 2026 – In a significant move to address the digital advertising industry's growing challenges with signal loss and data fragmentation, Eyeota, a Dun & Bradstreet company, has partnered with ShareThis, a Predactiv Company. The two firms today launched ShareThis In-Market, Powered by Eyeota, a new audience solution designed to help marketers target consumers with a high probability of making a purchase.

This collaboration introduces 900 new in-market audience segments built from predictive consumer signals. By combining the vast behavioral data of ShareThis with Eyeota's AI-driven modeling and activation infrastructure, the solution aims to provide a scalable and privacy-compliant way for advertisers to reach valuable audiences across the globe, even as traditional tracking methods like third-party cookies become less reliable.

Navigating a Fragmented Advertising World

The launch arrives at a critical juncture for the digital marketing ecosystem. For years, advertisers have relied on third-party cookies to track users across websites, build audience profiles, and measure campaign effectiveness. However, this foundation is crumbling. Major browsers like Safari and Firefox have already implemented stringent tracking protections, and while Google has adjusted its timeline, the industry-wide shift away from third-party cookies continues to accelerate, driven by both technological changes and consumer demand for greater privacy.

This trend, coupled with robust privacy regulations such as Europe's GDPR and California's CCPA, has created a phenomenon known as "signal loss." Marketers are finding it increasingly difficult to gather the data needed for precise targeting, personalization, and attribution. Industry reports indicate that a vast majority of marketers are already adapting their strategies, pivoting towards first-party data and exploring new technologies to maintain campaign performance. The challenge is not just adapting to the absence of cookies but navigating a complex and fragmented landscape of different identifiers, platforms, and privacy rules across the globe.

In response, the ad tech industry has been racing to develop alternatives. These range from strengthening first-party data collection through Customer Data Platforms (CDPs) and embracing contextual advertising, to developing new identity frameworks like Unified ID 2.0 and leveraging privacy-enhancing technologies like data clean rooms. The new offering from Eyeota and ShareThis enters this evolving market with a distinct focus on predictive analytics.

A Two-Pronged Approach to Predictive Intent

The ShareThis In-Market solution is built on a two-part framework that leverages the specialized strengths of each company. The process begins with ShareThis, which operates under the new Predactiv parent company and its proprietary Predactiv Data Platform. ShareThis analyzes behavioral signals across its massive global network, which spans over 3 million domains and captures 60 billion user events per month from more than a billion users.

Using proprietary AI and Large Language Model (LLM) driven modeling, ShareThis sifts through this ocean of data—including content consumption, search activity, and on-site interactions—to identify patterns that signal a user is actively in-market for a product or service. This goes beyond simple past behavior to forecast future intent.

“Our predictive models are built to identify real consumer intent as it forms, relying on behavioral signals observed across the open web,” said Michael Gorman, Chief Product Officer at Predactiv. “By combining our AI-driven scoring with Eyeota’s modeling and activation capabilities, we’re able to translate high-intent signals into scalable, privacy-conscious audiences.”

Once ShareThis identifies these high-intent signals, Eyeota steps in. The company selects the top 1% of the most potent signals and applies its own AI-driven modeling to transform them into activation-ready audiences. Critically, this is done through Eyeota’s privacy-first, ID-agnostic infrastructure, meaning it is not dependent on cookies or other unstable identifiers. This process ensures the resulting audiences are not only precise but also scalable and interoperable across different advertising platforms.

“This new offering makes it easier for marketers to reach the right consumers, even as signals are disappearing and the ecosystem is becoming more fragmented,” explained Marc Fanelli, SVP Global Digital Audiences & Operations at Dun & Bradstreet. “By selecting the highest intent signals from ShareThis and translating them into addressable audiences through our global, ID-agnostic infrastructure, we’re enabling advertisers to reach consumers based on what they are likely to do next, not just what they have done in the past.”

Global Scale and Omnichannel Activation

A key feature of the new solution is its breadth. The 900 in-market segments span a wide range of key advertiser verticals, including Automotive, Finance & Insurance, Retail & Ecommerce, CPG, and Travel & Hospitality. This provides marketers with granular options for reaching consumers who are demonstrating purchase intent in specific categories.

Furthermore, the audiences are built for a modern, omnichannel media environment. Advertisers can activate these segments across a diverse array of channels, including connected TV (CTV), online display, mobile, social media, streaming audio, and even digital out-of-home (DOOH). This allows brands to execute consistent, high-intent targeting across the entire customer journey, regardless of the device or platform.

To ensure seamless integration into existing workflows, the solution is available today through major demand-side platforms (DSPs), including the influential platform The Trade Desk. This direct availability allows media buyers and agencies to immediately begin testing and deploying these new predictive audiences within their campaigns.

By designing a solution that is both globally scalable and channel-agnostic, Eyeota and ShareThis are providing a tool that helps multinational brands maintain targeting consistency across fragmented international markets. The privacy-centric design is crucial for this global applicability, as it aims to navigate the patchwork of data protection laws from Europe to Asia and the Americas. This combined approach of predictive modeling and privacy-centric activation represents a significant step in the industry's ongoing effort to build a more sustainable and effective advertising ecosystem for the future.