Predactiv's New AI Tool Aims to Democratize Data Monetization

PALO ALTO, CA – March 03, 2026 – Data technology firm Predactiv today launched a new Lookalike Modeling feature within its data platform, a move aimed at simplifying how businesses transform their proprietary data into scalable advertising audiences and new commercial products. The new capability promises a 'push button' solution to what has traditionally been a resource-intensive process, potentially lowering the barrier for companies to unlock value from their first-party data assets.

The feature allows organizations to securely upload their own data—such as customer lists or transaction records—into The Predactiv Data Platform. The platform’s AI then analyzes this 'seed' data to identify and build a much larger audience of new individuals who share similar characteristics and behaviors. These newly created 'lookalike' audiences can be activated across various digital advertising channels, from online display ads to Connected TV (CTV), with the goal of improving campaign performance and increasing conversions.

This launch enters a highly competitive market where the effective use of first-party data is paramount, especially as third-party cookies are phased out. Predactiv, which emerged from the data-pioneering firm ShareThis, is positioning this tool as an infrastructure layer for any company looking to become a more sophisticated data player.

Democratizing Advanced Data Science

For many organizations, the challenge isn't a lack of data, but a lack of resources to interpret and activate it. Building predictive models traditionally requires a dedicated team of data scientists and engineers, a significant investment that puts such capabilities out of reach for many small to medium-sized businesses. Predactiv aims to level this playing field.

"Many organizations sit on incredibly valuable data, but lack a practical way to turn it into scalable products," said Dana Hayes, Jr., CEO of Predactiv, in the company's announcement. "With Lookalike Modeling, we're removing that barrier. Predactiv gives data providers and data-rich organizations a faster, more accessible path to transform their owned data into expanded, high-value audiences, and ultimately into new, recurring revenue streams."

The platform guides users through a simplified workflow: securely onboarding their seed data, letting the platform’s predictive intelligence automatically enrich it and build the model, and finally, generating a vastly expanded audience ready for activation. This abstraction of complexity is central to the product's appeal, promising the power of data science without the need for a Ph.D. to operate it.

The New Gold Rush: Unlocking Hidden Revenue

The economic implications of this technology are significant. The feature is not just about improving marketing efficiency; it's about creating entirely new commercial opportunities. By enabling companies to easily package and scale their data insights, Predactiv is facilitating a shift from being a 'data owner' to a 'data product company.'

Instead of selling raw data feeds, which have limited application and raise privacy concerns, data providers can now offer sophisticated, pre-built audience products. These modeled audiences are more valuable to advertisers because they are larger, more targeted, and ready for immediate use in campaigns. This move up the value chain represents a direct path to monetization, allowing data-rich organizations to generate incremental, recurring revenue from assets they already possess.

This aligns with a broader market trend toward data monetization, where businesses are increasingly looking for ways to leverage their data as a strategic asset. By providing the tools to refine, expand, and productize data, Predactiv is effectively offering the picks and shovels for this new digital gold rush. The company's existing case studies, which show clients achieving up to a 5x return on ad spend and a 65% reduction in conversion costs using its custom audiences, suggest a strong foundation for delivering tangible financial results.

A Competitive and Evolving Adtech Landscape

Predactiv's announcement does not happen in a vacuum. The adtech space is fiercely competitive, with major players racing to offer the most effective, privacy-compliant solutions. On the same day, data collaboration giant LiveRamp also announced AI upgrades to its platform, including enhanced lookalike modeling features, signaling the intense focus on AI-driven audience expansion across the industry. Companies like Acxiom and Oracle also offer robust data management and audience-building tools.

However, Predactiv's background and technical foundation provide it with key differentiators. Having emerged from ShareThis, the company inherited a massive proprietary dataset built on real-time global digital behaviors. It further enhances this with a partnership with Affinity Solutions, integrating purchase-based deterministic data that links online behavior with offline buying habits—a powerful combination for predictive modeling.

The company’s platform is built on a sophisticated AI stack, utilizing a continuously refreshed embedding framework and large language models (LLMs) to understand data in real-time. This allows its intelligent agents to generate insights and build audiences through natural language prompts, further simplifying the user experience.

Critically, Predactiv emphasizes a privacy-first approach. The platform is SOC 2 Type II certified and designed to comply with global regulations like GDPR and CCPA. In an era of heightened consumer awareness and regulatory scrutiny, providing a secure and compliant environment for data handling is not just a feature, but a prerequisite for building trust and ensuring long-term viability.

Predactiv is currently offering the new Lookalike Modeling capability through an early access program, inviting partners to use the tool and help shape its future development. This collaborative approach, combined with the option for custom, managed service modeling, allows the company to cater to a wide range of client needs as it seeks to carve out its place in the future of the data economy.