TransUnion, Actable Boost Models 10% With AI

As marketers race to adopt AI, new results underscore the critical role of a strong data foundation in driving real business outcomes

TransUnion (NYSE: TRU) today announced breakthrough results from a collaboration with Actable, a leader in predictive intelligence for marketers. By integrating TransUnion’s TruAudience® Marketing Solutions dataset into Actable’s machine learning models, the partnership achieved a 10% improvement in model fit for AI-driven marketing predictions.

The project focused on a win-back use case for a major retailer seeking to re-engage customers who now buy from competitors, a notoriously costly and data-scarce challenge. With TruAudience Marketing Solutions data filling critical gaps within the AI model, Actable reduced false positives by 19.5%, to improve audience targeting and enable more efficiency for high-cost marketing tactics, like catalogs and paid media.

Read the full findings in TransUnion’s What Does AI-Ready Really Mean?

“AI isn’t magic, its output is only as good as the information it’s given,” said Brian Silver, EVP of Global Marketing Solutions at TransUnion. “Garbage in, garbage out still applies. These results prove that when you start with a strong data foundation, AI can deliver meaningful lift and real ROI.”

Why Data Matters for AI
Poor data quality and fragmented identity undermine predictive performance. TransUnion’s identity graph and enrichment capabilities provide the single source of truth AI systems need—covering 98%+ of the U.S. population, with 700+ demographic attributes and 15,000+ behavioral signals.

“TruAudience data proved most powerful where knowledge gaps exist,” said Matt Greitzer, Co-Founder of Actable. “This partnership demonstrates how third-party intelligence can unlock better outcomes for marketers.”

Business Impact and Future Applications
The enhanced model enables more efficient allocation of marketing resources, particularly for expensive win-back campaigns. Beyond churn reduction, the collaboration identified promising future use cases, including:

• Site visitors with limited data
• Prospecting for new customers
• Luxury goods and brands with long buying cycles, where behavioral signals are weak

As AI adoption accelerates, marketers who invest in identity resolution, seamless connectivity, and data enrichment will be best positioned to realize its full potential.

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