TransUnion recently published a press release outlining results from a collaboration with Actable focused on improving AI-driven marketing performance through stronger data and predictive modeling.
According to TransUnion, the partnership combined TransUnion’s TruAudience Marketing Solutions data with Actable’s machine learning models to improve predictive accuracy in a win-back use case for a major retailer. TransUnion reported a 10 percent lift in predictive model fit as a result of this work.
“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.”
The announcement reinforces a broader point that many marketing teams are confronting as they adopt AI. Predictive performance depends not only on algorithms, but on the quality and structure of the data feeding those models. Actable’s role in the collaboration centered on applying advanced analytics to translate enriched data into more effective predictions.
TransUnion also noted improvements in targeting efficiency for high-cost channels and pointed to additional AI-driven use cases where stronger data foundations can unlock better results.
This summary reflects only what TransUnion shared publicly. For full context, methodology, and results, read the complete announcement directly from TransUnion.
