In Episode 85 of the Digital Velocity Podcast, Erik Martinez sits down with Pat Barry, President of demystifAI and a seasoned data scientist, to tackle one of the thorniest challenges in modern marketing: how to measure and forecast performance in a world full of fragmented data.

From McDonald’s digital tracking systems to direct-to-consumer (DTC) marketing attribution puzzles, Pat shares his cross-industry experiences using AI and synthetic data to fill in gaps, build more accurate forecasts, and drive smarter decision-making. They unpack the often-misunderstood limitations of Google Analytics, the data blind spots caused by Safari, cookies, and ad blockers, and the growing role of generative AI in turning incomplete data into actionable intelligence.

Whether you're a CMO building next year’s budget or a performance marketer struggling with conflicting reports, this episode offers deep insights into:
• Why most digital data is not as accurate as you think—and how to manage it
• How synthetic data can simulate realistic scenarios for forecasting and strategy
• Ways to test AI-generated forecasts for precision using statistical models
• What every DTC brand must know about attribution, consent loss, and multi-device journeys

Tune in to learn how to use AI as your data 'time machine'—not just for insights, but for impact.

Contact Pat:
demystifAI - Company Website
LinkedIn - demystifAI
LinkedIn - personal