
Episode #6
How AI Is Replacing The Media Planning Cycle | Josh Hudgins, CPO at VideoAmp
Have a question? Send us a text! Tim sits down with Josh Hudgins , Chief Product Officer at VideoAmp , to unpack how the performance media platform connects ad exposure directly to real-world outcomes — store visits, purchases, subscriber signups — and how AI is acting as a semantic layer to reinvent how that data gets interpreted, planned against, and acted on. The measurement problem is a signal-to-noise problem. Advertisers and analysts aren't starving for data — they're drowning in dashboards. VideoAmp's answer is a semantic AI layer built on top of their measurement stack that interprets the data, separates noise from signal, and surfaces the insights that actually matter — without replacing the rigorous measurement methodology underneath. 1:18 – What VideoAmp is and the core problem it solves: closing the loop between ad exposure and real-world outcomes 2:13 – How VideoAmp built its data asset: set-top boxes, smart TVs, streaming log-level data via clean rooms 6:19 – The new AI-powered reporting experience: from monolithic dashboards to interactive insight conversations The alchemy nobody expected: audience + content + platform = lift. When you can report at a creative level all the way through to outcomes across every platform simultaneously, you start finding combinations that no analyst would have predicted. A specific audience, paired with specific content, on a specific platform, driving measurable lift for a specific product. That's not a dashboard insight. That's a campaign brief. 7:54 – What the data reveals when AI interprets it: creative-level performance tied to real-world outcomes 9:30 – How the AI journey goes from insight to media plan to agentic campaign orchestration 10:25 – Why siloed channel teams are being replaced by audience-first, outcome-first structures Media planning is becoming a real-time optimization loop. The traditional cycle — annual media mix model, allocation decision, wait and see — is collapsing. VideoAmp is working with publishers on mid-flight optimization tied directly to outcomes, compressing what used to take a year into a near-real-time feedback loop. The automotive supply chain example makes the implications concrete: media exposure signals flowing back into inventory planning. 10:56 – How AI compresses the learning and response cycle from annual to near real time 11:59 – The automotive case: from dealership visits to supply chain signals, all connected to media exposure 13:21 – What it looks like when the measurement flywheel starts spinning faster Agent-to-agent integrations will make brittle API workflows obsolete. The next six months: agencies, streaming platforms, and media companies are all building AI agents — and those agents are starting to talk to each other. What used to take 12 months to integrate now takes weeks. Josh explains what that means for the pace of new capability development and why it's the most exciting technical shift he's seen. 13:48 – What agent-to-agent integrations actually are and why they replace brittle API workflows 14:27 – How different entities — buyers, sellers, platforms — are now connecting via agents 15:51 – Why AI unlocks more human time, not less: the case for focusing on connection and ideas Connect with Josh Hudgins on LinkedIn · VideoAmp Thanks to Looper Insights for sponsoring today’s show! Ready to unlock your streaming strategy edge? Head over to mystreamingvalue.com to compare CTV home screens and find out which spaces are worth the most. You’ll even learn exactly why Fox was willing to pay $22 billion for Roku. Stop guessing and start scaling—visit mystreamingvalue.com to get your free insights today!






