SAN JUAN, Puerto Rico — Controlling supply provides access to real-time user intent and behavioral patterns, while optimization approaches rely on cobbled-together attribution data that limits pre-bid decision-making effectiveness.
“When you control the supply, you’re not acting after the fact. You’re not cobbling together that intent based off of cookies or other attribution,” Mike Freides, senior director of Business Development — West at Infolinks Media, told Beet.TV contributor David Kaplan at the Beet Retreat San Juan. “When you own and control the supply, you’re optimizing in real time based on that user’s past behavioral action, but also you know the real time intent and you only get that when you own and control the supply.”
Supply path optimization eliminates chaos and inefficiencies from open market curation while providing transparency previously unavailable through direct supply partner relationships.
SPO removes programmatic inefficiencies
Supply path optimization (SPO) addresses market chaos by eliminating duplicate buying, extra hops, and duplicative fees that characterized early open market curation, creating efficiency gains through direct supply partnerships.
“Open market curation was great initially to give the industry access to inventory. What SPO has done is eliminate a lot of the chaos that we’ve seen in those inefficiencies,” Freides said. “By moving to an SPO model and working more directly with the supply partners, we do away with that, but we also now have the transparency that we didn’t before.”
Cross-environment mastery required
Consistent SPO application across mobile web, app, and connected TV environments requires technical mastery of different identifiers and user engagement patterns rather than one-size-fits-all approaches.
“You really have to have mastery of those identifiers in those different environments as you move across the programmatic pipes,” Freides said. “The notion of it being a one size fits all just doesn’t work because these users act and engage differently in each of those environments.”
Mapping user experience flow across environments enables inventory sourcing that follows user journeys effectively.
Clean rooms support analysis, not execution
Clean rooms provide valuable industry impact for post-campaign analysis but lack capability for media plan execution or pre-bid optimization, though convergence opportunities emerge through AI-powered buying decisions.
“Clean rooms are obviously huge impact on our industry, but they’re not an environment to execute on media plans. They’re great for analysis after the fact, but they’re not the environment to be executing on pre-bid,” Freides said.
Future applications will leverage clean room data combined with real-time supply proximity intent for more intelligent purchasing decisions.
AI shifts from analysis to execution
Artificial intelligence development will focus on real-time pre-bid decision-making rather than post-campaign analysis, moving beyond chatbot applications toward execution-focused implementation that impacts active buying decisions.
Clean room data combined with supply proximity will enable more intelligent purchasing, though the emphasis shifts toward operational integration during campaigns rather than retrospective evaluation.
“It’s going to be using AI to help make more real time pre-bid decisions than it is analyzing after the fact,” Freides said. “Not from just a chatbot or trying to cobble together some intent and analyzing data. It’s going to be moving it to the forefront of execution.”
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