AMENIA, NY — The gap between data collection and actionable insights in programmatic advertising is collapsing as artificial intelligence transforms campaign optimization from a weeks-long process into real-time decision making.
“The applications that are driving better outcomes for clients are really our trading agent,” Marion Hargett, chief revenue officer at MiQ, told Beet.TV contributor David Kaplan at the Beet Retreat Berkshires 2025. “The way that it is used is not just to deliver a better dashboard. It’s actually used to make real time optimizations to drive campaign performance in what would otherwise take us weeks to understand. And seconds.”
This acceleration represents a fundamental shift in how media buying operates, moving from reactive analysis to proactive optimization powered by AI systems that can process and act on data signals faster than human teams ever could.
Unifying 700 trillion data signals
Behind MiQ’s trading agent lies an ambitious effort to break down the data silos that have long fragmented the advertising industry. The company is working to unify what Hargett described as “over 700 trillion data signals” that brands could potentially leverage for audience targeting and campaign optimization.
“One of the things we’re looking to help do at MiQ is to be able to unify the over 700 trillion data signals that one could otherwise take advantage of,” Hargett said. This massive data integration challenge reflects the complexity of the media landscape, where consumer behavior spans multiple platforms, devices, and touchpoints.
The ad tech platform is focused on creating unified measurement and activation capabilities across channels and partners rather than forcing brands to work within individual ecosystem silos. “We’re seeing a lot of success in being able to bring those pieces together so that you have a way to measure and activate against audiences across platforms,” she said.
Moving beyond AI experimentation
While much of the industry continues to treat artificial intelligence as an experimental technology, Hargett takes a more pragmatic view of its current state and future development. Rather than looking at strictly at the present and the near-future of AI, Hargett stressed applying a wide-angle lens on the role of AI as part of the evolution of machine learning tools that have powered advertising technology for years.
Still, she acknowledged that the industry remains in early stages of AI adoption. “I don’t think we’re at the end of the journey,” she said. “We’re probably in the second or third inning.”
Platform-agnostic approach
Hargett’s background includes a stint at The Trade Desk, which shaped her understanding of the limitations of single-platform approaches. Her interest in trying to solve those issues is in part what led her to join MiQ, as she was attracted by what she described as the company’s platform-agnostic philosophy.
“Having come from a really large DSP, I found that there was only so much that we could accomplish in that environment,” Hargett said. “Brands were looking for ways to be able to optimize across multiple environments.”
This cross-platform capability becomes increasingly important as brands seek to reduce waste and improve efficiency across fragmented media landscapes. Rather than optimizing within individual platforms, MiQ’s approach allows for holistic audience creation and unified optimization strategies.
Measuring real impact
Despite the sophistication of available data and targeting technologies, Hargett notes that improved precision means little without clear measurement frameworks. She advocates for establishing specific key performance indicators before deploying advanced targeting capabilities.
“It really starts with a clear plan and a clear set of KPIs that the brand or agency is trying to achieve,” Hargett said. “Then, based on that insight, you can drive to a more desirable outcome.”
The ultimate test, in Hargett’s view, remains closed-loop attribution that connects media investment to actual sales results. “That’s how all the CMOs are being measured, and that’s how all the brands are being measured,” she noted. “And ultimately, if you’re driving increased sales performance, you’re delivering on an outcome that the brand is looking to achieve.”
The efficiency imperative
Hargett’s perspective reflects broader industry pressure to demonstrate clear return on investment from increasingly complex advertising technology stacks. As brands face mounting pressure to prove marketing effectiveness, the demand for partners who can optimize across multiple environments while reducing waste continues to grow.
“Most brands and agencies at their core are looking to drive efficiencies, and the way to do that is to continue to test and learn,” Hargett said.
