Smaller teams can now compete in premium advertising spaces thanks to AI-driven tools that simplify campaign management like AdLib DSP.
Marketing mix modeling tools are helping brands navigate walled gardens by providing a holistic view of ad performance.
Major streaming platforms like Netflix and Prime Video remain underutilized by advertisers, despite offering valuable engagement data.
AI is giving smaller teams access to the kind of advertising firepower that once took a Madison Avenue war chest. And with smarter tools stitching signals across walled gardens, those walls aren’t as tall as they look.
Mike Hauptman is the Founder and CEO of AdLib DSP, a company that helps brands automate creative and optimize media performance across digital platforms. He’s focused on turning complex campaigns into accessible, measurable, and scalable systems.
Democratizing the buy: “We’re seeing a clear shift. Smaller teams and emerging brands can finally play in arenas that were once gated behind six‑ or seven‑figure spends,” explains Hauptman. TikTok, Meta, Google, Spotify, and Pinterest have all invested heavily in intuitive, AI-powered self-serve ad tools. It’s no longer just Fortune 500 brands playing on premium programmatic and CTV channels.
“Mid‑market DTC or niche brands can now secure premium CTV, programmatic display, even DOOH placements without assembling an army of specialists,” says Hauptman. Campaign cycles that once dragged across weeks can now be collapsed into days or hours. “Creative variants—whether for mobile video or audio—can be auto‑generated and A/B‑tested on the fly.”
Beyond speed, these tools deliver smarter spend. “AI‑driven budget allocation steers spend toward the highest‑performing formats in near‑real time, so you squeeze more value out of every dollar,” says Hauptman. Channels that once felt off-limits—too complex or costly—are becoming as easy to access as Facebook Ads.
Breaking down walls: Platforms are becoming more closed, not less. But that doesn’t mean performance measurement is dead. “While each platform tightens its data and measurement controls, a new generation of self‑serve bridges and analytics partners is quietly emerging,” Hauptman says.
The walls are real. “Proprietary IDs and siloed dashboards on Meta, Google, Netflix, and Prime Video can leave you unsure which touchpoints really drove lift.” But marketing mix modeling (MMM) tools and signal-stitching platforms are changing the equation.
“With a holistic view, you can identify over‑indexed segments and redeploy budgets to complementary channels—say, a DOOH buy or ad‑supported Netflix—to reach fresh audiences.” By layering MMM insights over closed-loop metrics and unifying spend and performance data through a single pane, brands can reconstruct a full-funnel picture and optimize for true incremental lift.
AI collab: AdLib’s approach to AI is intentionally collaborative. “We build our AI modules to free your team from rote tasks rather than supplant them entirely,” says Hauptman. Optimization suggestions and creative variants are presented as recommendations, not final calls. “The system flags budget shifts or creative fatigue, recommending actions rather than performing them autonomously—so you stay in the driver’s seat,” Hauptman explains.
More scenario modeling and predictive bidding is coming, but Hauptman sees strategy staying firmly in human hands: “Teams can focus on big‑picture growth instead of dashboard drudgery.”
The untapped stream: Despite their reach and innovation, major streamers remain underutilized by many advertisers. Hauptman sees that as a mistake.”Netflix’s ad‑supported plan and Prime Video’s FAST channels come with viewership data and engagement signals that rival CTV networks—yet many brands still treat them as ‘brand only’ channels,” he says.Â
He’s also watching the commerce angle. “Prime Video increasingly surfaces shoppable ads tied to Amazon’s wider retail ecosystem, and Netflix is rumored to test similar ‘in‑app’ product showcases,” Hauptman says. These tie-ins offer more than awareness. “By syncing ads to e‑commerce events, you can measure downstream purchase lift far more cleanly than through panel data alone.”
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