How Demand Side Platforms (DSPs) Are Reshaping CTV And What Publishers Need To Know


The Pub Way Podcast returns with an in-depth look at CTV advertising, focusing on demand side platforms (DSPs). Hosted by Tina Iannacchino (VP of Publisher Partnerships North America at Seedtag) and Mike Villalobos (SVP of Strategy and Commercial Operations, North America at Seedtag), Episode 13 welcomes Keith Gooberman, CEO and Co-Founder of Pontiac Intelligence, to discuss how DSPs are adapting to evolving data policies and the new opportunities CTV brings for publishers. Here we bring you all you publishers need to know about how DSPs are changing connected TV buys, why privacy remains central, and what it all means for publisher revenue.
A demand side platform (DSP) is the digital interface that enables advertisers to purchase inventory across channels (desktop, mobile, and especially CTV advertising) in a unified manner.
Historically, DSPs relied on cookie-based data for granular targeting. Now, with privacy concerns reshaping online advertising, DSPs are turning to private marketplace (PMP) deals, prioritizing direct collaboration with content owners.
Publishers stand to benefit. PMP deals typically command higher CPMs and more transparent data-sharing. As Keith observes, tomorrow’s programmatic environment will feature deeper partnerships between DSPs and content owners, creating unique revenue streams for publishers who can provide distinctive inventory or advanced targeting signals.

Global privacy regulations are forcing a move away from broad data collection. While Google’s cookie plans fluctuate, the overall direction remains privacy-first. In a CTV context, cookies are largely irrelevant, so targeting methods must evolve. DSPs are adapting by focusing on content signals, forging direct relationships with streaming services, and negotiating PMPs that bypass the open exchange.
This is good news for publishers: those who excel at packaging content and user engagement data without compromising confidentiality will be well-positioned. Although sharing log-level data can be sensitive, it often reassures advertisers that they’re buying premium inventory, encouraging greater spend.
Advertisers increasingly seek transparency. They want show-level insights (e.g., “Which program did my ad appear in?”) to confirm brand suitability and measure effectiveness. Yet publishers understandably guard their data, worried about undercutting direct deals or exposing proprietary information.
Keith explains that with a tailored DSP approach (built around PMPs) publishers can negotiate exactly what to share. This selective data release can elevate CPMs, especially when unique audience contexts or exclusive programming is on offer.
The key is clear communication: publishers who help advertisers understand the content environment can attract stronger campaign commitments.
Traditional contextual targeting (based on keywords or page categories) now faces its biggest test in CTV advertising, where video content dominates. AI tools can parse shows at a deeper level beyond mere categories, recognizing mood, dialogue, or plot themes. This refined approach offers advertisers a better sense of what’s on screen, ensuring relevant ad placements without relying on personal data.
For publishers, robust AI-driven context elevates value. If you can detail the emotional tone or specific segments of your videos, you stand out in a crowded market. DSPs want premium signals to differentiate one CTV channel from another, and sophisticated content analytics can deliver that competitive edge.

Despite Google’s shifting timeline on cookies, the days of unrestricted data collection are numbered. Many CTV environments rely on device or IP-based identifiers rather than cookies. DSPs address this by blending partial user details with broader contextual cues and PMP agreements. Publishers with strong first-party data or advanced audience insights can fill that gap, commanding higher prices if they maintain user trust.
DSP technology once revolved around open exchanges and third-party data; now it’s pivoting to direct deals, granular content analysis, and privacy-friendly user signals. Publishers who adapt to these market realities and offer a mix of audience clarity, brand safety, and strong contextual data are poised for long-term success.
Want the full story? Tune in to Episode 13, featuring Pontiac Intelligence’s Keith Gooberman, to hear firsthand how DSPs operate, where CTV advertising is headed, and how publishers can thrive in a shifting ecosystem.

Find answers to get the most out of Seedtag.
Neuro-Contextual Advertising is an evolution of contextual advertising that uses AI to understand interest, emotion, and intent within content. Instead of relying on personal data, it helps brands align advertising with the moment people are experiencing in real time.
Contextual advertising places ads based on the content a person is engaging with, rather than personal browsing history or identifiers. Neuro-Contextual approaches go beyond traditional contextual targeting by understanding audience interest, emotion, and intent.
CTV advertising refers to ads delivered through Connected TV environments, including streaming platforms and smart TV applications. It allows brands to reach audiences across premium video experiences using more contextual and privacy-first targeting approaches.
Liz is Seedtag’s proprietary Neuro-Contextual AI, designed for full-funnel advertising across premium open web, video, and CTV environments. Grounded in neuroscience, Liz understands contextual signals such as interest, emotion, and intent in a human-like way to deliver relevant advertising experiences in real time while respecting user privacy.
With consumers increasingly wary of data collection and cookies, privacy-first advertising focuses on delivering personalized and relevant ads while respecting user privacy. Neuro-Contextual advertising enables relevant advertising experiences without relying on personal data or third-party cookies.
Leveraging neuroscience principles, Liz recognizes patterns, interprets context, and responds dynamically to user interests, emotions, and intentions. This creates a more cohesive and intelligent system capable of delivering more relevant advertising experiences.