Podcast episode

The Hardest KPI In Advertising

by Ken Rona ·July 29, 2026 ·AdExchanger Talks

ctv identity measurement political-advertising programmatic

TL;DR

Allison Schiff interviews Mark Jablonowski, CEO of DSPolitical, a DSP and ad platform built exclusively for Democratic campaigns and progressive causes. The episode covers why political advertisers have operated in a post-cookie world for years, how CTV is reshaping political ad spend, and the disinformation threat that Jablonowski argues dwarfs the AI deep-fake panic in paid media. Ad-tech practitioners will find the episode useful for its applied lessons on audience-first targeting, exclusion logic, and first-party data activation — but this is a political advertising niche episode with limited direct bearing on mainstream programmatic strategy.

What was covered

Political ad spend explosion: Host Allison Schiff cited Ad Impact figures projecting $11.6 billion in spending during the 2026 midterms, surpassing both the 2022 midterm record ($8.9 billion) and the 2024 presidential cycle ($11.2 billion). Mark Jablonowski attributed the surge to Citizens United, a new Supreme Court ruling allowing more coordinated party-committee spending, and structural polarization he traces to CNN's 1980 launch of 24-hour news.
DSPolitical's architecture: Jablonowski described running three separate bidders simultaneously on every campaign to maximize reach into matched offline (voter-file) audiences, with centralized reporting stitching it together — a deliberate over-engineering he argues is justified by the binary, time-constrained nature of elections.
CTV growth and persistent linear mindset: CTV is projected to generate roughly $2.7 billion in political ad spending this cycle. DS Political has focused on CTV since 2018. Jablonowski noted a DSPolitical partnership with FreeWheel specifically for CTV voter targeting. Despite CTV growth, broadcast TV is still expected to take nearly half of all political ad spending, because "no political consultant has ever gotten fired for buying a thousand points of TV."
Post-cookie as default operating mode: DSPolitical moved away from cookie-based targeting in late 2016 — before cookie deprecation entered mainstream ad-tech conversation — because voter-file matching required more durable identity solutions. Jablonowski noted the company had actually launched in 2011 as "home of the political cookie" before pivoting.
AI and disinformation: Jablonowski discussed specific examples of AI-generated political content — a fake Kamala Harris radio spot and deepfakes of Congressional candidate James Tellerico — but argued in a Newsweek op-ed that organic disinformation on social platforms, now with gutted trust-and-safety teams, is a bigger structural threat than disclosed paid-media AI abuse.
Lessons for brand marketers: Jablonowski outlined three transferable practices from political campaigns: (1) audience-first planning starting from voter-file data rather than channels; (2) aggressive exclusion logic — suppressing already-converted or unreachable audiences, including real-time feeds scrubbing voters who have already cast ballots; (3) building predictive models on first-party CRM/CDP data validated with randomized control trials rather than relying on vendor-defined audiences.

Notable claims & predictions

Mark Jablonowski: "We literally were the first folks to bring the national voter file and match it against online cookie identifiers" — positioning DSPolitical as the originator of voter-file-to-digital identity matching, a significant origin claim in the political ad-tech space.
Mark Jablonowski: "We have data feeds that are updated daily… anytime someone has voted it flows through the system and we're not going to be proactively targeting them" — real-time early-vote suppression as a standard operational practice, not a novel experiment.
Mark Jablonowski on CTV waste: Political advertisers are "using CTV as a broadcast means" — buying entire congressional districts rather than applying the precise audience segmentation CTV enables, effectively wasting the medium's targeting advantage.
Mark Jablonowski on AI and measurement: "AI [will] help… creating more accessibility into custom audiences and custom scoring and reducing the barrier to entry" for first-party data activation — but hedged that trust in generative AI outputs needs to be established before campaigns put real dollars behind it.
Mark Jablonowski on disinformation: Platforms have "fired, reduced, [and] even tried to say we were wrong" on trust-and-safety — and the organic disinformation ecosystem now operates with no disclosure rules, no ad archive requirements, and algorithmic amplification incentives that paid political ads do not face.

Fact check

Allison Schiff's ad-spend figures ($11.6B midterms, $8.9B 2022, $11.2B 2024 presidential): Sourced to Ad Impact, a recognized political ad-tracking firm. These figures are in a plausible range and consistent with widely reported estimates, but specific final tallies vary by methodology across Ad Impact, AdImpact, and Kantar. Described accurately as projections, not audited figures. Unverified at this precise level but not implausible.
Jablonowski's "first to match voter file to online cookie identifiers" claim: This is a competitive origin claim that is unverifiable from public record. Multiple firms (including NationBuilder, Data Trust on the Republican side, and early iterations of TargetSmart) were active in digital voter-file matching around the same period (2011–2013). Jablonowski is clearly talking his own book here — his company's founding narrative depends on this primacy claim. Take with appropriate skepticism.
CNN launch date of June 1, 1980: Standard historical fact, correct.
Citizens United: Correctly described as the Supreme Court ruling enabling unlimited independent expenditure (super PAC) spending. Jablonowski also references a newer ruling allowing more party-committee coordination with hard-money campaigns — this appears to reference Federal Election Commission v. National Republican Senatorial Committee (2024 or 2025 term). The specific ruling and its precise scope are unverified in the transcript and listeners should not treat Jablonowski's characterization of it as legal authority without independent confirmation.

Why this matters for ad-tech operators

CTV targeting maturity gap is real and measurable: Jablonowski's observation that even well-funded political campaigns default to district-wide CTV buys — ignoring the data-layering advantage — is a signal to CTV SSPs and DSPs that education and workflow tooling around audience-based CTV buying remains an unsolved commercial problem, not just a political one.
Real-time conversion suppression as a product opportunity: The daily voter-early-ballot suppression workflow Jablonowski describes is a more sophisticated version of the post-conversion audience exclusion that most brand programmatic still handles poorly. Any identity or clean-room vendor (LiveRamp, InfoSum, Snowflake) with real-time data pipeline capabilities has a clear upsell story here for high-velocity brand campaigns (retail, insurance, finance).
First-party data activation gap: Jablonowski's observation that brand marketers are routinely sold pre-packaged vendor audiences rather than activating their own CRM/CDP data against custom predictive models is consistent with broader industry critique. Measurement and attribution vendors (VideoAmp, iSpot) and clean-room providers should note that the "randomized control trial" culture political campaigns use is the standard brands aspire to but rarely deploy at scale.
Impact on mainstream ad-tech is low and indirect. This episode is primarily useful as a niche case study in audience-first discipline and identity infrastructure resilience — not as a signal about market structure, M&A, pricing, or regulatory shifts in the broader programmatic ecosystem.

Full analysis

Political advertising has run in a post-cookie world for a decade, and Mark Jablonowski, CEO of DSPolitical, spent this AdExchanger Talks episode with Allison Schiff explaining how. The practical question for the rest of us: are the disciplines political shops built out of necessity, audience-first targeting, aggressive exclusion, and RCT-validated first-party models, worth stealing for brand programmatic? And is the disinformation threat Jablonowski flags a real operator problem or a policy debate we can ignore?

This is a Type 2 situation. Nothing here forces a decision, and nothing here is hard to reverse. The forcing function is the 2026 midterms, with AdImpact projecting $11.6 billion in political spend, past the 2022 midterm record of $8.9 billion and even the 2024 presidential cycle's $11.2 billion. That money moves through the same CTV inventory and identity plumbing brands use. So the spillover is worth understanding even if the direct impact is low.

The council

The Market Analyst. Follow the $2.7 billion of CTV political spend this cycle. Jablonowski says campaigns buy CTV like it's broadcast, entire congressional districts, no audience layering. That's a district-wide buy on inventory sold at a premium for precision. For SSPs and CTV publishers, that's fine in the short run: dumb money at high CPMs is still money. But it tells you the audience-based CTV buying that FreeWheel, Magnite, and the CTV DSPs keep pitching still isn't landing, even with buyers who have the best voter data on earth and a binary win-or-lose incentive. In plain terms: if the most motivated buyers in advertising can't be bothered to use CTV's targeting, the workflow is too hard, not the buyer too lazy.

The Skeptic. The load-bearing claim is that political discipline transfers to brands. It mostly doesn't, and the reason is the incentive, not the tooling. Campaigns run RCTs and scrub converted voters daily because an election is one day, one outcome, and the data (who voted) arrives clean and fast. Brands have no election day, no voter file, and no clean signal that a customer "converted" and should be suppressed. Jablonowski's own origin claim, first to match the national voter file to online cookies, is unverifiable and self-serving; TargetSmart and Data Trust were in the same lane. Take the man's book with salt. The methods are real. The idea they port cleanly to a retailer's always-on campaign is the oversell.

The Operator. Two things here actually work on a Tuesday morning. First, real-time conversion suppression. Jablonowski's daily feed that stops targeting voters once they've cast a ballot is the grown-up version of the post-conversion exclusion most brand programmatic still botches, retargeting people who bought the thing three days ago. If you run high-velocity campaigns in retail, insurance, or finance, a real-time suppression feed is a concrete build worth scoping. Second, exclusion logic as a first-class lever, not an afterthought. The catch: the plumbing is real work. DSPolitical runs three separate bidders per campaign for match rate. That's expensive over-engineering justified only by binary election stakes. Don't copy that part.

The Customer / End User. For the brand marketer being sold pre-packaged vendor audiences, the useful message is that the campaigns spending billions build their own models on their own data and validate with control tests. That's the standard brands claim to want and rarely deploy. The honest read: they don't deploy it because their CRM is messier than a voter file and their org isn't structured to run experiments. The gap isn't knowledge. It's data quality and organizational patience, and no vendor deck fixes either.

The Pre-Mortem. Say the disinformation thread gets ignored and bites in 2027. Jablonowski's argument is that organic disinformation on platforms with gutted trust-and-safety teams dwarfs the AI deepfake panic in paid media, because organic content faces no disclosure rules, no ad archive, and algorithmic amplification. The warning sign is already flashing: bot-detection startup Spur just raised $200 million from Insight Partners, founded by two ex-Defense engineers in 2017. Capital is flowing to bot and disinformation infrastructure. If brand-safety vendors keep fighting the last war on deepfake creative in paid inventory while the organic bot problem swamps the environment their ads sit next to, they'll be selling the wrong product into 2027.

Where they part ways

The Market Analyst sees a real commercial gap in audience-based CTV; the Skeptic says the gap persists because the incentive to close it is weak even for the most motivated buyers, so don't hold your breath for tooling to fix it.

The Operator wants to steal real-time suppression; the Customer says most brands can't feed it clean enough data to matter. That tension is the whole "does political transfer to brand" question in miniature.

What it hinges on

The transfer question turns on one thing: whether a brand has a fast, clean conversion signal and the org to act on it. Political campaigns have that by nature. Most brands don't. Where a brand does have it, retail with loyalty data, subscriptions with a hard signup event, the suppression and exclusion playbook is worth building. Everywhere else it's aspiration.

On market structure, M&A, and pricing in mainstream programmatic, this episode moves nothing. It's a niche case study. Say that plainly. The one thread with legs beyond politics is the money moving toward bot and disinformation detection, and that's a real signal because the capital is already committed.

No high-conviction prediction this week.

The episode is a niche political case study. The one forward-looking thread with real evidence, capital flowing to bot-detection infrastructure like Spur's $200 million raise, isn't what the episode is actually about, and the transfer-to-brand and CTV-adoption threads are too slow-moving to pin a dated, falsifiable call on without manufacturing false precision.

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