Let’s face it: Programmatic curation didn't just lose its mojo—it faceplanted harder than Elon Musk's credibility at a SEC hearing. For years, the adtech evangelists—companies like Audigent, MediaMath’s Curated Marketplaces, and The Trade Desk’s Open Curate—paraded around town pitching their "curated," "premium," "fraud-free" inventory like it was cold-pressed juice at a Gwyneth Paltrow retreat. Advertisers bought the dream, happily paying premium prices because, hey, who doesn't want a clean, sophisticated deal handed to them on a silver platter?

And for a hot minute, life was good. Until it wasn't.

MediaMath, once the cool kid at the PMP lunch table, spectacularly imploded into bankruptcy, leaving Infillion rummaging through the wreckage like a bargain hunter at a T.J. Maxx clearance sale.

Audigent swiftly pivoted—because in adtech, you're either pivoting or you're dead—trading in manual PMP glamour for the less sexy but far more reliable predictive-AI hustle. And, of course, Experian swept in to buy Audigent because if there’s one constant in adtech, it's that yesterday's innovator becomes today's acquisition target.

Meanwhile, The Trade Desk’s Open Curate quietly vanished like the edit button on Twitter—quickly replaced by smarter, faster, AI-driven buying tools that don’t need "human curators" telling them what’s premium.

Yes, PMPs aren't exactly dead—but let's not kid ourselves, their glory days are behind them. Basis Technologies' latest 2025 numbers confirm it: PMP growth stands at about 13% YoY, which sounds okay until you realize it’s the adtech equivalent of Netflix adding just enough subscribers not to tank their stock. Sure, PMPs will stick around, but they're now more like vinyl records or print newspapers—great for nostalgia or niche uses, not the mainstream solution everyone once envisioned.

Meanwhile, open auctions—once the noisy, unloved cousin of programmatic—are staging a stealthy comeback, powered by next-gen AI engines that optimize faster and smarter, without the smug markup of "curated" deals. Turns out, advertisers prefer transparent algorithms to overpriced mystery boxes. Shocker, right?

Here's the thing about transparency in programmatic: everyone promises it, but few deliver—kind of like Congress promising to regulate Big Tech. The PMP model hinged entirely on offering transparent, high-quality inventory at a premium price. But as advertisers increasingly asked, “Exactly what are we paying extra for?” the answer was usually a lot of awkward silence and some vague PowerPoint slides.

The ANA’s 2024 Programmatic Benchmark Study was brutal yet clear: improvements in transparency overall, yes, but skepticism around PMP ROI remained stubbornly high. Turns out advertisers want to see actual results and not just glossy presentations that look like they were designed by unpaid interns at 2am.

Who knew?

And now, dear readers, we've reached the pinnacle of PMP absurdity—a phenomenon that industry insiders affectionately call the "FartLink Syndrome." (Yes, we've temporarily rebranded them as "FartLink" to protect the guilty—and because, let's be honest, it's way funnier.)

Here’s the story: FartLink didn’t just repackage standard inventory as "premium curated"—they served it up with an unwelcome side dish of actual malware. According to TheMediaTrust, over the past year FartLink has been inadvertently dishing out malicious goodies like GhostCat and ScamClub, effectively turning these so-called premium PMP experiences into sketchy malware distribution points.

TheMediaTrust directly confirmed to me they've repeatedly pleaded with FartLink to address the malware problem—but like asking Mark Zuckerberg to stop cloning competitor apps, the response was frustratingly slow and utterly inadequate. Eventually, TheMediaTrust threw their hands up and started advising publishers to dump FartLink entirely.

Yet despite all this, FartLink remains astonishingly persistent—still sponsoring industry events, throwing around marketing dollars, and actively trying to convince unsuspecting new clients to hop aboard their malware-infested bandwagon.

When your "premium" marketplace starts infecting your customers, you've officially crossed the line from disappointing service into full-blown, Theranos-level adtech malpractice.

Here’s the bottom line: PMPs aren’t going to vanish entirely—after all, even fax machines still exist somewhere. But the widespread fascination—the so-called PMP craze—is toast. Advertisers have caught on that paying premium prices doesn’t automatically equal premium inventory, and curated marketplaces have become the industry equivalent of overpriced bottled water: totally unnecessary and, increasingly, slightly suspicious.

So what's next? Will automation fully bury traditional curation? Are transparency and first-party data the next big things—or just another temporary bandwagon?

Stay tuned, folks, because if there's anything we know for sure, adtech always has another act coming up next.

Written by Kyle Vidasolo of Elcano

At its core, curation is about introducing value-driving assets into the programmatic supply chain to create more meaningful, efficient transactions between buyers and sellers. 

Today, more often than not, the “asset” being deployed in the supply chain is targeting data (first-party, contextual, predictive, etc.). Integrating and activating data directly within SSP’s increases match rates, fidelity and therefore scale. From the perspective of a data provider, this supply-side integration allows for more control of the data from a value, pricing and performance standpoint.  

But curation isn’t limited to applying targeting data to inventory, it is a multidimensional practice that offers so much more. Bidders are limited by QPS for decisioning and performance optimization, but curation can enable significantly stronger decisioning and allow for better performance and pricing for both advertisers and publishers, if applied properly.  

Working directly with supply gives curators access to the full bid stream and far more data to analyze, measure and leverage for targeting and optimization models. Understanding this data and refining it directs filtered bid requests that have a higher likelihood of performing to the bidder/DSP. This refined bid stream is more valuable to advertisers because it’s curated with their specific goals in mind, making them more willing to pay a premium, which in turn benefits the publishers providing these enhanced requests. 

Curation can also be used to protect advertisers against fraud and issues of brand safety. It can be applied by agencies and larger buying organizations as a form of governance, to ensure buys are being run with proper settings and inventory. It can greatly aid in the opaque world of CTV and allow buyers to ensure they are actually purchasing high-value inventory where their target audience is most engaged. It can also enable better retail and pharmaceutical media networks with accurate measurement, risk mitigation, compliance, and can be activated in a decentralized “anti-walled garden” manner unlike the networks forged in single DSP partnership. 

Despite its many applications, curation remains poorly understood across the industry. Its core promise is to deliver more value while enabling better transactions and communication between buyers and sellers. Yet, a lack of understanding and expertise has led to the rise of “false curation”, or the sale of valueless deals that include inflated margins but deliver no real benefit. It’s crucial for both buyers and sellers to remain vigilant when assessing partners and their methodology. 

At Elcano, we’re committed to building technology and automation that pushes the boundaries of what curation can achieve. AI, algorithms, and machine learning can all be applied to enhance outcomes, just as they were on the DSP side years ago. But as history has shown, technology alone isn’t enough. The most powerful curation happens when advanced tools are guided by people who understand the data, the strategy, and the goals.

Just as DSP algorithms required the guidance of savvy, well-incentivized traders, advanced curation demands the same. That’s why programmatic trade desks exist, and why consistently optimized campaigns outperform “set-it-and-forget-it” approaches that fail to meet KPIs. 

At Elcano, we understand this deeply. That’s why we’re building the most advanced curation desk in the industry, helping all parties fully harness the power of curation technology to drive better results for buyers and greater revenue yield for suppliers. 

If Part One was the funeral for the once-trendy PMP marketplace, consider Part Two its orderly estate sale. Supply-side platforms (SSPs) and demand-side platforms (DSPs)—the adtech powerhouses that spent the early 2020s heavily invested in manually curated deals—are now discreetly distancing themselves from that legacy model faster than corporate America dropped NFTs from quarterly earnings calls.

In the bustling corridors of companies like Magnite and PubMatic, terms like "seller-defined audiences (SDAs)" and "first-party data monetization" have replaced once-sacred PMP buzzwords. Magnite’s recent announcements, particularly their shift toward real-time adaptive buying and dynamic audience targeting, indicate a clear strategic direction: fewer handshake deals, more algorithm-driven results. PubMatic, similarly, has subtly emphasized the integration of first-party data solutions over manually curated inventory packages.

On the demand side, Google’s DV360 and Amazon’s DSP—two titans that historically dabbled deeply in curated PMPs—now quietly steer advertisers toward automated, AI-driven bidding. These days, Google’s pitch is less "exclusive PMP inventory" and more "let our AI do the work," which has an alluring simplicity akin to replacing your financial advisor with a high-performance ETF: less sexy perhaps, but frequently more profitable.

Why this collective pivot toward automation? To paraphrase Wall Street: it’s all about performance, stupid. Advanced algorithms like The Trade Desk’s celebrated Koa AI are proving to advertisers that smarter, faster, more scalable inventory selection beats human-curated guesswork nearly every time.

For advertisers increasingly focused on tangible, demonstrable ROI—especially under tighter budget constraints and heightened scrutiny—automated buying is more than a preference; it's becoming a necessity. The precise targeting enabled by AI-driven bidding means budgets stretch further, metrics are clearer, and CMOs get fewer uncomfortable questions during board meetings.

Manual curation, as appealingly bespoke as it may sound, suffers from human limitations—bias, inconsistency, and an inability to quickly adjust to rapidly shifting market conditions. Ask any marketer trying to manage PMP deals at scale, and they'll admit that manually curated marketplaces become unwieldy and inefficient at enterprise levels. It’s like attempting to hand-craft every product in your supply chain: charming in theory, nightmarish in practice.

Moreover, transparency issues haven’t exactly helped the cause. Brands, tired of opaque pricing structures and vague definitions of "premium," have pushed SSPs and DSPs toward clearer, algorithm-driven platforms that prioritize data-driven transparency over vague exclusivity promises.

While the phrase "seller-defined audiences" might induce yawns at your average cocktail party, in the world of digital advertising it's quickly becoming the new gold standard. SDAs empower publishers to clearly define their audiences based on robust first-party data, stripping out ambiguity and allowing buyers to purchase with precision and confidence. It’s a simple pitch: publishers provide clear definitions of their audiences, advertisers match their spend to clear outcomes. No intermediaries, no inflated pricing—just straightforward transactions. It’s less romantic, certainly, but significantly more practical.

Magnite, for example, touts SDAs as generating two to three times the revenue for publishers compared to traditional PMPs. Why wouldn’t SSPs jump enthusiastically onto this clearer, simpler—and notably more profitable—bandwagon?

The great pivot toward automation underscores a fundamental truth: advertisers and publishers alike value transparency, scalability, and performance more than carefully curated promises. While traditional curated marketplaces aren’t entirely extinct—certain niches, as we’ll see in later parts of this series, still find value in them—the bulk of the industry is steadily marching toward algorithmic solutions.

This shift might lack the charm of human curation, but charm rarely improves quarterly earnings. Automation, driven by AI, offers measurable, repeatable, and increasingly undeniable advantages. For SSPs and DSPs, it's simply good business sense to follow where the data leads.

Hey friends, welcome back to the ongoing saga of programmatic advertising’s identity crisis. Today we zoom in on Audigent, a company that’s mastering the art of the pivot—like Madonna in the ’90s, but with slightly fewer dance moves and significantly more acronyms.

Not long ago, Audigent was adtech’s darling, known mostly for hand-crafted PMP deals—a strategy as artisanal as an overpriced Brooklyn latte. But when manual curation went from cool to quaint faster than you could say "AI optimization," Audigent decided nostalgia wasn’t exactly a viable business strategy. They smartly pivoted toward AI-driven predictive audiences, a more pragmatic, scalable, and—let's face it—far less headache-inducing approach.

This shift might sound like just another jargon-filled shuffle, but here’s the bottom line: automation scales, algorithms sell, and humans...well, humans mostly slow things down. Audigent bet on machines over manual deals and, by most accounts, they placed the right bet.

Then things got really interesting. Early 2025 brought us Experian’s roughly $200 million acquisition of Audigent—not as a lifeline, mind you, but as part of a very deliberate play to dominate the cookieless future. See, the narrative everyone believed was that cookies were toast and offline data was about to become the advertising gold standard. Audigent, with its shiny new predictive-audience tools and sophisticated identity stitching, was exactly the kind of company Experian wanted in its pocket.

Of course, as of April 2025, Google Chrome threw everyone a curveball—delaying cookie deprecation yet again, like the guest who keeps saying goodbye at the party but somehow never leaves. Still, the delay hasn’t fundamentally changed the direction the market was already sprinting toward. Cookies might be hanging around, but advertisers have already tasted offline data, and let’s be honest: it's richer, more stable, and a whole lot more future-proof.

Almost immediately following the acquisition, Experian went about tidying house. Audigent’s legacy PMP business—the curated marketplace products that once defined the brand—got quietly phased out. Experian didn't buy Audigent for its curated charm or bespoke deals; it wanted the technology to marry offline consumer data (think credit scores, auto loans, and retail purchasing histories) to real-time online targeting.

And honestly, that makes total sense. Premium-curated PMPs were glamorous, sure—but Experian didn't spend $200 million to hand-select inventory. They spent it to turn offline data into measurable, predictable advertising results.

Yes, Chrome’s cookie reprieve threw the industry a small lifeline, but make no mistake: the market has already moved on. Offline-first, privacy-compliant, identity-based targeting is the future advertisers want—and Audigent, now under Experian’s umbrella, is perfectly positioned to deliver it.

Cookies might still be on life support, but the offline-data gold rush is in full swing. Advertisers have already learned the lesson: relying on third-party cookies is like betting your retirement on NFTs—tempting, risky, and inevitably disappointing.

Today’s Audigent is a vastly different animal. Forget hand-picked inventory packages; instead, picture dynamic, adaptive deals driven by AI and Experian’s deep offline data reservoirs. It’s less “bespoke hipster shop” and more “high-tech assembly line”—efficient, profitable, and easily scalable.

It might lack the glamour of the curation craze, but advertisers (and their CFOs) aren’t complaining.

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🤖 Future-Proof Your Strategy: Algorithms, AI, and first-party data aren't coming—they’re here, and they’re hungry. Our expert breakdown on Seller-Defined Audiences (SDAs) and AI-powered curation isn't just smart—it’s actionable. Stop chasing your tail; let our insights help you lead the pack.

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