Adtech spent a decade treating third-party cookies like a geological fact. Not a product. Not a policy choice. A law of nature. Something you could lean on, build around, and ignore the hairline cracks creeping up the walls.

Then privacy showed up like a building inspector with a clipboard, tapped the foundation twice, and suddenly the whole industry started whispering: Wait. We can’t live here anymore?

Cue the surprise. The LinkedIn op-eds. The emergency panels. The sudden reverence for “first-party strategy,” spoken the way people talk about kale after a bad doctor’s appointment.

Except this wasn’t a surprise. It was denial with a business model.

On The ADOTAT Show, you put two people in the room who didn’t pretend otherwise. And what followed wasn’t panic. It was something far more damning: recognition.

Nobody buys a seatbelt because they love seatbelts. You buy it because you like having a face.

That’s the frame Amol Waishampayan and David Regn have been operating in for years, long before “cookie deprecation” became a sponsored conference track. As you put it, they’ve been “preaching first-party identity the way some rabbis preach forgiveness, relentless, unbothered, and occasionally judgmental.”

And the industry is only now acting shocked, “like someone admitted the tooth fairy stopped making house calls around the time GDPR became a full-time lifestyle.”

Amol was blunt about it. Back in 2018, this wasn’t prophecy cosplay. It was basic survival thinking.

He said they started with two truths:

So instead of optimizing for whatever happened to work right now, they challenged themselves to build something “more resilient to signal loss,” something that wouldn’t collapse the moment the environment shifted.

That’s not trend chasing. That’s building a seatbelt while everyone else is arguing about how fast the car should go.

This is where the conversation quietly demolished a decade of adtech mythology.

David didn’t say third-party data is useless. He said something much more dangerous: it’s directional. Helpful for hints. Fine for context. Terrible for accountability.

“There’s a lot of companies that spend billions of dollars putting together third-party data sets,” he said, and depending on the use case, they can be useful. But the real problem they were trying to solve wasn’t abstract targeting. It was concrete reality.

Most of their clients don’t live entirely online. They start digital, then transact offline. Cars get sold. Services get booked. Inventory moves. And if your identity system can’t reconcile that journey with high confidence, all you’re really doing is storytelling with charts.

That’s why David pushed early on for household-level identity with ruthless confidence thresholds. Not perfect coverage. Not universal reach. Just this: of what we can identify, let’s be 95-plus percent sure we’re right.

That single constraint changes everything. It trades scale bravado for truth. And truth is uncomfortable in an industry built on plausible deniability.

Enterprise loves to posture like it’s the center of the universe, but enterprise also has something mid-market doesn’t: time, staff, tooling, and excuses.

Mid-market has bills due on Tuesday.

That’s why this shift hits harder there, and why it matters more. When attribution breaks, when identity gets fuzzy, when outcomes can’t be proven, mid-market brands don’t get to write thought leadership about it. They get to miss payroll.

As Amol put it, marketers don’t actually care whether data is “first-party” or “third-party.” That’s vendor language. What they care about is this: “I want to pick the best audiences that are going to deliver the greatest outcomes for me.”

Everything else is implementation detail. Or theater.

And for years, the industry sold mid-market brands theater. CPM knife fights. Tool sprawl. Dashboards that looked impressive and answered nothing. Now the illusion is cracking, and suddenly everyone wants to talk about outcomes.

This is where the fault line really opens.

Performance marketing says: look at my dashboard.
Outcome marketing says: show me gross profit and incremental lift.

Those are not the same conversation. They don’t even speak the same language.

Performance marketing thrives on proxies. Clicks. Conversions. Metrics that feel actionable but stay conveniently upstream from the business ledger. Outcome marketing walks straight into the CFO’s office and asks whether any of this actually mattered.

Amol nailed the reason the industry avoided this for so long: outcomes are scary. Because once you agree to measure real business impact, you lose the ability to hide behind tooling.

As he put it later in the conversation, many companies focused on tools instead of outcomes because “they weren’t sure they were going to like the result.”

Tools don’t argue back. Outcomes do.

Here’s the thesis of the episode, whether the industry likes it or not:

Most companies love tools because tools don’t talk back. Outcomes do.

Tools let you stay busy. Outcomes force you to be honest.

For years, adtech optimized for complexity, not clarity. It built cockpits instead of compasses. It rewarded motion over direction. And when the environment changed, everyone acted like the ground betrayed them.

It didn’t. The warning signs were always there.

In Part 2, we stop speaking in polite abstractions.

We’ll get specific about:

Adtech didn’t wander into a tools-first culture. It chose it. Repeatedly. Because tools are safe and outcomes are mirrors. And mirrors are rude.

A tool can always be improved, reconfigured, renamed, or quietly relaunched with “AI-powered” bolted onto the deck. An outcome just sits there, mute and judgmental, asking the one question that empties rooms faster than a calendar invite: did this actually move the business?

That tension surfaced again and again in the conversation, especially when the discussion drifted away from dashboards and toward results that survive contact with a CFO.

The most honest explanation arrived without theatrics. The industry avoided outcomes because it wasn’t sure it was going to like the result. As Amol put it, people didn’t dare go into outcomes. Once you do, you have to live with what they reveal.

That single admission explains a decade of product strategy.

Outcomes end arguments.
Tools extend them indefinitely.

Tool-first thinking creates infinite surface area for justification: new features, new workflows, new dashboards layered on top of old dashboards. Outcome-first thinking collapses all of that into a brutal binary. Either the campaign drove incremental business impact, or it didn’t.

Even the word outcome can become another hiding place. When outcomes are defined as whatever is easiest for the vendor to produce, they stop being outcomes and become features wearing a serious expression.

ADOTAT+ INSIGHT #1:
Subscribers get the unfiltered taxonomy of “fake outcomes” versus CFO-grade outcomes, including the exact phrases vendors use when they’re trying to dodge incrementality. Once seen, it’s impossible to unsee.

Automation theater has become the industry’s favorite genre.

Everyone claims automation. Everyone claims AI. And yet much of what’s sold looks suspiciously like constant supervision, snack-soothing, and the occasional system catching fire when someone changes a setting.

David refused to make automation mystical. Automation, as he described it, is about less hands on keyboards, especially around operational delivery that isn’t key to strategic outcomes. Compliance workflows. Manual approvals. Copy-paste purgatory that burns time without creating insight.

That distinction matters because a large percentage of “AI-powered” products are still workflow automation plus probabilistic scoring. Useful sometimes. Intelligent rarely.

It was said bluntly that everyone sprinkles a little AI on everything and claims it makes it better. But if a system can’t show lift tests, error bars, and what changes in the business when it’s turned on versus off, it isn’t intelligence.

It’s a nervous intern with a nicer UI and infinite overtime.

ADOTAT+ INSIGHT #2:
The paid edition breaks down the economics behind AI-labeled tools, including why “automation” often increases vendor margins while quietly shifting labor costs back onto agencies and clients. Real examples. Real math. No vibes.

This is where the conversation quietly invalidated half the industry’s favorite metrics.

When Amol talked about outcomes, he wasn’t talking marketing outcomes. He meant actual business outcomes. SKUs sold. Gross profit on those SKUs. CFO-level outcomes.

That definition strips the paint off the walls.

Not engagement.
Not awareness.
Not brand warmth.
Not vibes.

Outcomes, in finance language, are incremental lift, contribution margin, and cash payback. They survive audits. They don’t care how elegant the deck looked.

This is why the mid-market feels the pain first. Mid-market businesses live and die every month by actual business outcomes. There’s no runway for interpretive metrics when payroll is due.

And this is where the frustration surfaced clearly: why is it still hard to track CPA and brand lift at the same time? Why do performance marketing and brand marketing live in separate universes, like rival city-states that refuse to share maps?

David’s answer wasn’t technical. It was structural. Attribution collapses when marketing is discussed without business context. Pricing. Promotions. Operations. Customer experience. Without those inputs, attribution becomes a sophisticated way to argue internally instead of a tool to decide externally.

Attribution has been promised as salvation for so long it’s started to resemble mythology.

The issue isn’t math. It’s context.

Attribution models carve up credit across touchpoints, but they rarely ask the dangerous question: what would have happened without this spend? Without that counterfactual, attribution explains sequence, not cause.

That’s why incrementality remains the real holy grail. And that’s why so many systems quietly avoid it. Incrementality doesn’t just assign credit. It revokes it.

ADOTAT+ INSIGHT #3:
Subscribers get a deep dive into why incrementality threatens entire layers of the adtech stack, including which intermediaries benefit from attribution ambiguity and which ones disappear when incrementality becomes standard.

The conversation eventually circled back to Henry Ford, not as nostalgia but as indictment. Ask customers what they want and they’ll ask for a faster horse.

Adtech has spent years building better saddles. Cleaner dashboards. Shinier identity graphs. More optimization knobs. Horse after horse, all beautifully groomed.

What’s missing is the car.

Vendors keep shipping saddles because saddles sell well in RFPs. Cars demand outcome guarantees. Cars collapse categories. Cars make certain job titles uncomfortable.

And when a real car finally shows up, the floor gives way under the saddle business.

If this piece rattled you, wait until you see what’s behind the paywall. The free version gives you the tremors. ADOTAT+ is the full earthquake.

Inside the member edition, I map out the parts nobody else will print:
which RMNs are structurally insolvent, which pillars collapse first, who’s preparing for agentic commerce, who isn’t, and why the measurement layer is about to get rewritten by machines instead of marketers.

It’s the kind of analysis holding companies wish I’d keep to myself.
And the kind indie media can only produce if readers back it.

Support independent reporting, get the unfiltered version, and stay ahead of the herd sleepwalking into the shockwave.

Stay Bold, Stay Curious, and Know More than You Did Yesterday.