Let’s start with an uncomfortable truth: Marketing measurement was never good.
Sure, you had access to shiny dashboards, attribution models that made you look good (but also made you sweat), and vendors sending you spreadsheets filled with confidence intervals and confusing acronyms.

But behind the scenes? Smoke and mirrors. Flimsy assumptions. A whole lot of correlation dressed up as causation.

And now? It’s worse.

Privacy killed the last illusion of accuracy. IDFA deprecation, cookie loss, and user-level data restrictions didn't break measurement—they just revealed how broken it always was.

The correlation catastrophe

We’ve been treating correlation like it's gospel. A spike in sales coincides with an ad campaign? Must be the campaign. A drop in installs after pausing TikTok ads? TikTok must be gold!
Wrong. 

Real-world behavior is messy. Seasonality, promotions, virality, word of mouth, competitor actions, PR - all of these influence performance, yet most measurement tools conveniently ignore them.

Attribution models weren’t designed to understand causality. They were built to assign credit. And when you feed them bad data, guess what you get?
Here – you should be adjusting your attribution with an “incrementality factor” (IF). 
Some will say that the only way to measure incrementality scientifically is to run an experiment – and they are correct – But an experiment run in a laboratory is not the same as one running in reality.

Can you run an experiment while: 

• Making sure nothing drastic happens while you run your test?
• Keeping the weather roughly the same throughout the test?
• Not doing any promotions
• Not making any other changes
• Hoping your competitors also don’t make sudden moves so that it doesn’t interfere with your test?
• Can you holdout the same DMAs across all of your channels, including those who a) don’t support DMA, and b) you don’t have access to DMA data since neither Google Analytics, nor any of the MMPs provide you with this data!

If you answered no to any of these – then stop kidding yourself that Experiments are a “scientific way” to measure incrementality.

Bad data in, bad decisions out.

That’s a nice way of saying: Garbage in – garbage out.

We’ve seen marketers double down on performance networks because the attribution model said so, only to realize later that those platforms were just riding the wave, not creating it.
No one seems to use the term Fraud anymore. Maybe that’s because attribution fraud has been completely normalized. i.e. “everyone’s doing it”.

Let’s be clear: correlation is cheap. It’s easy to produce and easy to misread. And when you're spending millions on media, you can't afford to misread anything.

Measurement was broken before privacy killed it

The truth is: measurement was already failing us before privacy changes came into the picture. It just had better PR.

We lived in a fantasy world of IDFAs, pixels, and UTMs, pretending we had certainty. But the illusion was always delicate. Once browser policies shifted and mobile platforms locked down IDs, the data house of cards collapsed.

Retargeting audiences? Gone. Let’s just target everyone buying cheap inventory and call it “retargeting”. 
Multi-touch attribution? Toast. Let’s just spam clicks and we’ll catch something.

What marketers were left with was a mix of hunches and hacked-together spreadsheets. The tools we depended on simply weren’t built for a privacy-first world—or, frankly, for reality.
Most tools were retroactive. Most methodologies were reactive. And most CMOs had to choose between "data-driven" decisions that felt wrong or gut decisions that would never pass procurement scrutiny.

Now, the walls have come down. There's no hiding. The marketers left standing are the ones who realized that measurement isn’t about assigning credit - it's about uncovering truth.

Always-On Incrementality: Clarity in the chaos

Incrementality isn’t new. But historically, it was treated like a science experiment: stop a campaign, run a geo test, wait a month, hope for significance, pray for budget to restart it.
That doesn’t work anymore. Or, to be blunt: it never really did.

Always-on incrementality is different. It lives inside your live data, measuring the actual impact of your marketing activities, without needing user-level tracking or disruptive tests.
It doesn’t ask, “Where did the user click before converting?” It asks, “Would this conversion have happened anyway?”

See the difference?

Always-on incrementality separates signal from noise. It shows you which campaigns are truly driving outcomes, and which are just expensive passengers on the ride.

Why clients make the switch 

CMOs and performance marketers who switch to always-on incrementality report three game-changing benefits:

1. Confidence in Budget Decisions
Instead of relying on guesswork or legacy models, they know where to cut spend without losing performance - and where to invest more for true growth.
This level of clarity also helps marketing leaders push back when finance challenges marketing investments. With incrementality data, CMOs can finally move from a defensive posture to an offensive one, showing impact clearly and persuasively.

2. Alignment Across the Org
Imagine being in a meeting room and not having to defend your media spend based on sketchy last-click numbers. Instead, you bring a clear view of what's truly driving business growth. That builds credibility, not just with your team, but with your entire executive leadership.
When marketing, finance, and product all speak the same language decisions move faster. Less argument, more action.

3. Freedom from Fragile Data
No IDFA? No problem. Always-on incrementality works without user-level data, so it's future-proofed against privacy changes. No more late-night panic over a Chrome update or iOS version change.
You’re no longer chained to Facebook’s black box or Google’s attribution logic. You own the measurement layer, and that independence is a competitive advantage.

Bonus Question: What happens when you don’t change?

Let’s flip the question: what happens if you stick with the status quo?

• You’ll keep overpaying for media that looks good on paper but does nothing in reality.
• You’ll keep pausing the campaigns that actually work because they don't get the credit they deserve.
• You’ll keep getting grilled by finance and stuck in circular debates with agencies.

And worst of all? You’ll continue making decisions in the dark. You’ll optimize for optics, not outcomes.

The future is measured differently

Marketing isn't going backwards. You can't put the privacy genie back in the bottle. You can't keep spending like it's 2018 and expect your CFO not to notice.
But you can measure smarter.

You can switch to a system that respects reality. One that doesn’t need to pretend causation from correlation. One that doesn’t ask you to pause your best campaign just to run a test.

Always-on incrementality doesn’t just measure impact. It builds trust. It empowers marketers. And most importantly?

It lets you stop guessing and start knowing.

Ready to Join the Movement?

If you're still clinging to outdated models, ask yourself: what is that really costing you?
Spoiler alert: it's more than just wasted ad spend. It’s trust. It’s alignment. It’s velocity.

And your competitors who are measuring incrementally? They’re already winning.

Your team deserves better. Your business demands better.

Stop Guessing. Start Knowing.