- What attribution credited
- $1.2M
- Happened anyway
- −$860K
- Incremental sales caused by marketing
- $340K
Estimated revenue that would not exist without the spend.
Confidence 92%
Verified with Mediaura Fusion Engine
Attribution Is Not Causality.
Your reports aren’t lying to you. They’re answering the wrong question. “Which ads were near the revenue?” is not “which spend caused it?” Mediaura Signal answers the second one: estimated causal impact in dollars, anchored to geo-holdout experiments where you run them, with the confidence range stated and the disagreements shown. A number you can take to the board.
23 Years
Of marketing solutions and execution
$1B+
Revenue tracked to source
3 Verticals
Built for healthcare, restaurants, and B2B
The Problem
The Wrong Question Has Four Ways of Producing Wrong Answers
Attribution counts who was standing nearby when revenue happened. That's correlation. It feels like measurement, it charts beautifully, and it collapses the moment you ask the only question a budget decision needs: what would have happened without the spend?
And even as correlation, the data underneath is quietly broken in four ways:
Tracking Decays Silently.
Tags accumulate, properties duplicate, a release ships and a pixel stops firing. Nobody notices until you've made a quarter of budget decisions on corrupted data.
Identity Fractures Across the Journey.
One customer sees an ad on their phone, researches on a laptop, calls the front desk, and walks in. Your analytics counts four strangers and credits none of them.
Platforms Grade Their Own Homework.
Google reports Google's wins. Meta reports Meta's. Add the claims together and your channels "drove" 240% of your actual revenue.
Revenue Lives Where Tracking Doesn't.
The money changes hands at the POS, in the CRM, on a phone call. Attribution that can't reach those systems optimizes toward form fills and hopes they correlate with dollars. They usually don't.
Correlation on top of broken data: that's what most marketing reporting is. There's a name for it. Attribution theater: confident numbers that win the meeting and lose the money. Mediaura Signal was built to end the genre: fix the data first, then measure cause, not proximity.
The Answers
Three Answers You've Never Gotten From Marketing
You've seen a thousand marketing reports. Impressions, clicks, cost per lead, arrows pointing up. And if you've ever presented one, you know the private version of the problem: standing behind numbers you don't fully believe, hoping nobody asks the hard question. Here's what has never once been on the page:
What Did the Spend Cause?
Not what it touched. What it caused: an estimate of the revenue that would not exist without it, stated in dollars, with the model's confidence visible.
Causal receipts, not activity summaries.
How Sure Are We?
Every number Signal publishes carries its own confidence. When a geo-holdout design is in place, the results are causal estimates calibrated against it. Without one, they're statistical associations, and Signal labels them that way. When the evidence is thin, the interval says so.
A number that admits uncertainty is a number you can actually use.
What's It Worth to Change?
Recommendations quantified in dollars, including the moves we evaluated and rejected, so the reasoning is auditable.
Handed to whoever runs your marketing to execute.
Signal generates these answers every reporting period, automatically, against your latest data. The hard question stops being a threat. It becomes the part of the meeting you're ready for.
Start With the Fit Check
Free and honest, with no obligation on your side. If your data can support causal conclusions, you'll get a written fixed-fee quote and timeline. If it can't, you'll know that too.
Start the Fit Check →