AdCrux helps you plan media investment using each brand's real history of spend and results — a clearer starting point than intuition or generic assumptions.
Set up in minutes · Works with the spend and results data you already track
And you still have to recommend what to move. That's the job — regardless of whether the data lines up.
Every source tells its own version: Google says 87, Meta says 74, your CRM says 120 total. Each platform is just measuring a different slice of the same activity.
Looking at channels one at a time doesn't show how the mix works as a whole, and that's what you need before recommending the next move.
This isn't about which platform is lying. It's about needing a single, comparable read before you can recommend anything with confidence.
One channel looks like it's working The dashboard is green and the ROAS looks fine. But looking good in isolation isn't the same as being worth the next dollar.
Another looks expensive High CPA on paper. But expensive compared to what: the rest of the mix, or what it used to cost?
A third one, nobody's sure It might be driving new demand. It might just be riding along on what the other channels started. Nobody on the team can say for sure.
And the client still wants an answer "What should we do with the budget" doesn't wait for certainty. The recommendation still has to be more than a hunch.
Without a way to compare channels side by side, the decision ends up depending on who argues best in the room, not on the numbers.
Answering "why this channel and not that one" takes something more comparable than a quick dashboard read.
The client is looking at one report, the media team another, finance a third. Nobody's arguing from the same baseline.
Testing without a clear read going in amounts to "let's try something and see," with nothing to compare the result against.
Each quarter starts the argument over from scratch, with no record of what was tried last time.
AdCrux uses each brand's spend and results history to help you compare scenarios, understand contribution by channel, and plan tests.
Compare scenarios: See what a reallocation would do to the whole mix before you propose it.
Understand contribution — See how much each channel is adding, separate from baseline and from what the other channels are already driving.
Plan the test: Turn "let's try something" into a specific, bounded test with an expected range to compare the result against.
Build on what you know — Every run, scenario, and test adds to what's already known about this brand — so the next recommendation starts ahead of the last one.
Modeled from the uploaded spend and results, not an industry benchmark
The workspace for comparing scenarios, reading contribution by channel, and planning the next test.
One comparable read across the whole mix.
Sample dashboard · Your data stays in your account · Export to PDF
Every step below runs on the spend and results you upload.
Spend and results by channel and week, straight from what you upload.
CSV uploadThe model reads the full mix together: contribution, saturation, and baseline for every channel.
~30 secondsTry different reallocations side by side, see the projected outcome of each, then save the one you'd recommend.
Compare & saveTurn the recommendation into a bounded test, log what happened, and it becomes part of this brand's planning history.
Build the recordFour calls, each grounded in the uploaded numbers for this brand.
Channels with room left in the mix, worth the next dollar based on how they're performing now.
Once a channel passes the point where more spend stops adding, it's a candidate to scale back, even if the platform report still looks fine.
At the current level, some channels are simply doing what they should. No case yet to move either way.
A specific, bounded test to validate the move before you commit the full recommendation.
Built for the person who has to make the call.
Marketing Mix Modeling used to require data scientists. AdCrux makes it available to any team with a CSV file.
Built independently from any platform attribution model. No pixel, no SDK, no API key connecting back to Google or Meta.
Every result comes with a confidence score and model diagnostics. You know when the model is reliable.
If you're already planning budget for $10K–$30K/month in spend, this pays for itself the first time it changes a recommendation.
For brands and small teams running paid media and looking for their first independent view of performance.
For growing teams managing multiple brands or business units who need a reliable, repeatable measurement process.
For agencies that plan budget, defend recommendations, and track tests for their clients — not just a one-time measurement report.
All plans include a 14-day free trial. Cancel anytime. Need more? Contact us about Enterprise.
Book a demo — we'll walk through it using a case close to your own.
Book a demo →Set up in minutes · Works with the spend and results data you already track