go upstream
Media decision intelligence

If every channel is performing, where is the waste?

Meta says its AI drove 15.7% more conversions this year. The average ad also cost 12% more. DTC brands spent a quarter more on Meta and earned about the same per dollar. When every number looks fine, nobody goes looking for the money in the wrong channel.

Meta will keep getting better at Meta. Google will keep getting better at Google. Neither of them will ever see all your channels at once. You do. That is the only place left to find money.

From the sample report
Sample report page: where the next $1.5M goes, with every channel marked increase, reduce or hold
Mock data, real methodology Download the full report →
02 / WHY YOU CAN'T SEE IT

Reported one way, modeled another.

Across 299 DTC brands last quarter, Google brand search reported 19x. Tested against holdouts, the same spend returned 5.7x. Meta went the other way.

ChannelReportedTested
Google Brand19.07x5.72x
Meta Acquisition1.83x2.07x

One channel overstated by 70 percent, the other understated. You cannot guess which way yours are off.

We model a ROAS for each channel from your own spend and revenue, and show it next to what the platform reported. Holdout tests are how you check a model like that. If you run them, send them and they go in. If you don't, the model still ranks your channels, and it shows you where a test would be worth running.

03 / WHAT COMES BACK

A ranked allocation, and the evidence under it.

Budget recommendation page: every channel with its current and recommended share, the change in points, next-quarter budget, and projected revenue for the same budget One page of four. Download the full report →

Run it again as new sales and spend data lands, so the split keeps up instead of waiting for the next planning cycle.

Selling DTC, Amazon and retail

Kestrel, active apparel. $3M across 8 channels, modeled against each revenue stream separately, so retail shows up where the platforms can't see it.

4 pages · mock data
Performance and brand in different teams

Luma, mass beauty. $24M across 13 channels, one ranking grouped the way the teams are organised, so each reads its own channels in the same numbers.

10 pages · mock data
04 / GET IT

Send exports. About a week. Then again as data comes in.

01
Send what your platforms already export. CSV or Excel is fine. Six or more months if you have it.
Shopify sales reports ↗·Meta Ads Manager: Reports → Export → CSV·Google Ads reports ↗·TikTok Ads reporting ↗
02
We model a ROAS for each channel and rank where the next dollar goes.
03
Back in about a week. Then again as new data lands, so you are deciding on this quarter rather than last one.
Writing
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