Where Your Next Marketing Dollar Goes
We rank your channels by the growth each one will actually buy you — without ever asking for your analytics, your ad accounts, or your sales data.
Search stopped sending traffic. Roughly 60% of searches now end without a click to any website — the answer arrives on the results page and the visit never happens (Bain & Company). The audience is still there. The measurable evidence that you reached them is not.
Marketers know it. They just can't see it.
43% of marketers say they are optimizing for AI search. Only 14% actually measure how they perform in it.
Conductor, 2026
That gap is the whole problem. Optimizing something you cannot measure isn't a strategy — it's spending with a story attached. Closing it is what we do.
What you get
We tell you where to put your next marketing dollar to get the most growth. Redesign the content on your site. Put more into Google Ads. Publish more on YouTube. Push harder on earned coverage. Each option comes back ranked, with an expected lift attached — not "this channel looks healthy," but a number for what moves if you push here instead of there.
You never hand over a thing
Here is the part that surprises people: we don't need your data.
No analytics access. No ad account permissions. No sales exports. No security questionnaire, no data-sharing agreement, no six-week wait on legal and IT — the part of every measurement engagement that quietly eats the first quarter before anyone learns anything.
Instead we reconstruct your marketing from traces that are already public:
Ad-transparency disclosures | Google's Ads Transparency Center and the Meta Ad Library, read week by week — paid activity and flight timing, for you and your rival. |
Web-archive snapshots | Your site's capture history, which dates every page you published or rewrote — weighted by how well-structured that page is, so a solid page counts for more than a thin one. |
Public search interest | The demand side: what people actually looked for, week by week. |
Channel upload history | YouTube publishing cadence and minutes of video shipped. |
News coverage | Earned media volume — the coverage your marketing bought you for free. |
Share of voice | You against your competitor on one common scale — the outcome the model has to explain. |
Out of those traces we rebuild a weekly investment series for every channel and a weekly demand series to explain: a close simulation of your real spend and your real sales, assembled entirely from the outside.
The timing isn't incidental.
71% of brands cut their reliance on user-level tracking after iOS 14.5 and cookie deprecation. Marketing Mix Modeling came back precisely because it needs none of it — no cookies, no device IDs, no user- level tracking at all.
eMarketer, 2025; industry reporting, 2026
We took that one step further. If the method doesn't need user-level data, it doesn't need your data either.
A causal model, not a correlation report
Correlation is easy and mostly useless. Brands spend more when their category is already hot, so a naive model hands the credit to whichever channel happened to be running — and quietly blames a channel for a decline that was already underway before it launched.
Our engine is a causal model built on Marketing Mix Modeling and refined over several iterations to isolate the incremental contribution of each channel. It accounts for carryover, because advertising keeps working after the flight ends, and for saturation, because the tenth video does less than the first.
Then every channel has to earn its recommendation. The sharpest test is a placebo: we check whether your activity also predicts your competitor's search demand. Your ads cannot cause your rival's searches — so if both rise together, what you were looking at was the category lifting, not your marketing working. Channels that survive are labeled and ranked. Channels that don't are named and held back, so their absence reads as unproven, never as cut it.
Channel | Estimated lift | Survives testing |
Website content | +8.34 share pts | Validated |
Google Ads | +21.48 share pts | Shared trend |
Meta Ads | +7.34 share pts | Trend dominated |
Illustrative rows in the format every report uses. The biggest number is not the recommendation. Google Ads shows the largest raw effect and still fails the placebo — its activity predicts the competitor's demand too. Website content, the smaller number, is the one that holds up.
No number in a vacuum
Every movement in your search volume gets tested through two lenses: what your competitors are doing, and what the whole market is doing. A rise can be your work — or your rival pulling their ads. A drop can be a failure — or a category-wide slump you actually outperformed.
Our market-share model handles this structurally rather than as an afterthought: every channel is measured relative to your competitor's activity in the same week, so anything moving the whole market cancels out of the math instead of being adjusted away afterward. The report then splits the change you actually observed into named sources — category demand, competitor effort, and each of your own channels. On one worked example the category alone accounted for roughly 88% of a movement the brand could easily have claimed as its own.
We've run the full pipeline end to end on a pharma matchup — BESREMi against Jakafi in polycythemia vera — and a consumer one, Garmin against Whoop. Same public sources, same engine, two categories that share nothing else.
See one before you commit to anything
We'll send a sample report for a real brand pair: the channel ranking, the expected lift on each, the verdicts on what survived testing, and the appendix showing every formula behind it. No access required — that's the point.
