How we calculate our estimates
Most e-commerce analytics tools show a number without saying where it came from. This page sets out our method in full, including its limits — those are part of the product, not fine print.
Two kinds of figures, never conflated
Every number we display carries its provenance. A published fact is data the platform publishes itself under a legal obligation. We do not compute it, we report it. Anyone can verify it. Modeled data is computed by us from a real input specific to the store, combined with published sector averages. It is shown with a ≈ sign — a published fact never is. A sector benchmark is a market average, with no data specific to the store. It serves as an input, never as a result: we publish no estimate that would rest on it alone.
The published fact: European ad reach
The EU Digital Services Act requires large platforms to publish, for every ad delivered in the European Union, the number of people reached — commercial ads included, not just political ones. This data has two rare properties. It is exact, because it comes from the platform that delivered the ad. And it has no volume floor: a tiny store appears as precisely as a large brand, where conventional audience panels report nothing below tens of thousands of monthly visitors. We show it as-is: cumulative since the ads started running, within the EU, in unique people. Never turned into a monthly figure or a visit count without saying so.
From reach to sales: the full chain
published reach × frequency × click-through rate = visits visits × conversion rate = orders orders × average basket = revenue Frequency (impressions per person reached) and click-through rate come from published, sourced and dated sector averages. So does the conversion rate. The average basket, however, is the price actually observed in the store's own catalog whenever we have it — data specific to that store, preferred over any market average. Two ads from the same store often reach the same people, and the platform does not de-duplicate. So for each country we keep the largest reach observed, then add across countries — a person cannot be in two countries at once. This floor has one property that matters: it does not depend on how many creatives a store tests, otherwise we would be ranking stores by creative activity rather than by size.
What this figure is not
It is a floor, not a total. It only sees the European Union: a campaign running solely in the United States does not appear. And it only sees paid social advertising: not organic search, not direct traffic, not email, not physical retail. The direct consequence, and the most important limit to grasp: this figure is not comparable across store profiles. A small store driving all its traffic through advertising will come out close to its real revenue. An established multi-channel brand will come out far below its own. Comparing the two on this metric would measure their dependence on advertising, not their size.
When we show nothing
If a store has no measurable EU advertising, we have no real input about it. So we display no estimate. We could produce a figure from sector averages alone. It would look credible and mean nothing about that particular store. We prefer to say the estimate is unavailable, and why.
Frequently asked questions
- Where exactly does the reach data come from?
- From the ad library Meta publishes under the EU Digital Services Act. Every ad delivered in the EU discloses the number of people reached, broken down by country. We report it unmodified.
- Why do your estimates look low?
- Because they only cover paid advertising delivered in the European Union. Everything else in a store's revenue — search, direct, email, outside the EU — is absent by construction. It is a deliberate floor.
- Can two stores be compared on this figure?
- Only if their profiles are comparable. Between an ad-driven store and a multi-channel brand, the gap measures dependence on advertising, not a difference in size.
- What happens if a merchant does not want to appear?
- Removal means deletion, not a pause: we erase the data derived from their store, it disappears from our public pages and our sitemap, and we stop visiting it.