The difference the customer doesn't see can usually be found — just not in the company's own story. This page shows how the benchmark brings that difference to the surface, from the initial setup to the report on the table. Anyone who first wants to know exactly what the tool is can read that on what it is.
You provide the sector and a peer group of three to seven players. Based on that, the tool proposes dimensions from a library — the aspects on which deals in that market are won or lost — and a five-point scale that is calibrated per dimension with examples, so that a score of, say, 3 carries the same meaning for everyone.
This is input work, not a session. One person can go through the setup in a single pass; most of the time goes into sharpening the peer group, since that is what makes or breaks the comparison.
The tool invites your own people to score, and where desired, also customers or external experts. This can be split across multiple people: everyone gets their own invitation and fills in their part separately, at their own moment. There is no session in which everyone has to participate at the same time.
In parallel, desk research runs per competitor, following fixed recipes — and every score that results from it requires a source URL. No source, no score that counts as fact. Where a link with existing data exists, it is imported. The time here lies in the number of participants and the availability of sources per competitor, not in the number of steps.
All scores come together in a matrix. Each cell gets its score, the source on which that score rests, a date and a name. Four sources — your own people, customers or experts, desk research and imported data — automatically correct each other here: where the organization itself gives a 4 and no external source can be found to confirm it, that 4 stays in the report as an opinion, not as a fact.
That is precisely why the outcome remains explainable. Nothing is rewritten or smoothed over; every cell can be traced back to who gave the score and what it is based on. Anyone who later disputes the report can look up the underlying cell for every statement.
This part is machine work: the tool adds up, compares and flags where proof is missing. No one is interviewed by the tool itself — expert interviews belong to a different phase, further along in this story.
From the matrix roll four views: a maturity table, a quadrant, a radar per player and a heatmap across the entire peer group. In addition, there is a white-space analysis — where none of the players scores well, and where room is therefore open — and a claim check that shows per claim whether there is a cell with a source underneath it or not.
The priorities in the report are ranked by urgency: not every gap is a problem. A weak point on a dimension that doesn't weigh in the deal can simply be left as is. A small gap on the dimension the customer actually chooses on is a different story — the report indicates which of the two it is, instead of weighing everything equally.
The report comes out as a document you can browse through and share, with the four views, the white space and the claim check included, and a set of priorities with first steps per gap. What happens with it afterwards, and which routes exist to proceed with the more difficult scores or with expert interviews, is worked out on the page outcomes.
Running the benchmark can be a one-off or repeated periodically — that is a choice, not an obligation the tool imposes. In a repeat run, the setup largely stays the same: the same dimensions, the same scale, possibly an updated peer group. What changes is the sourcing round: new scores, new sources, new dates in the matrix.
This turns the heatmap into a series instead of a single image. Has the gap on the buying dimension become smaller after the previous round with priorities, or not? Is there a claim that couldn't be defended before and now has a source? A repeat run shows whether a gap has shifted or is fixed — something a single measurement can never show, no matter how detailed the proof matrix is.
Anyone who wants more depth after the report than their own sourcing round allows — for example because a peer is hard to score without an external conversation — will find the options for that with a partner, not in the tool itself. Background pieces on dimensions, scale calibration and evidencing are collected in the knowledge base.
A sharper claim and a smaller gap on the buying dimension are not yet an action. Anyone who wants to know what that concretely requires in terms of tasks, hours and systems will find the work scan at ftetoai.com.