Optimise ledgerly.co/vs/ramp
Ramp is cited on 6 comparison prompts you are absent from
Product · Act
Optimise Content scores any URL for answer engine optimization, then shows exactly what to change: the terms AI expects, the questions you leave unanswered, and the facts it needs to cite you.
The scorecard
Every module below is one input into the same score, and every fix moves it while you watch.
How ready the page is to be quoted in an AI answer.
Rises to 88 after the fixes belowThe vocabulary AI expects on this topic, and how much of it you use.
7 terms missing entirelyFollow-up questions the page resolves, out of what AI actually asks.
2 missing, 1 too thinAI answers that quote this page today. Ramp holds all six.
3 within reachLive demo data: ledgerly.co/vs/ramp scored against the prompt “Ramp vs Brex vs Ledgerly”.
The audit · Module 01
Prefer reads your page, reads the AI answers it should be winning, and reports the difference as two scores: one for search engines, one for answer engines. They are not the same test.
ledgerly.co/vs/rampScored against “Ramp vs Brex vs Ledgerly”
Whether an assistant can lift a quotable answer straight off the page.
Traditional signals: terms, structure, depth, links.
A page can rank well and still never be quoted. That 31-point spread is the whole reason this module exists.
The three pages winning the answers this URL should own.
Terms · Module 02
Answer engines match on language, not keywords. Prefer derives the terms that appear in winning answers for your topic, then marks each one optimal, thin, missing or overused on your page.
16 terms derived from the answers AI already gives.
Answer coverage · Module 03
One prompt fans out into follow-up questions. If your page resolves them, AI can answer from you. If it does not, AI goes elsewhere and cites whoever did.
What the prompt actually fans out into.
Assistants prefer sources with facts they can verify. Yours carries one of three.
Each missing item becomes a suggested edit in module 05, written and ready to accept.
Page identity · Module 04
Assistants pick sources with a clear job. A page that reads half comparison and half sales pitch reads as neither, so a cleaner rival page gets cited instead. Identity is the check nobody else runs.
What this page reads as, to an assistant.
This page cannot decide whether it is a fair comparison or a Ledgerly pitch, so AI cites cleaner comparison pages instead.
One-click fixes · Module 05
Prefer does not hand you a checklist. Each finding comes as a drafted edit you can read, accept or reject in place, with the score moving as you go.
Four edits, drafted in place. Accept, reject or edit each one.
Accept them one at a time or apply all. Everything is reversible, and the score recomputes on every change.
Measured outcome · Module 06
An optimisation is a claim until an engine re-reads the page. Prefer watches the crawl, re-runs the affected prompts, and closes the loop with a before and after you can open.
ledgerly.co/vs/ramp, 18 to 27 July.
If the prompts do not move, the page reopens with a new set of suggestions instead of quietly closing as done.
Where the work comes from
Action Center queues the pages worth optimising, ranked by the visibility at stake. Optimise Content is where that queue gets done.
Ramp is cited on 6 comparison prompts you are absent from
5 expected terms missing on a page AI already crawls
AI quotes pricing that changed two quarters ago
“We had written the comparison page three times and it never got cited. The identity check explained it in one line: we kept writing a pitch and calling it a comparison.”
Questions
Prefer's AI content optimization tool. It scores any page for answer engine optimization (AEO) and generative engine optimization (GEO), shows the terms, questions and facts it is missing, and drafts the edits that close the gap.
The SEO score measures traditional ranking signals: terms, structure, depth and links. The AEO score measures whether an assistant can lift a quotable answer off the page. Pages often score well on one and badly on the other.
Lead with a direct answer, use the vocabulary that appears in winning answers, resolve the follow-up questions the prompt fans out into, add checkable facts and structured data, and give the page one clear job. Optimise Content measures all five and drafts the fixes.
It drafts each edit and shows it in context. You accept, reject or edit before anything ships, and every change is reversible.
The ones with visibility at stake. Action Center ranks them by how many prompts they affect and how far behind you are, then hands the top one to Optimise Content.
The page stays tied to the prompts it was meant to move. Prefer watches for the re-crawl, re-runs those prompts, and reports the before and after. If nothing moves, the page reopens with new suggestions.
It covers the same ground and goes further. Traditional optimizers grade a page against the top ten blue links. Optimise Content grades it against the AI answers themselves, including answer structure, fact coverage and page identity, which no keyword tool measures.
See how answer engines describe your brand today, and where the openings are to outpace the competition.