Persona testing
AI personas with distinct backstories visit a site the way real people would — with a goal, no map, and no patience — and tell you, in their own words, what confused them. We point them at our own site and publish what they find. Here’s the proof it works.
AI-persona observations — they behave as real people would; they are not human testers.
Each tester has a real backstory — Grandma Pat, a busy contractor, a first-time founder. They read like the person, not a checklist.
They get a first-time-visitor goal (“order dinner”, “figure out what this costs”) and browse autonomously — cost- and step-capped.
The finding is what they experienced, in their voice — “I couldn’t tell whether the 20% was mine or theirs” — not a tidy recap.
Every finding lands as an unconfirmed claim. A person confirms it against reality before it becomes real work — and we log what we fixed.
Proven with a real partner
We pointed the personas at QuickSites, a sister product. One persona, Daniel, tried to work out what the company did — and hit a wall:
“I wanted to know if they had templates for different industries, but I couldn’t find that information easily.”
He was right. The homepage was wall-to-wall commerce and reseller copy and never once mentioned that QuickSites has 57 industry-specific starting points — a genuine differentiator, invisible to a first-time visitor. A human read the source, confirmed the gap, and promoted the finding to real work. QuickSites wrote an industries section the same session, and — after review — shipped it to the live homepage.
Live — on our own site
We run this on ourselves, in the open. Nothing here is cherry-picked to flatter us.
Simple, pay-per-use
Verify a domain you own and get free credits every month — about three reports, no card. One credit runs one persona toward one goal; a typical report is a few credits. Need more? Buy a credit pack. No seats, no annual contract.
Delivered where you work
Every run produces a shareable report page. You can also have the results land as a message in your team’s Slack channel the moment they’re ready, or POST to a webhook into your own tools — no dashboard to babysit.
If a testing tool can never come out against you, it’s broken. A page where every finding is “fixed” would be as untrustworthy as one where none are. So we leave the open ones open, mark the shaky ones shaky, and only a human — never the AI — decides a claim is real. The finding that stays a claim is what makes the confirmed one mean something.