Predictive content diagnostics

See your content through your audience's eyes

Synthetic personas visit your page in a real browser. An attention model trained on real eye-tracking data predicts where their eyes land first — then they read, think aloud and try to complete the task. You get one report: what they see, what they understand, and where they drop off.

Try a free focus group See a real report

Free to try: the focus group runs on the credits you get when you create an account by email. Full page tests are in private pilot. The example reports are open.

Attention heatmap over a real product page
Predicted first glance on a real product page — red = high attention
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What would a room full of people say about your idea?

Type a name, a tagline, a headline or an offer. A simulated focus group of five personas — sceptic, enthusiast, busy, newcomer, expert — reacts: first impression, what they expect, what worries them, and which one they'd pick.

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No card. Nothing runs until you click the link in the email — that creates your account and starts the panel with free credits.

What you get

A prioritized list of what to fix — with evidence

Not a score. Not a wall of analytics. A short, readable report: the strongest finding first, each one backed by what the personas actually said and where they said it.

Findings that converge across personas

When several different personas hit the same wall, it counts. This finding — a missing demo path on a pricing page — was flagged by every persona and marked "start here".

From a real run on a real LMS product page.

A convergent finding with quotes
Key figures band
The headline numbers: attention on actions, convergent problems

Numbers you can act on

How much of the first glance lands on an action instead of decoration? How many problems did independent personas agree on? Two numbers, honestly thresholded — no invented benchmarks.

How it works

Perception first, explanation after — like a real visitor

People don't read pages top-to-bottom. The eye lands somewhere, and the story starts there. ThinkAloud works in the same order.

1

Point it at a page

A public URL, an uploaded HTML prototype, or an image. Choose the purpose: conversion, communication or reference — the test judges accordingly.

2

Personas experience it

An attention model trained on real eye-tracking data predicts the first glance. Personas — built from your real search queries if you have them — then read, navigate and think aloud in a real browser.

3

Read the report

Heatmap on top, then coverage, strengths and prioritized friction — each finding with quotes, severity and the exact page it happened on. PDF included.

Four kinds of friction, covered

Trust, meaning, ability and effort — the behavioral friction framework behind the analysis. The report shows which fields work, which have problems, and what nobody mentioned.

Four-field coverage panel
Examples

Real reports from real runs

Not mockups — actual output, run on live pages with personas built from real Google Search Console queries.

LMS product page

Conversion test. Found a convergent leak: buyers at the pricing page couldn't find a demo path.

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E-learning agency

Vendor evaluation. Zero friction — and the case pages turned a sceptical buyer around.

Open report →

Analytics site (EN)

English searchers with real query intent, from landing to signup. Report in English.

Open report →

Prediction, not measurement. ThinkAloud is a fast pre-test, not a replacement for real users. It tells you what to fix before anyone real sees it — and it is honest about being a simulation: every report is labeled accordingly.

Test your page before your audience does

Run a test See a real report