Traffic is not your problem. Your landing page is.
Not a hunch about your headline. LandingQA measures what your visitors actually see on desktop and mobile, shows the evidence behind every problem it finds, and hands you a correction you can test.
EVIDENCE-FIRST LANDING PAGE QA
This is what happens after you paste the URL.
Find the leak. Show the evidence. Produce a correction you can test. Validate the result. Below, that loop runs end to end on one representative finding — a single button, measured against a threshold it missed.
The “Sign up” tap target is 32×18 px on mobile.
Below the 44×44 px minimum recommended for mobile.
Measured on the mobile capture (390×844 CSS px). Selector, crop, and threshold are stored with the finding.
(32×18 px)
(48×44 px)
Meets 44×44 px minimum tap target; clearer label.
Nothing in that sequence was a guess. Code measured before anything interpreted, the correction had to survive a rescan before it counted, and your live site was never touched.
Evidence before opinion
Playwright captures the page on desktop and mobile. Deterministic checks run before any model does, so a measured fact never reaches you as an opinion.
Corrections are proposals
Corrections are versioned proposals. You preview one in an isolated sandbox, then a rescan classifies what resolved, what remains, and what the change introduced.
One report. Nine decision lenses.
Every finding lands in exactly one pillar and carries exactly one evidence label. The pillars roll up into three scores you read separately: Conversion Readiness, Technical Health, and SEO Health.
Facts stay separate from interpretation.
Typography, contrast, tap targets, heading and focus order, metadata, links, console and network failures, Lighthouse diagnostics, and axe-core results. Produced by code, never by a model.
Clarity, relevance, persuasion, trust, objections, visual hierarchy, and journey continuity. Each must cite evidence from this scan; unsupported prose is rejected, not published.
Severity and confidence are scored separately — a severe but uncertain finding is presented as a hypothesis. Connect your own analytics and a third label appears: analytics-observed.
EXAMPLE REPORT
See the report before you run your own.
Here is a real report in the shape you would receive it — the captured evidence, and the three findings that ranked highest. The scores, the other five findings, and every validation plan are in the full example.
Captured evidence
Measured by code from this scan’s capture
Top three findings
Ready to find out what is costing you the sale?
Start with a public URL. Payment is requested after the scan.
Scan first. Decide after the report is ready.
You can start with a public URL. Payment is requested only when the scan finishes and you choose to unlock the full report.
The same browser continues even when you open the private confirmation link on your phone.
Desktop, mobile, states, and technical evidence
Wait here or leave; we email you when the saved report is ready
Desktop 1440, mobile 390
Nine pillars, measured first
Verified, deduplicated, ranked
Payment is requested at this step
Your report is ready
Before payment, you see only how many findings landed in each category.
3 findings
2 findings
1 finding
2 findings
1 finding
4 findings
- Conversion Readiness, Technical Health, SEO Health
- Top three priorities, ranked by evidence and effort
- All findings by pillar, with severity and confidence
- Evidence crops, measured values, and thresholds
- Correction proposals with sandboxed preview
- A validation plan for every correction
- AI remediation prompt and Markdown download
$37 for 3 reports · $79 for 10 · $149 for 20 plus human specialist validation within 48 hours. One-time payment, no subscription.
Everything needed to choose the next test.
The report names what the page already communicates successfully, so a fix never quietly breaks it.
Ranked by severity, goal relevance, visitor exposure, and confidence, divided by effort.
Grouped by pillar and deduplicated, with severity and confidence held apart.
Screenshot crops, selectors, viewport and state, plus the measured value and the threshold it missed.
Exact copy replacements, or allowlisted DOM and CSS patches you can preview.
What to test, what to measure, and what would count as a result.
WHY LANDINGQA
Why not just ask ChatGPT or Claude?
You can—and they can be useful. But a one-off conversation is not the same as a repeatable landing-page QA system.
The audit process is the product.
Multiple checks. Independent validation. One report.
EVIDENCE LABELS THAT DO NOT BLUR
The report separates facts, interpretations, and observations.
LandingQA does not turn every concern into a measured fact. Each finding says where it came from, how confident the system is, and what still needs validation.
Dimensions, contrast, focus order, broken resources, metadata, performance diagnostics, and accessibility-rule results retain their cited evidence.
Clarity, persuasion, trust, and journey findings include the supporting page evidence, confidence, correction, and a way to test the correction.
When analytics is connected, the report keeps aggregate observations separate from page measurements and never presents correlation as causation.
The report identifies what to inspect and test. It does not guarantee uplift, choose a winning variant, or replace an experiment with real visitors.
That distinction is preserved in the saved report and its Markdown download.
The example shows the structure you unlock, including what the system cannot conclude from a public-page scan.
- Claims, evidence, corrections, and validation plans stay separate.
- The final section explains how to use the report safely with AI.
- Category totals are visible before you choose a package.
You can start a scan with any public landing-page URL.
Questions before you scan
Your next landing-page decision should start with evidence.
Scan first. Unlock the full report when it is ready. You are reading a page that has to survive its own product — that is the whole pitch.