What to look for
- Product pages that fail social sharing or search snippets
- Mobile tap targets and image weight
- Trust signals around returns, shipping and payment
Ecommerce teams
Ecommerce report example
Review the PageLens AI checks that matter for ecommerce: product page clarity, mobile UX, trust, metadata, checkout friction and performance.
Likely findings
- Oversized product images on mobile
- Missing alt text on product galleries
- Shipping and return policy hard to find
How to use the report
- Fix conversion-blocking issues before paid traffic.
- Use repeated findings to improve templates rather than one product at a time.
Report anatomy
A PageLens AI report is built to move from evidence to repair.
Example pages should be crawlable because the buyer needs to know what they get before starting a scan. These are the sections the Primary Scan turns into action.
Owner verdict
A plain-English launch decision before the report dives into technical findings.
Evidence snapshot
Rendered-page proof: screenshots, observed HTML, headers and the exact page affected.
Priority queue
Critical and high-risk issues first, with owner impact and acceptance criteria.
Copyable prompt
Copy-paste prompts for an AI builder, developer or agency to apply safely.
Re-scan proof
Before/after evidence after the deployed site changes.
Before / fix / after
The useful part is the proof loop.
A report should not leave you translating scanner output. It should show what failed, what to change, and what improved after the deployed page was scanned again.
Before
Oversized product images on mobile
Fix
Fix conversion-blocking issues before paid traffic.
After
Re-scan the live URL and keep the score movement, screenshot and resolved-finding proof.
Agent handoff
Use the report with the builder that created the problem.
The report is intentionally written so a founder, developer, agency or AI coding agent can act without re-diagnosing the page.
Cursor: paste the finding, route, screenshot note and acceptance criteria into the repo chat.
Codex: attach the Markdown report and ask for a scoped patch plus tests where relevant.
Lovable/Bolt: paste the priority finding and ask for the smallest safe UI or metadata fix.
Agency handoff: send the client-safe summary, then keep the detailed fix queue internal.
Start small
Use the example to choose the smallest useful scan.
If one page decides the launch, start there. If traffic will hit multiple routes, use the Launch Pack so desktop, mobile and the re-scan proof stay together.
Free Growth Baseline
$0
First visible signal
Full One-Page
$1
One URL, every finding
Launch Pack
$29
15 pages and re-scan proof
Frequently asked.
- Is this the same as a live PageLens AI report?
- It is an explainer page for a report example. The live public sample and paid reports contain the actual report UI, screenshots, findings, fix prompts and re-scan proof.
- Can I use this with Cursor, Codex, Lovable or Bolt?
- Yes. PageLens AI reports are designed to become fix prompts. Copy the finding evidence and acceptance criteria into your AI builder or coding agent, then re-scan the deployed page.
- What should I buy after reading an example report?
- Start with the Free Growth Baseline. Use the Primary Scan for one important URL, or the Launch Pack when a homepage, pricing path, social preview and mobile flow all need proof.