A before/after fix pack, walked through section by section.

1 · Before

The scan-shaped starting point

Subject: acme-example.com (redacted placeholder — illustrative sample, not a real domain)

?What this section is: the same shape as the free scan card above the fold — a hygiene score plus a citation read across answer engines. A real audit runs this on your actual domain across ChatGPT, Claude, Gemini, and Perplexity, with a competitor citation diff.

Measured findings

• HIGHAI visibilityNot cited when buyers ask category questions across ChatGPT, Claude, Gemini, or Perplexity — the direct competitor is.
• HIGHSchemaMissing FAQPage JSON-LD — the format AI answers pull from most.
• HIGHSchemaMissing SoftwareApplication JSON-LD — engines can't cleanly parse the product as a named entity (name, category, pricing).
• MEDSchemaMissing WebSite + BreadcrumbList JSON-LD.
• MEDAccessibility5 automated WCAG 2.1 AA findings across form labels, image alt text, and landmark structure.
• LOWTechnical SEOThin meta descriptions on 6 of the top 10 crawled pages.

?What this section is: every finding is tagged by severity (HIGH/MED/LOW — impact on citation and accessibility, not a generic priority label) and by which of the four scan layers it came from. Nothing here is scored 0 for being hard to read — an unreadable or JS-rendered page gets flagged, not penalized.

2 · Ranked fix queue

What the paid engagement hands back

Every finding above becomes a ranked, paste-ready fix — ordered by impact × effort, the same way a real fix queue ships.

1. 01
   impact: HIGHeffort: LOW

   Add FAQPage JSON-LD to the top 5 buyer-question pages

   Paste-ready schema block generated from existing on-page copy — no new content required.

   why it's ranked here: The single most-pulled-from format for AI-answer summaries; currently absent entirely.

2. 02
   impact: HIGHeffort: LOW

   Add SoftwareApplication JSON-LD to the product page

   Paste-ready schema block with name, category, and pricing fields mapped from the pricing page.

   why it's ranked here: Lets engines parse the product as a named, priced entity instead of an unstructured page.

3. 03
   impact: MEDeffort: MED

   Rewrite the comparison page to name the query buyers actually ask

   Reviewed copy rewrite — same claims, structured around the exact phrasing buyers use in AI chats.

   why it's ranked here: Category queries currently surface the competitor's comparison page instead; this is the direct citation gap.

4. 04
   impact: MEDeffort: LOW

   Fix 5 WCAG 2.1 AA findings (labels, alt text, landmarks)

   Paste-ready markup fixes per finding, human-reviewed.

   why it's ranked here: Beyond accessibility compliance, the same semantic fixes make the page more legible to crawlers and AI engines.

5. 05
   impact: LOWeffort: LOW

   Expand thin meta descriptions on 6 pages

   Reviewed rewrites, one per page.

   why it's ranked here: Supporting signal — improves crawl clarity without being a standalone citation lever.

?What this section is: the $499 Fix tier generates exactly this — a prioritized, paste-ready queue with stack-specific snippets. Nothing is auto-deployed; every fix is human-reviewed before it ships to you.

3 · What changed

The re-scan delta — illustrative, not a promise

After the fixes ship, we re-run the scan and report what moved. Below is what that delta looks like — illustrative sample values, not a guaranteed outcome for any real domain.

?What this section is:the honest re-scan. We guarantee the work, not the algorithm — nobody can honestly promise a specific citation count, so we don't. If a re-run shows no movement on a layer, that's reported too.