Why run a PixelGR scan now
PixelGR scans give you a compact, actionable view of how search engines and AI systems see your local site, enabling you to address the highest-impact issues first. Scans come back in about a minute, so you can re-scan after each change and see exactly what moved.
Start a scan: step-by-step
Go to the PixelGR scan page, enter the address of the site you want to check and start the scan. While it runs, the scan crawls your public pages and checks structured data, metadata, links and page performance.
Understand the AI visibility score
PixelGR presents results as a single AI visibility score out of 100, a clear snapshot you can compare from one scan to the next.
Because it is one number, the score makes progress easy to track: run a baseline scan, fix the highest-impact issues, then scan again and compare. If the score rises, your changes are being picked up.
Also check the pages indexed count beside the score. It shows how many of your pages were found, so you can spot any the crawl missed.
Use the score together with the detailed export to understand where gains are available. A small rise in the score can mean a broad improvement across many pages, while a larger change on a handful of pages can indicate focused wins. The export breakdown maps score components to specific checks to show whether technical fixes, schema updates, or content improvements are driving progress.
Export the scan results for triage
After the scan completes, download the export of page-level checks, errors and suggested fixes to assign tasks or import the data into your issue tracker. Exported data gives a line-by-line view of failing checks, which is essential for triage when you have many pages or content types to review.
When exporting, include the columns that list the check name, failing URL, severity and suggested remediation. That structure lets you sort by severity and page type and then plan a practical work queue.
Common fields to rely on include the page URL, the specific check that failed, a short description of the issue, and any recommended remediation text. Those fields make it simple to copy entries into tickets, add screenshots or notes, and set the right priority for each task. If your tracker supports bulk import from CSV, use the exported file to create work items in one pass and avoid transcription errors.
Prioritize fixes: a practical workflow
Use the AI visibility score, pages indexed ratio and export details to build a short, effective roadmap. Start with fixes that improve user experience and indexing, then move to content and local consistency.
1. Page speed and Core Web Vitals
Page speed is often the highest-impact area because slow pages reduce user engagement and can prevent content from being surfaced. Aim to have Largest Contentful Paint occur within the first 2.5 seconds for a good user experience, as recommended in Google’s Core Web Vitals guidance.
From the export, sort pages by LCP or total load time and focus on the pages that get the most traffic or are most relevant to local queries. Common fixes to implement first include optimizing images, deferring noncritical JavaScript, and enabling efficient caching. Re-run scans after changes to confirm measurable score improvements.
2. Metadata and title tags
Metadata errors are cheap wins with directly measurable impact on discovery. Use the exported rows for missing or duplicate title and meta description checks to create a prioritized list. Fix titles on high-priority pages first so search engines and AI agents can understand page intent more reliably.
If your site uses WordPress, publish metadata changes via the editor; PixelGR supports workflows that push fixes from the dashboard into the CMS, streamlining verification.
Keep metadata concise and descriptive, and align titles and descriptions with the main user intent for each page. That alignment improves how your content is summarized by search and AI systems and reduces the chance of incorrect or irrelevant snippets being shown for your business.
3. Broken links and internal linking
Broken links create crawl dead ends and reduce index coverage. Filter the export for 4xx and 5xx link failures and correct or redirect those URLs. Strengthen internal linking to distribute relevance to priority pages; add contextual links from high-traffic posts to service and location pages to improve visibility.
Document redirects and fixes in your deploy notes so future scans reflect the corrected URL paths. Monitoring link health as part of each sprint helps prevent regressions and keeps index coverage stable.
4. Local content and structured data
Local content quality and consistent business data are core to being found for local intent. PixelGR checks LocalBusiness schema and related signals, because search engines and AI systems use that structured data to confirm who you are, where you are and what you offer.
Use the export to find pages missing LocalBusiness or organization schema, then implement structured data on service and location pages. Validate schema changes with your structured data testing tool and re-run the scan to ensure the changes are recognized.
Consistency across citations, your site and any local listings reduces friction for verification systems and for AI models that rely on structured facts. Keep hours, addresses and service details aligned to avoid mismatches that can hurt visibility.
Act on the export: triage board example
Create a triage board with three columns: fix now, fix this sprint, and backlog. Move any items that block indexing or directly affect conversions into fix now. For example, if the export shows your most visited product page has a slow LCP, a missing title, and a broken internal link, assign that page to fix now and track the fix across performance, metadata, and links.
Make assignment explicit by adding an owner and a QA checklist to each card. After a fix is applied, re-scan and attach the new export row or a before and after screenshot so stakeholders can see the change was verified by the scan results.
Publish fixes from WordPress
If your site is built on WordPress use the PixelGR WordPress integration to reduce friction. Apply content and metadata edits inside the WordPress editor and publish them directly; then re-run a scan to confirm that the new version is indexed and the score updates. This workflow shortens the loop from detection to verification and lets you iterate quickly.
When publishing, use staging where available and push to production only after verification steps are complete. Note the time of changes in your deployment log so scans can be correlated with releases when you review progress.
Measure progress and set targets
Use the AI visibility score as a single metric to show progress, but always pair it with the pages indexed number so you know whether score changes reflect broader coverage or just a subset of pages. Track both metrics after each sprint and set a realistic target for improvement based on the number of fixes you can complete each cycle.
Report regularly to stakeholders with a short summary of the highest-impact fixes, the change in score and the pages indexed figure. Visualizing the trend for both numbers over time helps show whether technical investments are producing sustained discoverability gains.
Quick checklist before you start
- Run an initial PixelGR scan and download the export for triage.
- Note the AI visibility score and pages indexed from the scan summary for baseline reporting.
- Prioritize fixes by impact: Core Web Vitals first, then metadata, links and local schema.
- Apply fixes in WordPress where possible and re-run scans to confirm improvements.
- Assign owners and add QA steps to each high-priority fix so verification is consistent.
- Keep a log of changes and scan timestamps to map fixes to score movement.
Following this routine will let you use PixelGR scans as a rapid feedback loop: run a scan, export the data, prioritize the highest-impact technical and content fixes, publish changes via WordPress, and re-scan to measure gains. Repeat the cycle and aim to improve both the AI visibility score and pages indexed over time.
Frequently asked questions
How long does a PixelGR scan take?
A PixelGR scan usually returns results in about a minute, so you can re-scan after each change and see what moved.
What does the AI visibility score represent?
The AI visibility score is a single number out of 100 that summarizes how well search engines and AI systems can find, read and understand your site. Track it over time to see whether your fixes are working.
How should I prioritize fixes from the export?
Start with issues that affect indexing and user experience, such as slow pages, where Google recommends a Largest Contentful Paint of 2.5 seconds or faster. Then fix titles and meta descriptions, broken links, and finally local schema and content consistency.
Can I publish fixes from WordPress?
Yes. PixelGR works with WordPress, so you can apply edits in the WordPress editor, publish them, and then re-run a scan to confirm the changes are recognized.