Playbook
structured data for AI discovery for reference check platforms
A practical playbook for talent marketers to improve structured data—with checks, fixes, and measurement.
Why structured data matters in reference check
talent marketers cannot win AI shortlists on content alone if structured data is broken. Whether commercial pages expose accurate JSON-LD and related markup so AI systems and search engines can parse entities, products, FAQs, and organization facts.
In reference check, common blockers include: Integration and security pages are PDF-only; Canonical host inconsistency splits crawl equity; Assistants quote outdated feature claims. Incumbents and well-documented review sites often dominate AI answers until you publish crawlable comparison content.
What to check
- Organization and WebSite JSON-LD consistent with on-page branding
- FAQPage or HowTo markup only where visible FAQ/HowTo content exists
- Product, SoftwareApplication, or Service types on commercial pages when accurate
- No conflicting schema that invents ratings, prices, or claims not on the page
reference check-specific page priorities
- Pricing — ensure this URL is crawlable HTML with facts assistants can quote when answering “best reference check tools for teams evaluating options”
- Integrations — ensure this URL is crawlable HTML with facts assistants can quote when answering “best reference check tools for teams evaluating options”
- Use-case landing pages — ensure this URL is crawlable HTML with facts assistants can quote when answering “best reference check tools for teams evaluating options”
Fix guidance
Ship truthful JSON-LD that mirrors visible HTML, validate it, and keep entity names consistent across llms.txt and key URLs.
Deep dive: structured data for AI discovery. Industry hub: AI visibility for reference check platforms.
Measure with BatSignal
- Run a Visibility Scan on your reference check site
- Inspect the pillar tied to structured data
- Ship the prioritized fixes and copy-paste deliverables
- Re-verify within 30 days to confirm movement
Related
- reference check hub
- crawl access for reference check
- content readiness for reference check
- ChatGPT citations for reference check
- llms.txt for reference check
- structured data for AI discovery
- All industries
FAQ
What is structured data for reference check platforms?
Whether commercial pages expose accurate JSON-LD and related markup so AI systems and search engines can parse entities, products, FAQs, and organization facts. For reference check, this shows up when buyers ask “best reference check tools for teams evaluating options” and when AI crawlers attempt to fetch your commercial pages.
How do we improve structured data?
Ship truthful JSON-LD that mirrors visible HTML, validate it, and keep entity names consistent across llms.txt and key URLs. Industry-specific must-have pages include Pricing, Integrations, Use-case landing pages.
How does BatSignal score this?
Content readiness / entity clarity. See the [methodology](/methodology) and related guide: /guides/json-ld-ai-discovery.