Getting your per-page JSON-LD schema right for AI engines can be a bit tricky, and there are some common pitfalls to watch out for. Avoiding these can really boost your site's AI visibility:
- Using the wrong schema types: A big mistake is just slapping a generic `WebPage` type on everything. How to avoid: Carefully audit each page's primary intent – is it an article, a product, an FAQ, a how-to? Then, select the most specific and accurate Schema.org type (e.g., `Article`, `Product`, `FAQPage`, `HowTo`). This helps AI truly understand your content.
- Schema that doesn't match content: Embedding schema that lists information not visibly present on the page can actually harm your credibility. How to avoid: Always ensure your JSON-LD accurately mirrors the visible content. If you're describing FAQs in schema, those FAQs should be clearly displayed on the page itself.
- Omitting key properties: Things like `author`, `publisher`, `organization`, or `mainEntity` provide crucial context to AI. How to avoid: Include all required and recommended properties for your chosen schema type. This helps LLMs determine expertise and relevance.
- Implementing schema inconsistently: Just doing a few pages here and there won't cut it for AI. How to avoid: Plan to apply schema systematically across all high-impact sections of your site – services, products, key articles, important FAQs. Consistency is key for AI understanding.
- Failing to test your JSON-LD: Invalid markup won't be picked up by crawlers. How to avoid: Always use structured data testing tools to validate your schema before it goes live. This catches errors early and ensures your efforts aren't wasted. If your site has a lot of diverse content, or you want to be a top-tier source for AI, automating this process or getting professional help for templating can be incredibly beneficial.