//JSON to JSON-LD - FAQPage
JSON to JSON-LD - FAQPage
JSON-LD output
Paste JSON on the left to convert it to JSON-LD automatically.
How to use
- Paste FAQ JSON using faq, questions, or mainEntity-like arrays.
- Select FAQPage schema to map entries into Question and acceptedAnswer output.
- Review output and validate before publishing FAQ markup.
FAQ
Which input shapes are supported?
The tool detects faq, questions, mainEntity, and array-based question-answer structures.
Will it build Question and Answer types?
Yes. It outputs Question items with acceptedAnswer in Answer format.
Introduction
Use this page when your source data is a question-answer list and you need FAQPage JSON-LD with predictable structure. It is designed for support pages, policy explainers, onboarding docs, and marketing FAQs where input formats vary between teams.
What this variant optimizes
It transforms common Q&A payload shapes into schema-ready mainEntity arrays. Inputs from faq, questions, or lightweight arrays are normalized into Question objects with acceptedAnswer so you can publish consistent markup without hand-editing every entry.
Key Features
- Supports multiple source patterns, including flat Q&A arrays and object-based FAQ blocks.
- Creates
QuestionandAnswertyped nodes to improve validator compatibility. - Preserves reusable fields outside FAQ arrays instead of stripping non-FAQ metadata.
- Outputs readable JSON-LD that is easy to inspect and maintain.
Common Use Cases
- Converting help-center content exports into FAQPage schema for article templates.
- Cleaning inconsistent FAQ payloads before integration into static site builds.
- Generating structured data snippets for localized FAQ pages with shared pipeline logic.
Related Variants
You may also need:
- Article variant when FAQs are embedded in long-form guides.
- Product variant for commerce pages combining product and FAQ blocks.
- Base JSON to JSON-LD converter for generic JSON-LD conversion tasks.
Best Practices
- Keep each answer concise and factual; overly promotional text can reduce structured-data quality.
- Avoid duplicate questions across sections to prevent conflicting entity interpretation.
- Revalidate after localization because translated punctuation and quotes can break JSON input.