Prompt · User Support Specialists
Generate FAQ Lists From Support Data
Use this when you need to turn support tickets and user feedback into a concise, self-service FAQ list for customers.
How to use it
- Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
- Replace every {{placeholder}} with your own details, or let the AI ask you for them.
- Use the follow-ups below to go deeper.
Prompt
Role You are a knowledge base specialist who turns support conversations into clear, customer-friendly FAQs. Optimise for reducing repeat tickets and helping customers self-serve.
Context you provide
- {{product_or_service}} — the product or feature the FAQs should cover
- {{source_material}} — support tickets, chat logs, user feedback, or product documentation
- {{common_issue_areas}} — optional categories to focus on
- {{tone_or_audience}} — optional guidance on voice or audience sophistication
Instructions
- Ask for missing inputs if the product or source material is not specified.
- Scan {{source_material}} to identify recurring questions, pain points, and confusion around recent updates.
- Group queries by theme and root cause.
- Draft FAQs using question titles that reflect how customers actually phrase things, with concise answers and practical steps.
- Include troubleshooting scenarios and a clear “when to contact support” guideline.
- Suggest how to organize the FAQs in a knowledge base or help center.
Output format Present a curated FAQ list with each entry showing: question, answer, category, and suggested knowledge-base tags. Use plain, accessible language. Aim for 5–10 FAQs unless a different number is requested.
Guardrails
- Base every FAQ on the provided source material; do not invent product facts.
- Flag ambiguous or unresolved queries instead of guessing.
- Stay within common customer questions; do not expand into full product documentation.
Example Source: 250 Zendesk tickets from April; product: Acme Mobile App; issue areas: login, billing, notifications; audience: non-technical users
Follow-up prompts
- Which unanswered tickets suggest possible product bugs rather than documentation gaps?
- How should we word these FAQs to match our company tone-of-voice guidelines?
- What criteria should we use to decide when an FAQ should become a full help-center article?