TheAI Academy
職場與商業

Mine common questions from support history and generate an FAQ knowledge base

Aggregate past support conversations and complaints, use AI to cluster high-frequency questions into clear Q&As, and build a site FAQ and an internal support-script library to cut repetitive replies.

  1. 1. Export and clean support records

    Export the last six months of conversations from your support system or inbox, remove personal data and noise, and organize into a question-and-answer table as analysis material.

    ChatGPT Notion AI

  2. 2. Cluster high-frequency questions

    Give the conversations to AI, ask it to cluster by topic and count occurrences, find the top 20 most-asked questions like returns, shipping, specs, and warranty, and prioritize them.

    Claude ChatPDF

  3. 3. Write standard Q&A content

    For each high-frequency question, have AI write a concise, correct answer per company policy, in consistent Traditional Chinese and a friendly tone, avoiding ambiguous wording.

    ChatGPT Notion AI

  4. 4. Proofread and polish tone

    Check whether each answer matches actual policy and has no typos or grammar issues, use a writing tool to polish into a consistent brand voice, and flag sensitive questions needing manager confirmation.

    Grammarly

  5. 5. Publish and consolidate into a script library

    Publish the finished Q&As to your site's FAQ page, organize the same content into an internal support-script library for new hires, and schedule a quarterly review and update.

    Notion AI NoteGPT

FAQ

How complete must the data be for AI to analyze conversations?

The more the better, but the key is covering common scenarios. The last six months and a few hundred conversations are enough to derive high-frequency questions; too little data easily misses important ones.

Are there privacy concerns exporting support records?

Yes — be sure to remove names, phone numbers, order numbers, and other personal data before uploading for analysis, or use de-identified summaries, to meet data-protection requirements.

Can the generated FAQ answers be published directly?

Not recommended. AI-produced answers should be proofread by someone familiar with policy, especially questions involving rights like refunds and warranties — publish only after confirming they're correct.

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