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YES

As of 13 August 2026, AI can turn your support tickets into FAQs.

This still needs a person who signs their name to it.

Can you do it?

5 minutesto a draft.

30 minutesto something you’d act on.

Cost, all in£0

Skill neededchat-fluent

Who has to check ita colleague

What the alternative costsDocsBot is a purpose-built alternative that trains chatbots on your documentation and can be embedded anywhere.

If this goes wrong, customers follow an invented or outdated answer and your support team has to correct the resulting confusion.

What to actually do

  1. Hand it to a person

    The route this page recommends

    A person who owns the outcome does this end to end, worth it when the failure is dear.

  2. Use a tool built for this

    Second choice
  3. Do it yourself

    The distant third

    A chat interface, chat-fluent skill, and roughly 30 minutes until you can act on the result.

    How to actually do it

    1. Open your support platform and export a representative set of resolved tickets, including the ticket text, subject, status and an internal ticket ID.
    2. Remove names, email addresses, telephone numbers, addresses, order numbers, payment details, account identifiers and any other customer information that is not needed to identify the question.
    3. Open the current product pages, delivery terms, returns policy, pricing information and support escalation rules, then paste the relevant text into the current business information section of the prompt.
    4. Paste the anonymised tickets into the prompt and ask the chatbot to produce the grouped FAQ with evidence, confidence labels and unresolved questions.
    5. Give each draft answer to the colleague who owns the relevant product or policy and compare it with the current source information, correcting outdated wording, exceptions and escalation routes.
    6. Publish only entries labelled Confirmed in your help centre, then send unresolved or account-specific questions to your normal support process instead of adding them to the public FAQ.

    Prompt

    Turn the anonymised support tickets below into a draft FAQ for [business or product].
    
    Use only facts supported by the tickets and the current business information. Do not invent policies, prices, delivery times, guarantees, product features or legal claims. If the tickets do not establish an answer, write "Needs business confirmation" instead of guessing.
    
    First group tickets that ask the same underlying question, then rank the groups by apparent frequency. Ignore greetings, one-off complaints, internal notes and questions that need a private account lookup. Remove or avoid repeating names, email addresses, telephone numbers, addresses, order numbers, payment details and other personal data.
    
    For each FAQ entry, provide:
    1. A natural customer question.
    2. A concise answer in plain UK English.
    3. The source ticket IDs or quoted evidence supporting the answer.
    4. A label of Confirmed, Needs business confirmation, or Not suitable for a public FAQ.
    
    Preserve important exceptions and escalation routes. Separate questions that require a support agent, account access or a case-by-case decision from questions suitable for a public FAQ. End with a short list of missing information and contradictions for a colleague to resolve before publication.
    
    Current business information:
    [PASTE CURRENT PRODUCT, DELIVERY, RETURNS, BILLING AND SUPPORT INFORMATION HERE]
    
    Anonymised support tickets:
    [PASTE TICKETS HERE]

    Open it prefilled in ChatGPT or Claude, or copy it into Gemini, which takes no prefill link.

What it gets wrong

  • AI cannot tell whether a cluster of tickets reflects a genuine common need or a temporary incident without your operational context.
  • AI cannot establish the current policy when tickets contradict your website, contracts or internal guidance.
  • AI cannot safely turn account-specific problems, complaints or exceptions into general public answers.
  • AI cannot decide which wording your business is prepared to stand behind when a policy is ambiguous.
  • AI cannot remove the need for a colleague to check personal-data handling before the source tickets are uploaded.

Even on a YES, the friction has a name: context depth, verification cost and consent and privacy.

How we scored this

Five axes, each scored nought to two by hand: ten means AI carries the task cleanly, and the thresholds that turn a total into YES, PARTLY or NO are published in the methodology. Each axis name links to its definition.

AxisScore (0–2)
Output2
Inputs2
Verification1
Liability2
Effort delta2
Total9 / 10

FAQ

Can ChatGPT analyse my support tickets and write FAQs?
Yes. It can group repeated questions and draft FAQ answers from anonymised tickets, but it may treat an outdated ticket or an unusual case as a general rule. Supply your current policies and require it to flag anything the tickets do not prove.
How do I use AI to turn customer questions into an FAQ?
Export resolved tickets, remove personal data, add your current product and policy information, and ask the model to group recurring questions with source evidence. A colleague should then check every answer against the information you currently publish.
Can AI find the most common questions in support tickets?
It can sort tickets into apparent themes and identify repeated wording. It cannot reliably measure business importance from ticket text alone, so a temporary outage or a small number of serious cases still needs human interpretation.
Is it safe to upload customer support tickets to AI?
Only upload data that has been appropriately anonymised and that your organisation is allowed to process in that tool. Remove customer identifiers and private case details, and check your organisation's data-handling rules before using an external service.

Nearby answers

Assessed by gpt-5.6-luna (gpt-5.6-luna) on 2026-08-13, second-checked by an independent model. Wrong somewhere? Email [email protected] and it gets re-checked.

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