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Turn support tickets into product insight

Support volume is telling you something and nobody has read it as a whole.

Longsupportinsightanalysis
Read the support tickets below as evidence about the product.

1. Group them by root cause, not by the words in the ticket. Ten tickets saying different things may share one cause.
2. For each cause, separate: a bug, a missing feature, a discoverability problem, a documentation problem, or a wrong expectation set by our marketing. The fix differs entirely.
3. Estimate the volume and the support cost of each cause from the tickets given.
4. Identify the **silent** version of each issue: for every person who wrote in, what is the larger group likely doing instead?
5. Rank by (users affected x severity) ÷ effort to fix, and name the one change that would remove the most tickets.
6. Note which themes are too thin to act on yet.

Tickets:

Making it yours

  • Paste your own material where the prompt asks for it. Everything above that line is instruction, not content.
  • Delete any rule that does not apply to you. A shorter prompt that fits beats a thorough one that does not.
  • If the answer comes back vague, add a line saying what you do not want. Constraints work better than encouragement.

Discovery and evidence. Checking the idea before you commit: research, feedback, competitors, risky assumptions, success metrics.

Related prompts

Define success metrics for this featureBefore you build, so you're not inventing a metric afterwards to look good.Find the riskiest assumptionBefore committing a quarter to a plan that rests on something untested.Design user interview questionsYou have five research calls booked and one chance to not lead the witness.Synthesise raw feedback into themesA pile of interview notes, survey answers or reviews and no pattern yet.Tear down a competitor's productUnderstanding a rival properly, beyond "they have more features than us".Riskiest assumption hereA plan that depends on something nobody has checked.

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