Your team, thoughtfully built.

How to Summarize Product Feedback With AI

By Staffmor Staff

Practical guides from the team building Staffmor.

To summarize product feedback with AI, ask for themes that each carry their evidence: which reports, how many different people, a quote, and anything that disagrees. Decide first whether you are counting reports or people. A summary that loses its sources turns five messages into "users want," and you can no longer tell which five.

The example is a made-up booking product with five reports.

Count the right thing

Two different people could not find the equipment instructions.
One person asked for another date.
One person wrote twice about the address link.

Five reports, four people. Give each report a label and a date, mark the repeats, and remove names the analysis doesn't need. Material included in a model request goes to your AI provider, so share only what you are allowed to share.

The request

The request: "Group the five reports below by the problem the person had. For each group show the report labels, how many different people, a representative quote and any evidence that disagrees. Keep feature requests separate from things that failed. Recommend what to check before we prioritize. Do not invent a root cause or a roadmap."

What comes back

Equipment instructions unclear: two reports, two people. Check whether the instructions are visible on the page.
Another date: one request. Check availability before promising anything.
Address link: two messages, one person. Counted once.
Not known: how common any of this is among everyone who visits.

The mistakes to watch for

The percentage. "40% of users can't find the equipment instructions" is two of five reports, dressed as a statistic about every user. The people who wrote in are the people who wrote in. Most visitors never say anything.

Counting the loudest. The person who wrote twice about the address link is one person with one problem. Count messages and the persistent look like a crowd.

One request, promoted. A single request can matter a great deal. It still isn't "customers are asking for." Say "one customer asked."

Keep the disagreement

If a later report says the equipment instructions are clear, put it beside the two that say otherwise. It may come from a different version of the page. Evidence that doesn't fit is the part of a summary that keeps the rest believable.

Run it in your Staffmor office

Open the office on the computer running it with its Start Staffmor launcher. If you already have a paired web office, open it here. Paste this request and the source material into the conversation. Use your approved Codex connection, or ask your open Claude Code session to "Check Staffmor for work." A saved request is not a completed result. Review the answer or file when it comes back and reply with corrections. Ask for the groups with their labels first, and the recommendations second.

Staffmor groups what you give it. Deciding what to build stays with you. New to Staffmor? Set up your office with Codex or Claude Code and an empty folder. Use your own supported AI account and approve the download, office activation and local folder/network access during setup. Claude Code pickup is manual; keep that local session open.