Turn customer conversations into a weekly product signal
A weekly evidence pack groups recurring problems, affected segments, verbatim examples, and changes since last week.
The problem
Customer feedback is abundant but fragmented across calls, tickets, chats, and account-team memory.
What you get
A working system with the steps, tools, checkpoints, and expected return made explicit.
- Setup
- 150 minutes
- Back each week
- 5 hours
- Difficulty
- agentic
Expected return
The working case
A planning estimate, not a guaranteed result. Measure the first four weeks against your own baseline.
240
hours returned per year
At 5 hours/week across 48 working weeks.
1
week to earn back setup
Compare the setup estimate with the weekly time returned.
Operating contract
Input
The source material, constraints, and examples a human would need to do this work well.
Checkpoint
A person reviews judgment calls, sensitive content, unfamiliar tools, and irreversible actions.
Success signal
Track time returned, corrections required, and exceptions. Keep it only if the measured result compounds.
Before you start
- ·Feedback taxonomy owner
- ·Approved retention and access policy
The steps
- 01
Define approved feedback sources, redaction rules, taxonomy, and the minimum count for calling something a pattern.
- 02
Normalize feedback into problem, context, segment, severity, source, and date.
- 03
Cluster similar problems while preserving links to every underlying example.
Copy this prompt
Group these feedback items by customer problem, not requested feature. For each cluster: count, segments, severity evidence, representative verbatim excerpts, source links, and change from last period. Do not rank from sentiment alone. Items: [feedback]
- 04
Product and CS review the pack; decisions are made by humans and linked back to evidence.
What it runs on
Where this goes wrong
- Frequency is not the same as commercial importance.
- Redact personal and confidential customer information before model processing.
Definition of done
Run it for four weeks. Then make it earn its place.
- □ Baseline the manual time before launch.
- □ Keep a human approval step for consequential output.
- □ Record corrections and exceptions, not just successes.
- □ Expand, revise, or retire it after the first review.
Build the system around it
Related workflows
If this one stops working, tell us. Three reports in a month and it leaves the library until a person has looked at it again.