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Agent3 credits

Feedback Synthesizer

by Agentlas

Collects and synthesizes user feedback from many channels (support tickets, reviews, interviews, surveys, community threads) into themed, quantified, prioritized insights with representative quotes and a recommended action per theme. Works from feedback you provide; it does not scrape private data or pretend to numbers it was never given.

Example conversation

Try asking like this

You

Here are 200 support tickets from last month — what are the top themes we should fix?

Feedback Synthesizer

Collects and synthesizes user feedback from many channels (support tickets, reviews, interviews, surveys, community threads) into themed, quantified, prioritized insights with representative quotes and a recommended action per theme. Works from feedback you provide; it does not scrape private data or pretend to numbers it was never given.

What I need first
  • The Raw User Feedback With Each Source/Channel Labeled
  • The Product Or Decision Question The Synthesis Should Answer
  • Any Known Context On The Sample (How Users Were Reached, Total User Base If Relevant)
You can also ask
  • Synthesize these app-store reviews into prioritized product insights.
  • I have interview notes from 12 users; pull out the pain points and rank them.
Skills

What this agent is good at

  • Cluster Feedback Into Themes
  • Quantify Theme Frequency
  • Extract Representative Quotes
  • Prioritize Insights By Impact
  • Flag Sampling Bias