Auto-Request Feedback

Persona

Product Manager / Community Lead / Indie Builder
Motivated to build better products by staying close to early users, but lacks time and structure to consistently collect and prioritize user feedback across public platforms like Twitter/X.

Problem

Users often reply to product announcement or update tweets with complaints, bugs, or feature suggestions.
However:

• These replies are scattered, unstructured, and hard to track.

• Valuable feedback often gets buried or missed.

• There's no quick way to prioritize input based on who said it (e.g. power users, influencers).

• Teams lack a systematic way to turn replies into actionable insights.

Solution

Build an Auto-Request Feedback agent that works as follows:

1. Trigger: After a product update or prompt tweet is posted, the system automatically tracks replies and quote tweets.

2. Collection: Gathers all relevant user replies containing feedback, suggestions, or complaints.

3. Prioritization:

   • Uses engagement metrics (likes, retweets) and user metadata (follower count, prior interactions) to rank replies by influence and relationship.

4. Processing:

   • Clusters similar feedback.

   • Identifies themes (e.g. bugs, usability, feature request).

5. Output:

   • Generates an actionable report with:

     • Ranked list of user feedback

     • Suggested product responses or actions

     • Option to one-click reply or acknowledge in-thread.