Proposal: Intelligent User Feedback Pipeline for ChatGPT
Submitted by: User “봄빛” (Power User Insight)
Background
Current feedback collection in ChatGPT appears largely passive, with limited real-time response or structured routing. High-quality, actionable user insights (such as bug reports, rendering errors, session conflicts, etc.) may be diluted among general feedback, resulting in delayed or missed resolutions. A more intelligent, automated, and prioritized pipeline is needed.
Proposal Summary
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Critical Feedback Auto-Escalation ChatGPT should detect keywords/symptoms indicating potential bugs or UX errors. Example: “text is getting cut off,” “session crashed,” “audio prompt failed.” System flags these with high severity and automatically forwards them to internal engineering dashboards as Immediate Reports.
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Routine Feedback Aggregation & Summarization General suggestions, requests, usability complaints, etc., are logged continuously. System groups similar feedback and submits them weekly or monthly as Summary Reports to the product team. Includes heatmaps, trend data, and common suggestions.
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AI-Powered Feedback Classification GPT itself (or an internal classifier) evaluates incoming feedback: Severity (Critical / Moderate / Low) Type (Bug / UX / Feature Request / Clarification) Frequency (Isolated / Recurring / Trending) Result: a smart routing system that prioritizes what really matters.
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Special User Feedback Recognition Introduce “Trusted Feedback Contributor” tagging for insightful users. Feedback from these users is more heavily weighted or bypasses certain filters. Allows community-based signal boosting.
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Transparent Feedback Loop Once feedback is actioned or planned, notify the user: “Thanks, your feedback on ‘X’ helped us fix/update ___.” Builds trust, accountability, and user engagement. Benefits Faster response to real issues Prioritized attention on real user needs Encouragement for high-quality user engagement Less friction between real-world use and model iteration Final Note
This proposal comes from a high-context power user (봄빛) who has identified practical issues from real usage — such as rendering bugs and session instability — and who actively contributes strategic insight to make ChatGPT a more trusted, consistent, and professional assistant.
OpenAI’s continuous improvement depends on not just data, but dialogue. A structured feedback system is not just helpful — it is essential.