Dashboard for Quantifiable Insights in User Feedback
- Dominant language
- Python
- Stars
- 44.8k
- Forks
- 4.9k
- Avg merge
- 21h 10m
- Merged PRs (30d)
- 635
Description
### Problem Statement
User Feedback currently provides a chronological list of submissions, but it’s difficult to extract actionable insights from that format alone. It would be extremely helpful to have a dashboard or analytics view that surfaces quantifiable metrics from User Feedback so teams can better understand trends, prioritize work, and measure improvements over time.
Some example metrics that would be valuable:
- Issues per platform: Identify which platforms (e.g. web, iOS, Android) generate the most feedback or issues.
Trend of issues raised over time: A time-series view (e.g. daily/weekly/monthly) showing whether the volume of feedback is increasing or decreasing. This would help answer whether product quality is improving or regressing.
Issues by state (resolved vs unresolved): A breakdown showing how many feedback items are resolved versus still open. This would help teams track whether feedback is being actioned or accumulating.
Issues by tagged area (e.g. productArea): Many teams tag feedback to indicate product areas. Aggregating feedback by tag would make it easier to identify which areas of the product generate the most user issues.
### Solution Brainstorm
_No response_
### Product Area
Dashboards
Contributor guide
Research direction
No files, tests, or entry points are identified in the issue. Start by clarifying the dashboard scope and which metrics are required, then define completion around views for platform, time trends, resolution state, and tagged product areas.
Written by the indexing model from the issue text.
Assessment
- Domain
- analytics
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100