Customer feedback themes
Turn scattered feedback into a clear, calm dashboard of ranked themes and supporting evidence.
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When to use it
The prompt starts from the decision the dashboard supports, then constrains hierarchy, density, semantics, and responsive behavior.
Prompt
Design and implement a customer-feedback themes dashboard for [PRODUCT OR TEAM]. Inspect the current app conventions before editing. The page should help someone answer: what matters most, why, and what should we inspect next? Include a compact summary, ranked theme rows or cards, impact and trend signals, source counts, and a detail view with representative feedback. Use realistic, concise seed data. Favor an analytical editorial style: high information density without clutter, neutral surfaces, one semantic accent, aligned numbers, readable labels, and subtle separators. Do not rely on color alone. Make the highest-impact theme visually obvious while preserving scanability. Implement search, impact sorting, a time-range filter, theme selection, and empty/loading/error states. On narrow screens, preserve the ranking and core evidence instead of squeezing desktop columns. Use semantic tables or lists where appropriate, accessible controls, visible focus, and reduced-motion-friendly transitions. Do not copy source branding or text. Use the source output only as a quality and hierarchy reference. Test the interactions and render at [DESKTOP WIDTH] and [MOBILE WIDTH]. Report changed files, validation commands, and screenshots of the overview plus one selected theme.
Adapt it to your task
Adapted from Feedback Themes' grouped customer-signal interface and committed preview.
Third-party prompt. Source review does not establish benchmark performance or guarantee an outcome.
Reviewed source output
Source and license
Contributor: @jamesmontemagno. Repository: github/awesome-copilot.
License: MIT. Pinned commit: b95e24caae4f25c5985f8527fd092ccfed039c36.
Review: output-reviewed, . Reviewed the commit-pinned implementation and its committed preview image. The preview is representative source output, not a claim that this adapted prompt reproduces it pixel-for-pixel.