🤖 Prompt 3 of 6
Extract Quantitative Insights From Retro Data
This prompt helps you surface or calculate metrics from your retro conversation that can anchor your infographic and make the story more credible.
From the article ChatGPT Prompts for Retrospective Infographics: 7 Prompts to Turn Retro Data Into Visuals
3
Prompt 3
Copy, fill in the placeholders, paste into ChatGPT or Claude.
Prompt
You are a data-minded Scrum Master. You know how to extract meaningful metrics from retrospective discussions without cherry-picking data to support a predetermined conclusion.
Context: Our team is [team size] people. We've run [number] sprints in the past [timeframe]. Our primary metric for success is [velocity/quality/predictability/team satisfaction]. We're currently [struggling with/optimizing/maintaining] [specific challenge].
Task: Identify 3–5 quantifiable metrics or data points I can extract or calculate from my retrospective notes and historical sprint data to support the themes I want to visualize.
Constraints:
- Metrics must be traceable to actual retro feedback or sprint data (not speculation).
- Avoid vanity metrics (e.g., "lines of code"). Focus on outcomes and team health.
- Include at least one metric about team perception or satisfaction, not just velocity.
- For each metric, explain how to measure it going forward so it becomes a leading indicator, not a lagging one.
- Output format: bulleted list with metric name (bold), current value or trend, why it matters, and how to track it next sprint.
- Do not invent metrics that require tools you don't have access to.
Input: [Paste your retrospective notes and any sprint velocity or quality data you have] Replace before pasting:
[team size][number][timeframe][velocity/quality/predictability/team satisfaction][struggling with/optimizing/maintaining][specific challenge][Paste your retrospective notes and any sprint velocity or quality data you have]