Metric Story Generator
Paste your raw product metrics and get a clear narrative — what changed, why it likely happened, and what to do next. No more staring at a dashboard trying to write the weekly update.
Numbers, percentages, trends — any format. One metric per line works best.
What your product is and any relevant recent changes — helps generate a more accurate narrative.
What you get
- Executive summary — one paragraph capturing the headline story
- What changed — key movements with directional framing (up/down, good/bad)
- Likely root causes — ranked hypotheses with reasoning
- Recommended next steps — specific, actionable, prioritised
- Signals to watch — leading indicators to monitor in the next cycle
Frequently asked questions
What kind of metrics can I paste?
Anything — DAU/MAU, churn, conversion rates, latency numbers, feature adoption, revenue metrics, NPS scores. The AI works with numbers in any format. One metric per line gives the cleanest output.
How is this different from asking ChatGPT?
This tool is purpose-built for product metric narratives. The prompt is structured to produce a specific format: what changed, likely root causes ranked by probability, and concrete next steps — not a generic summary.
Should I add context about my product?
Yes, if you want more accurate root cause analysis. Without context the AI makes plausible general guesses. With context (product type, recent changes, user base) it can make more specific, useful hypotheses.
Can I use this for a weekly PM report?
That's a common use case. Paste the week's key metrics, add a line of context, and get a narrative that explains the week to stakeholders — in a format they can actually read.
Connect your metrics to customer evidence
PMRead links product metrics to actual customer feedback — so your metric story says “DAU dropped because 8 customers flagged this specific pain” instead of guessing.
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