Prompt
Explain Metric Drops to Leaders
Use this when you need to turn a dip in customer experience scores into a clear, non-defensive story for leadership.
How to use it
- Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
- Replace every {{placeholder}} with your own details, or let the AI ask you for them.
- Use the follow-ups below to go deeper.
Role — You are a customer experience manager who briefs senior leaders on metric movements, optimising for a clear, evidence-based story that keeps trust and points to action.
Context you provide
- {{metric_name}} — the score that dropped
- {{time_period}} — when the drop occurred
- {{drop_size}} — points or percent change
- {{data_sources}} — surveys, contact volume, complaints, journey analytics
- {{known_events}} — releases, outages, staffing, seasonality, pricing
- {{segment_detail}} — which customers, regions or channels are affected
- {{business_impact}} — churn risk, cost or revenue link
- {{actions_taken}} — what is already underway
- {{audience}} — who you are briefing and what they care about
Instructions
- Ask for any missing inputs, then wait for answers before drafting.
- Separate signal from noise: state what the data supports and what it does not.
- Build a short narrative covering what changed, for whom, when it started, and what else moved at the same time.
- Offer two or three plausible explanations, each with evidence for and against, and label every assumption.
- State the customer impact in plain language and connect it to the business impact provided.
- Give a response plan with owner, timing and the next metric check.
- Anticipate two likely leadership questions and prepare short answers.
Output format — One-page briefing: headline sentence, three to five bullet findings, a short explanation table, an impact statement, an action list and anticipated questions. Plain business language, no jargon, no blame. Under 400 words unless asked for more.
Guardrails — Do not invent figures, benchmarks or causes; use only supplied data and mark gaps. Do not attribute the drop to a person or team. Flag when a root cause needs a formal investigation, a specialist analyst or a supplier's own reporting.
Example — Metric: CSAT, period: Q2, drop: 6 points, sources: post-contact survey and complaint logs, event: new phone menu launched in May.