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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

  1. Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
  2. Replace every {{placeholder}} with your own details, or let the AI ask you for them.
  3. Use the follow-ups below to go deeper.
Prompt

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

  1. Ask for any missing inputs, then wait for answers before drafting.
  2. Separate signal from noise: state what the data supports and what it does not.
  3. Build a short narrative covering what changed, for whom, when it started, and what else moved at the same time.
  4. Offer two or three plausible explanations, each with evidence for and against, and label every assumption.
  5. State the customer impact in plain language and connect it to the business impact provided.
  6. Give a response plan with owner, timing and the next metric check.
  7. 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.