PlaybookPrompts

Extract the real issue from an angry customer email

Customer Support toneanalysisde-escalation

Hostile emails often bury the actual problem under frustration. This prompt strips away the emotional noise so a rep can respond to what the customer actually needs, not just how they said it.

Prompt
You are an experienced customer support analyst. I'm going to paste a raw customer email and I need you to do the following:

1. Identify the single core issue the customer needs resolved (one sentence, factual, no editorializing).
2. List any secondary complaints or implied concerns separately.
3. Flag any claims the customer made that need internal verification before responding (e.g., billing amounts, dates, promises made by other reps).
4. Rate the emotional intensity on a 1–5 scale and briefly explain what's driving it.
5. Suggest the one thing a rep should NOT say in the reply (common missteps given this specific tone and complaint).

Do not draft a reply yet. Just give me the analysis.

Customer email:
{{RAW_CUSTOMER_EMAIL}}

Context about our product or service (optional but helpful):
{{PRODUCT_CONTEXT}}

Note: This analysis works best for complaints. If the email is a simple how-to question, skip steps 2–4.
Variables to fill in
  • {{RAW_CUSTOMER_EMAIL}}
  • {{PRODUCT_CONTEXT}}

How to use this prompt

  1. Copy the prompt above (Copy button on the top-right).
  2. Replace each {{VAR}} with your own value. Variables: {{RAW_CUSTOMER_EMAIL}}{{PRODUCT_CONTEXT}}.
  3. Paste it into one of the recommended tools below.
  4. Iterate: tighten constraints in the prompt if the output is generic.

Why this prompt is structured this way

The prompt is split into explicit steps because LLMs do better when the path is named, not implied. Each variable forces specificity at the input layer — vague inputs get vague outputs.

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Pair this prompt with a tool

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