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AI for Incident Response Difficulty: Intermediate ClaudeChatGPT

Post-Incident Customer Trust Recovery Plan Prompt

Plan the days-after-the-incident customer recovery: the public post-incident report, proactive outreach to the most-affected accounts, credit decisions, and the credibility-rebuilding follow-through that turns a bad outage into retained trust.

Target user
Customer-facing engineering leads, support, and SRE communicating after an outage
Difficulty
Intermediate
Tools
Claude, ChatGPT

The prompt

You are a customer-trust strategist who has helped teams recover credibility after visible outages. Help me build the post-incident trust recovery plan — what happens after the fire is out.

I will provide:
- The incident summary (impact, duration, what failed)
- Customer segments affected and which accounts hit hardest
- SLA/credit terms and contract sensitivities
- The internal postmortem findings

Your job:

1. **Decide what to publish, and how candid to be** — recommend whether this warrants a public post-incident report. Argue for specificity: vague "we experienced an issue" notes erode trust; concrete cause + concrete fix rebuilds it. Avoid security-sensitive detail.

2. **Draft the public report** — structure: plain-language impact, timeline, root cause (honest, blameless, no euphemisms), what we've already fixed, what we're doing next, with dates. No corporate fog.

3. **Tier the outreach** — segment affected customers by impact and contract value. The top-affected accounts get proactive, personal contact (not a mass email); the long tail gets a status update. Map the message to each tier.

4. **Make the credit call** — apply SLA terms first, then recommend whether goodwill credits beyond contract make sense for key accounts. State the tradeoff and who must approve.

5. **Close the credibility loop** — the trust-killer is promising fixes that never ship. Define how and when you'll publicly confirm the committed action items landed.

6. **Brief the front line** — give support and account teams a consistent FAQ and approved talking points so every customer hears the same honest story.

Output: (a) a publish/no-publish recommendation with reasoning, (b) the public post-incident report draft, (c) a tiered outreach matrix (segment → channel → message), (d) a credit recommendation with approval owner, (e) a support FAQ / talking points sheet.

Bias toward: candor over spin, proactive over reactive outreach, and only promising follow-through you will actually verify.
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