SupportSupport Operations Specialistbeginner 5 min saved

Customer Support Ticket Summarizer

Instantly distill verbose customer messages into a structured, actionable three-bullet summary for faster triage.

Customise & copy

Add the context you have. The prompt updates as you work.

Customer Message *

The raw support message, email, chat log, or ticket transcript.

Urgency Level *

Select the perceived urgency of the ticket.

Context Notes

Any optional internal context, product version, or account tier.

Live prompt

3 fields

Analyze the following customer support message and extract a standardized three-bullet summary.

Raw Customer Message:
{{customer_message}}

Urgency Level:
Medium

Context Notes:
{{context_notes}}

Rules:
- Output must contain exactly three distinct bullets in this exact format:
  - Problem: [Clear, concise description of the core issue]
  - What they tried: [Summary of troubleshooting steps already taken, or state "None mentioned" if absent without inventing details]
  - What they want: [Explicit statement of the desired outcome or resolution]
- Do not include extraneous conversational filler, greetings, or sign-offs.

Proof before you use it

A real example

Tested on gemini-3.1-flash-lite on 2026-09-04

{
  "context_notes": "SaaS analytics platform user",
  "urgency_level": "High",
  "customer_message": "Hey support team, I've been trying to export my monthly analytics report since Tuesday, but every time I click the CSV export button, the page just refreshes and logs me out. I tried clearing my cache, switching from Chrome to Safari, and even resetting my password. I really need this report fixed today for our board meeting tomorrow!"
}

A small ritual that works

How to use it

01Paste the raw customer message into the 'Customer Message' field.
02Select the appropriate urgency level from the dropdown.
03Add any relevant account context or version notes.
04Run the prompt to generate a clean, standardized summary for your ticketing system.

Why it works

The prompt establishes strict structural constraints by explicitly defining a three-bullet output format (Problem, What they tried, What they want) and providing exact fallback language ('None mentioned') for missing information. It also leverages contextual inputs (urgency level and context notes) alongside the raw message to inform the extraction.

Where it fails

INSUFFICIENT_EVIDENCE

Customisation tips

You can add more specific categorization tags under the rules section if your ticketing system requires tagging by product module, sentiment, or impact category alongside the three bullet points.

Watch-outs

Failing to enforce the exact bullet prefixes ('- Problem:', '- What they tried:', '- What they want:') will break downstream parsers that rely on strict string matching.
Leaving the context notes empty when processing complex multi-system issues may result in summaries that lack necessary technical environment details.