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Claude for Operators

Customer Support Automation

Last verified: 14 February 2026 | Applies to: Team, Enterprise (Customer Support plugin; connectors for ticketing tools)

In 30 seconds

Section titled “In 30 seconds”

Support teams spend most of their time on tasks that follow a pattern — categorising tickets, drafting first responses, escalating edge cases, and producing weekly reports. The Customer Support plugin automates the repetitive parts so your team can focus on the conversations that actually need a human. This workflow covers ticket triage, response drafting, trend analysis, and quality monitoring, and it requires a Team or Enterprise plan.

What it does

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The Customer Support plugin gives Claude the context and structure to handle support operations:

  • Ticket categorisation — automatically classify incoming tickets by topic, urgency, and complexity
  • Response drafting — produce draft replies that follow your tone guide and reference your knowledge base
  • Escalation routing — flag tickets that need senior attention or specialist knowledge
  • Trend analysis — identify recurring issues, emerging problems, and patterns across your ticket volume
  • Quality reports — review a sample of closed tickets against your quality standards and produce a scorecard
  • Knowledge base maintenance — identify gaps in your help docs based on what customers keep asking about

Claude doesn’t send responses automatically. Every draft goes through a human before it reaches the customer. The goal is to reduce the time from ticket received to human-reviewed response — not to remove the human.

How to set it up

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Step 1: Install the plugin and connect your tools

Section titled “Step 1: Install the plugin and connect your tools”

Install the Customer Support plugin from claude.com/plugins. Then connect your ticketing tool via MCP if available.

With a connector: Claude reads tickets directly from your queue. This is the best experience — live data, no copy-pasting.

Without a connector: You can still use the plugin by exporting tickets as a CSV or copying ticket details into the conversation. Less seamless, but still useful.

Step 2: Seed your support context

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Give Claude the information it needs to handle your tickets properly:

Our product: [Product name] — a project management tool for construction companies. Pricing: Starter ($99/month), Professional ($199/month), Enterprise ($499/month).


Support tiers:
- Tier 1: Password resets, login issues, basic how-to questions. Target first response: 2 hours.
- Tier 2: Feature configuration, integration troubleshooting, billing disputes. Target first response: 4 hours.
- Tier 3: Data issues, system errors, security concerns. Escalate to engineering immediately.


Tone: Friendly, helpful, no jargon. We use first names. We never say "unfortunately" — reframe as what we CAN do. Sign off with the agent's first name, not "The Support Team."


Common issues right now:
- Users having trouble with the new calendar sync feature (launched 2 weeks ago — known bugs being fixed)
- Confusion about the new pricing tier for teams over 20 users
- Occasional slow load times on the project dashboard (infrastructure team investigating)


Escalation rules:
- Any mention of data loss → Tier 3 immediately
- Any mention of cancellation → flag for account manager, respond within 1 hour
- Any legal or compliance question → flag for legal team, do not attempt to answer

Step 3: Test with real tickets

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Start with a small batch to calibrate:

Here are 10 recent support tickets [paste or upload]. For each one:
1. Categorise by topic and tier
2. Rate urgency (low / medium / high / critical)
3. Draft a response following our tone guide
4. Flag any that should be escalated


Let me review before we scale this up.

Review Claude’s categorisation and drafts. Adjust your context prompt based on what it gets right and what needs correcting. This calibration step is worth doing properly — it sets the quality bar for everything that follows.

How operators actually use it

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Daily ticket triage

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The core workflow for support managers:

Pull today's open tickets from our queue. Categorise each one and give me a triage summary:
- Critical tickets that need immediate attention
- Tier 2 tickets with draft responses ready for review
- Tier 1 tickets with draft responses ready for review
- Tickets that need more information from the customer (draft a follow-up question for each)


For each draft response, include the ticket number and a confidence rating — how certain are you this response fully addresses the issue?

Claude returns a prioritised list with drafts attached. Your support agents review the drafts, personalise where needed, and send. The Tier 1 tickets — which typically make up 60-70% of volume — get handled in a fraction of the usual time.

Response drafting for common issues

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Draft a response to this ticket:


"Hi, I'm trying to sync my project calendar with Google Calendar but nothing shows up. I followed the instructions in your help docs but the sync button is greyed out. I'm on the Professional plan. This is urgent because I have a client meeting tomorrow and need the schedule."


Follow our tone guide. Reference the known calendar sync bug if applicable. Offer a workaround if one exists. Don't promise a fix date — engineering hasn't given us one yet.

Claude drafts a response that:

  • Acknowledges the urgency without overpromising
  • References the known issue (because you seeded that context)
  • Offers a practical workaround
  • Sets expectations about the fix timeline
  • Follows your tone guide

Weekly trend analysis

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Analyse all tickets from the past 7 days. Tell me:
1. Total ticket volume — up or down compared to last week?
2. Top 5 ticket categories by volume
3. Average first response time by tier — are we hitting SLA targets?
4. Emerging issues — anything new this week that wasn't in last week's top 10?
5. Customer sentiment — are tickets getting more frustrated or less?
6. Repeat contacts — customers who submitted 3+ tickets this week


Give me a summary I can share with the leadership team. Keep it under 500 words. Lead with the most important finding.

This is the report most support managers wish they had time to produce every week. Claude analyses the ticket data and surfaces patterns that would take hours to find manually.

Quality scorecard

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Review a random sample of 20 closed tickets from last week. Score each one against our quality criteria:
1. Was the initial categorisation correct?
2. Was the response within SLA for its tier?
3. Did the response fully address the customer's question?
4. Was the tone consistent with our guide?
5. Was the ticket resolved in one touch, or did it require follow-up?


Produce a scorecard with an overall quality percentage and flag any tickets that scored below 3/5 on any criterion. Include specific feedback for each flagged ticket — what should the agent have done differently?

Knowledge base gap analysis

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Review all tickets from the past month and compare them against our help docs at [URL or uploaded file]. Identify:
1. Questions customers ask that our help docs don't answer
2. Help docs that exist but customers clearly can't find (they ask about topics we've already documented)
3. Help docs that are outdated — customer questions reveal the docs don't match current product behaviour
4. The top 5 help articles we should create or update first, ranked by ticket volume they'd deflect

This turns your ticket data into a knowledge base improvement roadmap. Most support teams know their docs have gaps but don’t have time to systematically identify them.

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