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Atera Ticket Analysis Report Template for MSPs

Deep-dive analysis of support ticket patterns, categories, resolution efficiency, and workload distribution to optimize MSP service delivery.

What's Included

  • Ticket Volume Overview
  • Category Breakdown
  • Priority Distribution
  • Resolution Time by Category
  • Recurring Issues Analysis
  • Technician Workload Distribution
  • Efficiency Recommendations

Why Atera MSPs Need a Ticket Analysis

Ticket analysis reveals patterns your team might miss in daily firefighting. It helps you identify recurring issues to fix permanently, balance technician workload, and make data-driven staffing decisions.

Atera Preset reports for hardware, ticketing, patches, and technician overview. Custom analytics (Explore) only on Power tier and above. However, these built-in reports are typically designed for internal operations — not for client communication. This template bridges that gap with a professional, client-ready format structured around Atera's data exports.

Atera is best for: Small MSPs and solo technicians who want simple setup with unlimited device management at a flat per-tech price.

How to Use This Template

  1. Export ticket data from your PSA for the analysis period
  2. Categorize tickets by type, priority, and resolution method
  3. Identify the top 5 recurring issues and their total time cost
  4. Analyze technician utilization and identify bottlenecks
  5. Generate recommendations for process improvements

How to Export Ticket Data from Atera

To populate this report template with real data from Atera, follow these steps to export your ticket data:

  1. Navigate to the Reports tab in the Atera console
  2. Select Ticketing Summary or Customer Tickets Overview
  3. Set the date range and client filters
  4. Click Export and choose CSV or Excel format
  5. Note: full ticket history requires per-ticket API calls

API alternative: REST API with Swagger V3 documentation. X-API-KEY auth, 700 requests/minute limit.

Why Atera MSPs Need This Report

Preset reports for hardware, ticketing, patches, and technician overview. Custom analytics (Explore) only on Power tier and above.

This template fills the gap by providing a professional, client-ready ticket analysis report format that you can populate with data exported from Atera.

Atera Strengths

  • Per-technician pricing with unlimited devices — most predictable cost model
  • AI Copilot auto-resolves up to 85% of L1 tickets
  • Fastest setup: cloud-native, no on-prem, single-pane for RMM+PSA

Reporting Limitations

  • Reporting lacks customization depth compared to enterprise tools
  • Bulk CSV export of tickets is not available from the web UI — requires Reports or API

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Atera Ticket Analysis FAQ

How do I export ticket analysis data from Atera?
Navigate to the Reports tab in the Atera console. Select Ticketing Summary or Customer Tickets Overview Set the date range and client filters See the full export guide above for detailed steps.
Does Atera have built-in client reporting?
Preset reports for hardware, ticketing, patches, and technician overview. Custom analytics (Explore) only on Power tier and above. This template complements Atera's built-in reporting by providing a professional, client-ready format that non-technical stakeholders can easily understand.
Can I automate this ticket analysis with Atera?
Atera's built-in automation can schedule data exports, but assembling a professional client-facing report still requires manual formatting. This template handles the presentation layer — you provide the data. Atera also offers REST API with Swagger V3 documentation. X-API-KEY auth, 700 requests/minute limit.
How often should I run ticket analysis?
Monthly at minimum, weekly for high-volume environments. The more frequently you analyze, the faster you catch emerging patterns.
What's a healthy ticket resolution time?
For MSPs: critical tickets under 4 hours, high priority under 8 hours, normal under 24 hours. But your SLA targets should define your specific benchmarks.
How do I identify recurring issues?
Group tickets by category and search for patterns. If the same issue appears 3+ times in a month, it's a candidate for a permanent fix or automation.
Should I share ticket analysis with clients?
Share a summarized version highlighting improvements and proactive work. Keep the internal operational details for your team's eyes only.