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N-able 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 N-able 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.

N-able N-central Built-in online reports plus optional Report Manager add-on with 50+ pre-built branded stock reports across network, security, patch, and help desk categories. 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 N-able's data exports.

N-able is best for: Larger MSPs managing complex, multi-tenant environments who need enterprise-grade automation and patching.

How to Use This Template

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

How to Export Ticket Data from N-able

To populate this report template with real data from N-able N-central, follow these steps to export your ticket data:

Navigate to Reports and select the desired report
Complete parameters and click View Report
Click Export at the bottom, select CSV format
For dashboards: Analytics > Dashboards, click ellipsis > Export as CSV or XLSX
Note: Data Export must be enabled in Admin Console first

API alternative: REST API (V2) with OAuth2 auth and Swagger documentation. Also supports legacy SOAP API.

Why N-able MSPs Need This Report

Built-in online reports plus optional Report Manager add-on with 50+ pre-built branded stock reports across network, security, patch, and help desk categories.

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

N-able Strengths

Enterprise-grade scalability for massive multi-tenant deployments
Most powerful patching engine in the RMM space
Deepest automation with layered policy inheritance (Organization > Customer > Site > Device)

Reporting Limitations

Scheduled reports are forced to run at 3 AM with no custom scheduling
Complex initial setup; overpriced for smaller MSPs

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N-able Ticket Analysis FAQ

How do I export ticket analysis data from N-able?

Navigate to Reports and select the desired report. Complete parameters and click View Report Click Export at the bottom, select CSV format See the full export guide above for detailed steps.

Does N-able have built-in client reporting?

Built-in online reports plus optional Report Manager add-on with 50+ pre-built branded stock reports across network, security, patch, and help desk categories. This template complements N-able'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 N-able?

N-able'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. N-able also offers REST API (V2) with OAuth2 auth and Swagger documentation. Also supports legacy SOAP API.

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.