“N-able RMM Customer State Tracker”
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N-able RMM Customer State Tracker

Analysis and reporting on customer state tracker - active vs inactive for managed service providers.

Built from: N-able Cove
How this report was made
1
Autotask PSA
Multiple data sources combined
2
Proxuma Power BI
Pre-built MSP semantic model, 50+ measures
3
AI via MCP
Claude or ChatGPT writes DAX queries, executes them, formats output
4
This Report
KPIs, breakdowns, trends, recommendations
Ready in < 15 min

N-able RMM Customer State Tracker

Analysis and reporting on customer state tracker - active vs inactive for managed service providers.

The data covers the full scope of Autotask PSA records relevant to this analysis, broken down by the key dimensions your team needs for day-to-day decisions and client reporting.

Who should use this: Account managers, MSP owners, and service delivery leads

How often: Monthly for client reviews, quarterly for QBRs, on-demand when client signals change

Time saved
Cross-referencing client data from multiple tools manually takes hours. This report brings it together.
Client intelligence
See the full picture of each client across service, satisfaction, and commercial metrics.
Retention data
Early warning signals for at-risk clients, backed by actual data instead of gut feeling.
Report categoryClient Management
Data sourceAutotask PSA · Datto RMM · Datto Backup · Microsoft 365 · SmileBack · HubSpot · IT Glue
RefreshReal-time via Power BI
Generation timeUnder 15 minutes
AI requiredClaude, ChatGPT or Copilot
AudienceAccount managers, MSP owners
Where to find this in Proxuma
Power BI › Client Management › N-able RMM Customer State Tracker
What you can measure in this report
Summary Metrics
Active by Client
Customer State Tracker Trend (3 Quarters)
Risk Comparison View
Detailed Breakdown
Portfolio Health Overview
Key Findings
Strategic Recommendations
Frequently Asked Questions
Active
Inactive
Newly Active
AI-Generated Power BI Report
N-able RMM Customer State Tracker

Analysis and reporting on customer state tracker - active vs inactive for managed service providers.

Demo Report: This report uses synthetic data to demonstrate AI-generated insights from Proxuma Power BI. The structure, DAX queries, and analysis reflect real MSP data patterns.
1.0 Summary Metrics
Active
218
92.4% of customers
Inactive
18
No activity 60d+
Newly Active
12
Last 30 days
At Risk
8
Declining activity
View DAX Query - Summary Metrics
EVALUATE
ROW(
    "Active", COUNTROWS(BI_Nable_Rmm_Customers),
    "Inactive", CALCULATE(COUNTROWS(BI_Nable_Rmm_Customers), BI_Nable_Rmm_Customers[status] = "Active")
)
2.0 Active by Client

Breakdown of active vs inactive across managed clients.

Lewis LLC
218
Martin Group
83
Wall PLC
71
Ramos Group
59
Hahn Group
47
Anderson Group
35
ClientActiveInactiveNewly ActiveAt RiskStatus
Lewis LLC21818128Good
Martin Group20117117Good
Wall PLC18315107Warning
Ramos Group1661496Warning
Hahn Group1481285Critical
Anderson Group1311175Good

Lewis LLC leads across most metrics in this analysis. Hahn Group shows the weakest performance and should be flagged for a dedicated review. The gap between top and bottom performers suggests an opportunity to standardize processes across the portfolio.

View DAX Query - Active by Client
EVALUATE
SUMMARIZECOLUMNS(
    BI_Nable_Rmm_Customers[company_name],
    "Active", COUNTROWS(BI_Nable_Rmm_Customers),
    "Inactive", CALCULATE(COUNTROWS(BI_Nable_Rmm_Customers), BI_Nable_Rmm_Customers[status] = "Active")
)
ORDER BY [Active] DESC
3.0 Customer State Tracker Trend (3 Quarters)

How active vs inactive has evolved over the past three quarters.

Q1 2026
87.4%
Q4 2025
84.2%
Q3 2025
81.8%
StateCount
(not set)109

The portfolio shows steady improvement over three quarters, with the primary metric increasing from 81.8% to 87.4%. This 5.6 percentage point gain reflects ongoing optimization efforts. To maintain this trajectory, continue the current remediation cadence and expand coverage to newly onboarded clients.

View DAX Query - Customer State Tracker Trend (3 Quarters)
EVALUATE SUMMARIZECOLUMNS('BI_NAble_Customer'[state], "CustomerCount", COUNTROWS('BI_NAble_Customer'))
4.0
Risk Comparison View
Categorizing entities by key risk indicators.
HIGH RISK
4 entities
Performance significantly below portfolio average. Immediate action required.
MODERATE RISK
7 entities
Performance below target but stable. Review within 2 weeks.
LOW RISK
12 entities
Performance above target level. Standard monitoring sufficient.
NOT ASSESSED
3 entities
Insufficient data available for risk assessment.

The risk matrix shows that most entities fall in the low-risk category, but the high-risk group demands immediate attention. The moderate-risk group shows a declining trend that could escalate without intervention.

5.0
Detailed Breakdown
Granular data across all entities.
CategoryItemsPrimarySecondaryStatus
Category A23494.2%14Healthy
Category B18789.3%20Review
Category C15691.7%13Healthy
Category D9886.7%13Review
Category E6782.1%12At Risk
Category F4595.6%2Healthy

The detailed breakdown shows clear performance differences. The bottom two categories require targeted action to improve overall portfolio health.

6.0
Portfolio Health Overview
Key health indicators across all dimensions.
92.4% health score
Portfolio Health
87.3% of 100%
Coverage
23 action items
Open Items

Overall portfolio health is strong at 92.4%, but the 87.3% coverage rate suggests that roughly 1 in 8 entities is not fully monitored. The 23 open action items represent a manageable backlog if addressed within 2 weeks.

7.0
Key Findings
!

Performance Gap Requires Attention

The gap between top and bottom performers is wider than expected. The bottom 20% scores more than 25 percentage points below the portfolio average, indicating structural issues that require targeted intervention.

!

Declining Trend in Moderate Risk Group

Entities in the moderate risk category show a declining trend over the past quarter. Without intervention, 3-4 of these entities may shift to the high-risk category within 60 days.

Top Performers Remain Consistent

The top 30% of the portfolio maintains stable performance above target, indicating current best practices are effective and can serve as a model for the rest.

8.0
Strategic Recommendations

1. Conduct a targeted review of all high-risk entities within 2 weeks. Document the root cause for each entity and create a remediation plan with clear deadlines and accountable owners.

2. Implement automated monitoring for the moderate-risk group. Set thresholds that trigger an alert when performance drops 5 percentage points below target, enabling early intervention before entities slip into high risk.

3. Schedule this report monthly as part of the QBR process. Use the trend data to verify that improvement initiatives are delivering measurable results across multiple quarters.

9.0
Frequently Asked Questions
What does Active measure?

Active tracks the key performance indicator for active vs inactive. It is calculated based on data from N-able RMM and refreshed daily.

How often is this report updated?

Data syncs every 24 hours from N-able RMM. The report reflects the most recent complete data set.

What should we do about poor performers?

Schedule a dedicated review for any client falling below the portfolio average. Create an action plan with specific remediation steps and follow up within 2 weeks.

Can we use this in QBR presentations?

Yes. This report is designed to be QBR-ready. Export the key metrics and trend data to include in your quarterly business review slide deck.

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