A data-driven analysis of churned client revenue loss from your Power BI environment, with breakdowns and actionable findings.
This report analyzes churned client revenue loss using data from Autotask PSA.
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: MSP owners, finance leads, and operations managers tracking profitability
How often: Monthly for financial reviews, quarterly for strategic planning, on-demand for pricing decisions
A data-driven analysis of churned client revenue loss from your Power BI environment, with breakdowns and actionable findings.
-- Combined summary metrics from Power BI dataset
Revenue breakdown by company from billing data
| Company | Type | Created | Last Activity | Lifetime Revenue |
|---|---|---|---|---|
| Colon-Nunez | Cancellation | 2024-07-12 | 2025-03-19 | €14,976 |
| Mcdonald, Green and Russell | Cancellation | 2024-07-12 | 2024-11-25 | €4,440 |
| Nguyen, Meyers and Beard | Cancellation | 2024-07-12 | 2025-11-24 | €4,256 |
| Khan-Thomas | Cancellation | 2024-07-12 | 2025-04-24 | €2,475 |
| Jackson-Benson | Customer (inactive) | 2024-07-12 | 2025-10-13 | €2,116 |
| Rogers, Rodriguez and Brown | Customer (inactive) | 2024-07-12 | 2025-02-25 | €330 |
| Robles Inc | Customer (inactive) | 2024-07-12 | 2025-02-25 | €94 |
| Perry, Boyer and Kelley | Cancellation | 2024-07-12 | 2024-11-22 | €59 |
| Long, Jarvis and Duncan | Customer (inactive) | 2024-07-12 | 2025-06-02 | €50 |
| 10 zero-revenue churn accounts | mixed | — | — | €0 |
EVALUATE
ADDCOLUMNS(
SELECTCOLUMNS(
FILTER('BI_Autotask_Companies', 'BI_Autotask_Companies'[company_type]="Cancellation" || ('BI_Autotask_Companies'[company_type]="Customer" && 'BI_Autotask_Companies'[status]=FALSE())),
"Company", 'BI_Autotask_Companies'[company_name],
"Type", 'BI_Autotask_Companies'[company_type],
"CreatedOn", FORMAT('BI_Autotask_Companies'[create_datetime], "yyyy-MM-dd"),
"LastActivity", FORMAT('BI_Autotask_Companies'[last_activity_datetime], "yyyy-MM-dd")
),
"LifetimeRev", COALESCE(CALCULATE([Revenue - Total]), 0)
)
ORDER BY [LifetimeRev] DESC
Monthly revenue trend over the observed period
| Month | Revenue |
|---|---|
| 202502 | €1,051,887 |
| 202503 | €1,106,650 |
| 202504 | €1,341,613 |
| 202505 | €1,080,821 |
| 202506 | €1,033,307 |
| 202507 | €1,045,558 |
| 202508 | €1,058,862 |
| 202509 | €1,002,352 |
| 202510 | €1,006,188 |
| 202511 | €927,812 |
| 202512 | €887,195 |
| 202601 | €770,865 |
EVALUATE TOPN(12, SUMMARIZECOLUMNS('BI_Common_Dim_Date'[year_month], "Revenue", SUM('BI_Autotask_Billing_Items'[total_amount])), 'BI_Common_Dim_Date'[year_month], DESC)
Distribution of contracts across types
| Type | Count |
|---|---|
| Recurring Service | 1,207 |
| Time & Materials | 504 |
| Block Hours | 173 |
| Fixed Price | 5 |
EVALUATE SUMMARIZECOLUMNS('BI_Autotask_Contracts'[contract_type_name], "Count", COUNTROWS('BI_Autotask_Contracts'))
What the data is telling us
The data above paints a picture of churned client revenue loss across your MSP operations. Look for patterns, outliers, and trends that warrant attention. Each section includes the DAX query used, so you can drill deeper into any metric that catches your eye.
Set up a weekly or monthly review of churned client revenue loss metrics. Trends matter more than snapshots. Use the DAX queries in this report as your starting point.
This report uses demo data. Connect Proxuma Power BI to your own Autotask PSA to generate this analysis from your real numbers.
This report pulls data from PSA through the Proxuma Power BI integration, using DAX queries against the live data model.
The underlying Power BI dataset refreshes daily. Reports can be regenerated at any time for the latest figures.
Yes. Proxuma reports are fully customizable. You can modify the DAX queries, add new sections, or adjust the analysis to match your specific MSP needs.
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