A data-driven analysis of client revenue month over month from your Power BI environment, with breakdowns and actionable findings.
This report analyzes client revenue month over month 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 client revenue month over month from your Power BI environment, with breakdowns and actionable findings.
EVALUATE
ROW(
"Top 15 Revenue", SUMX(TOPN(15, SUMMARIZECOLUMNS('BI_Autotask_Companies'[company_name], "Rev", SUM('BI_Autotask_Billing_Items'[total_amount])), [Rev], DESC), [Rev]),
"Total Contracts", COUNTROWS('BI_Autotask_Contracts'),
"Contract Types", DISTINCTCOUNT('BI_Autotask_Contracts'[contract_type_name])
)Revenue breakdown by company from billing data
| Company | Revenue |
|---|---|
| Craig-Huynh | €2,324,617 |
| Lewis LLC | €2,212,915 |
| Little Group | €1,431,177 |
| Martin Group | €637,092 |
| Lopez-Reyes | €589,694 |
| Wall PLC | €476,622 |
| Burke, Armstrong and Morgan | €469,660 |
| Patterson, Riley and Lawson | €416,450 |
| Richards, Bell and Christensen | €328,165 |
| Wu-Jackson | €321,669 |
| Thompson, Contreras and Rios | €320,832 |
| Price-Gomez | €286,926 |
| Torres-Jones | €255,698 |
| Hahn Group | €253,148 |
| Montgomery-Peck | €214,469 |
EVALUATE
TOPN(15, SUMMARIZECOLUMNS('BI_Autotask_Companies'[company_name], "Revenue", SUM('BI_Autotask_Billing_Items'[total_amount])), [Revenue], DESC)
ORDER BY [Revenue] DESCMonthly revenue trend over the observed period
| Month | Revenue |
|---|---|
| 202502 | €1,051,887 |
| 202503 | €1,106,651 |
| 202504 | €1,341,613 |
| 202505 | €1,080,822 |
| 202506 | €1,033,307 |
| 202507 | €1,045,558 |
| 202508 | €1,058,862 |
| 202509 | €1,002,352 |
| 202510 | €1,006,189 |
| 202511 | €927,813 |
| 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)
ORDER BY 'BI_Common_Dim_Date'[year_month] ASCDistribution 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'))
ORDER BY [Count] DESCWhat the data is telling us
The data above paints a picture of client revenue month over month 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 client revenue month over month 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.
Connect Proxuma Power BI to your PSA, RMM, and M365 environment, use an MCP-compatible AI to ask questions, and generate custom reports - in minutes, not days.
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