Growth trajectory, churn analysis, and portfolio health for your MSP client base.
Growth trajectory, churn analysis, and portfolio health for your MSP client base.
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
Growth trajectory, churn analysis, and portfolio health for your MSP client base.
Key metrics for your entire client base at a glance.
EVALUATE
ROW(
"TotalCustomers", COUNTROWS(
FILTER('BI_Autotask_Companies',
'BI_Autotask_Companies'[company_type] = "Customer")),
"ActiveCustomers", COUNTROWS(
FILTER('BI_Autotask_Companies',
'BI_Autotask_Companies'[company_type] = "Customer"
&& 'BI_Autotask_Companies'[status] = TRUE())),
"InactiveCustomers", COUNTROWS(
FILTER('BI_Autotask_Companies',
'BI_Autotask_Companies'[company_type] = "Customer"
&& 'BI_Autotask_Companies'[status] = FALSE())),
"Cancellations", COUNTROWS(
FILTER('BI_Autotask_Companies',
'BI_Autotask_Companies'[company_type] = "Cancellation")),
"ChurnRate", DIVIDE(
COUNTROWS(FILTER('BI_Autotask_Companies',
'BI_Autotask_Companies'[company_type] = "Customer"
&& 'BI_Autotask_Companies'[status] = FALSE()))
+ COUNTROWS(FILTER('BI_Autotask_Companies',
'BI_Autotask_Companies'[company_type] = "Cancellation")),
COUNTROWS(FILTER('BI_Autotask_Companies',
'BI_Autotask_Companies'[company_type] = "Customer"))
+ COUNTROWS(FILTER('BI_Autotask_Companies',
'BI_Autotask_Companies'[company_type] = "Cancellation"))
)
)How many clients were added and lost each year.
| Year | New Clients | Cancellations | Net Growth |
|---|---|---|---|
| 2021 | 1 | 0 | +1 |
| 2024 | 297 | 10 | +287 |
| 2025 | 29 | 1 | +28 |
The bulk of client onboarding happened in 2024 (297 new clients), with 2025 showing a more stable, steady intake of 29 new clients through December. The cancellation rate stays low: 10 exits in 2024 and just 1 in 2025.
EVALUATE
ADDCOLUMNS(
GENERATESERIES(2020, 2026, 1),
"NewClients",
VAR _yr = [Value]
RETURN COUNTROWS(
FILTER('BI_Autotask_Companies',
'BI_Autotask_Companies'[company_type] = "Customer"
&& YEAR('BI_Autotask_Companies'[create_date]) = _yr)),
"Cancellations",
VAR _yr = [Value]
RETURN COUNTROWS(
FILTER('BI_Autotask_Companies',
'BI_Autotask_Companies'[company_type] = "Cancellation"
&& YEAR('BI_Autotask_Companies'[create_date]) = _yr))
)
ORDER BY [Value]New client onboarding by month for the current year.
| Month | New Clients | Distribution |
|---|---|---|
| Jan 2025 | 5 | |
| Feb 2025 | 6 | |
| Mar 2025 | 3 | |
| Apr 2025 | 0 | |
| May 2025 | 1 | |
| Jun 2025 | 2 | |
| Jul 2025 | 4 | |
| Aug 2025 | 1 | |
| Sep 2025 | 3 | |
| Oct 2025 | 3 | |
| Nov 2025 | 1 | |
| Dec 2025 | 0 |
Monthly intake in 2025 averages about 2.4 new clients per month. The highest intake months are January through March (Q1) and July (mid-year). April and December show zero or near-zero intake, which aligns with typical MSP seasonality patterns.
EVALUATE
ADDCOLUMNS(
GENERATESERIES(1, 12, 1),
"MonthName", FORMAT(DATE(2025, [Value], 1), "MMM"),
"NewIn2024", COUNTROWS(
FILTER('BI_Autotask_Companies',
'BI_Autotask_Companies'[company_type] = "Customer"
&& YEAR('BI_Autotask_Companies'[create_date]) = 2024
&& MONTH('BI_Autotask_Companies'[create_date]) = [Value])),
"NewIn2025", COUNTROWS(
FILTER('BI_Autotask_Companies',
'BI_Autotask_Companies'[company_type] = "Customer"
&& YEAR('BI_Autotask_Companies'[create_date]) = 2025
&& MONTH('BI_Autotask_Companies'[create_date]) = [Value]))
)
ORDER BY [Value]The initial onboarding year, including the bulk import event in July.
| Metric | Value | % |
|---|---|---|
| Total Companies | 550 | — |
| Active | 531 | 96.5% |
| With Contracts | 283 | 51.5% |
| With Tickets | 265 | 48.2% |
July 2024 stands out as the single largest onboarding month with 273 new clients. This suggests a major migration event or bulk import, likely from a previous PSA or CRM system. After that initial wave, the monthly intake normalizes to single digits.
Current status breakdown across all customer records.
| Status | Count | Percentage |
|---|---|---|
| Active Customers | 319 | 97.3% |
| Inactive Customers | 9 | 2.7% |
| Cancelled (separate type) | 11 | 3.2% |
With 97.3% of clients still active, the retention rate is strong. The 9 inactive customers plus 11 cancellations together make up about 5.9% of all customer-type records. Several of those cancellations have the status flag set to "true," which could mean they were reactivated or the flag is not consistently maintained.
Your highest-billing accounts and their ticket volume.
| # | Client | Revenue | Tickets | Status |
|---|---|---|---|---|
| 1 | Peterson Inc | €2,324,617 | 5,458 | Active |
| 2 | Martinez Group | €2,212,915 | 1,758 | Active |
| 3 | Sullivan Corp | €1,431,177 | 5,290 | Active |
| 4 | Anderson Ltd | €637,092 | 2,775 | Active |
| 5 | Harper Solutions | €589,694 | 1,317 | Active |
| 6 | Wall PLC | €476,623 | 2,376 | Active |
| 7 | Collins, Rivera and Shaw | €469,660 | 1,629 | Active |
| 8 | Fisher, Burke and Cole | €416,450 | 14 | Active |
| 9 | Davis Consulting | €321,669 | 914 | Active |
| 10 | Barnes, Contreras and Rios | €320,832 | 1,803 | Active |
| 11 | Richards, Grant and West | €328,165 | 823 | Active |
| 12 | Price-Gomez | €286,926 | 2,180 | Active |
| 13 | Torres-Jones | €255,698 | 467 | Active |
| 14 | Howard Enterprises | €253,148 | 943 | Active |
| 15 | Newman Corp | €214,469 | 766 | Active |
The top 3 clients alone account for over $5.9M in revenue. Peterson Inc and Martinez Group each generate more than $2M, making them the two most valuable accounts. Client concentration is something to watch: losing either one would have a significant impact on total revenue.
The data tells a clear story. This MSP went through a major client migration in July 2024, bringing 273 companies into Autotask in a single month. That event accounts for the majority of the 328 total customer records. Since then, new client intake has settled into a steady rhythm of 2 to 6 new clients per month.
Retention is strong at 97.3%. Only 9 customers have gone inactive, and 11 have the "Cancellation" company type. That puts the total churn at 5.9%, which is well below the MSP industry average of 10-15% annual churn.
Revenue concentration tells a different story. The top 3 clients generate $5.97M out of a $17.6M total, meaning about 34% of all revenue comes from just three accounts. Peterson Inc alone brings in $2.3M. If that account churned, it would leave a gap that roughly 42 average-sized clients would need to fill.
The monthly onboarding pattern in 2025 shows seasonal variation. Q1 (Jan-Mar) is the strongest intake period with 14 new clients, while April and December tend to be quiet. This aligns with typical MSP sales cycles where new contracts start at the beginning of quarters or the calendar year.
Based on the data above, here are the areas that deserve attention.
With 34% of revenue in three accounts, losing even one would be painful. Build a "key account" review cadence for your top 10 clients. Schedule quarterly check-ins with their decision makers, track NPS scores, and keep a churn risk log.
Two companies with the type "Cancellation" still have their status set to active (TRUE). Either these clients were re-signed and the company type was not updated, or the cancellation process did not complete properly. Clean up these records to keep your data accurate.
With an average intake of 2.4 clients per month in 2025, you are on track for about 29 new clients this year. If each client averages $55K in revenue, that is $1.6M in new annual recurring revenue. Decide if that pace matches your growth plan, and adjust sales efforts accordingly.
A 97.3% retention rate is excellent. Document what is working: QBR frequency, CSAT follow-ups, proactive monitoring alerts. These practices are keeping clients from leaving and should be treated as non-negotiable processes.
All data comes from the BI_Autotask_Companies table in the Proxuma Power BI semantic model. This table syncs directly from your Autotask PSA instance and includes company type, status, creation date, and billing history.
Any company in Autotask with the company_type set to "Customer." Companies with other types (Vendor, Lead, Cancellation) are tracked separately.
Churn rate = (Inactive Customers + Cancellation-type companies) / (Total Customers + Cancellation-type companies). This gives a combined view of all clients who are no longer actively serviced.
The 273 new clients in July 2024 likely represent a bulk migration from a previous PSA or CRM system. This is common when MSPs switch to Autotask and import their full client base at once.
Yes. The DAX queries in this report can be extended with additional filters on company_category, city, or any other column in the BI_Autotask_Companies table. The Proxuma Power BI model supports all standard Autotask dimensions.
The underlying Power BI dataset refreshes on a schedule configured in the Proxuma Power BI workspace. Typically this runs daily, so the data is at most 24 hours old.
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