Per-client profitability breakdown with margin bands, loss-making client identification, revenue concentration risk, and monthly trend analysis. Generated by AI via Proxuma Power BI MCP server.
Per-client profitability breakdown with margin bands, loss-making client identification, revenue concentration risk, and monthly trend analysis. Generated by AI via Proxuma Power BI MCP server.
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
Per-client profitability breakdown with margin bands, loss-making client identification, revenue concentration risk, and monthly trend analysis. Generated by AI via Proxuma Power BI MCP server.
BI_Autotask_Billing_Items and BI_Autotask_Companies, and calculated revenue, cost, profit, and margin for each client. All numbers are pulled live from Power BI.
EVALUATE
SUMMARIZECOLUMNS(
"TotalRevenue", [Revenue - Total],
"TotalCost", [Cost - Total],
"TotalProfit", [Profit - total],
"AvgMargin", [Profit - total - percentage]
)All 20 clients sorted by absolute profit. Margin badges: green (>50%), amber (30-50%), red (<30%).
| # | Client | Revenue | Cost | Profit | Margin |
|---|---|---|---|---|---|
| 1 | Craig-Huynh | €2,324,617 | €1,013,970 | €1,310,647 | 56.4% |
| 2 | Lewis LLC | €2,212,915 | €894,222 | €1,318,693 | 59.6% |
| 3 | Little Group | €1,431,177 | €603,420 | €827,758 | 57.8% |
| 4 | Martin Group | €637,092 | €248,212 | €388,880 | 61.0% |
| 5 | Lopez-Reyes | €589,694 | €645,574 | -€55,879 | -9.5% |
| 6 | Wall PLC | €476,622 | €214,395 | €262,227 | 55.0% |
| 7 | Burke, Armstrong and Morgan | €469,660 | €224,394 | €245,267 | 52.2% |
| 8 | Patterson, Riley and Lawson | €416,450 | €206,868 | €209,582 | 50.3% |
| 9 | Richards, Bell and Christensen | €328,165 | €107,091 | €221,073 | 67.4% |
| 10 | Wu-Jackson | €321,669 | €121,483 | €200,186 | 62.2% |
| 11 | Thompson, Contreras and Rios | €320,832 | €141,416 | €179,416 | 55.9% |
| 12 | Price-Gomez | €286,926 | €120,188 | €166,739 | 58.1% |
| 13 | Torres-Jones | €255,698 | €46,812 | €208,887 | 81.7% |
| 14 | Hahn Group | €253,148 | €133,138 | €120,010 | 47.4% |
| 15 | Montgomery-Peck | €214,469 | €133,755 | €80,714 | 37.6% |
| 16 | Ramos Group | €205,547 | €126,248 | €79,299 | 38.6% |
| 17 | Kelley-Walsh | €203,888 | €131,810 | €72,077 | 35.4% |
| 18 | Lee-Dalton | €198,503 | €69,709 | €128,794 | 64.9% |
| 19 | Buchanan, Acosta and Chambers | €188,912 | €93,716 | €95,196 | 50.4% |
| 20 | Clements, Pham and Garcia | €175,507 | €71,242 | €104,264 | 59.4% |
EVALUATE
TOPN(20, SUMMARIZECOLUMNS('BI_Autotask_Companies'[company_name],
"Revenue",[Revenue - Total],"Cost",[Cost - Total],"Profit",[Profit - total],"ProfitMargin",[Profit - total - percentage]),
[Revenue],DESC) ORDER BY [Revenue] DESCHow the 20 clients distribute across margin bands. The majority sit above 50%, but four clients fall below that threshold.
15 out of 20 clients (75%) sit above the 50% margin threshold. Three clients cluster in the 30-40% band, which may indicate pricing issues or scope creep on those accounts. Client E is the only loss-making account, and Client N sits just below 50% at 47.4%.
Revenue distribution across the client base. High concentration in a few accounts increases business risk.
| # | Client | Revenue | Share | Cumulative |
|---|---|---|---|---|
| 1 | Craig-Huynh | €2,324,617 | 13.2% | 13.2% |
| 2 | Lewis LLC | €2,212,915 | 12.6% | 25.8% |
| 3 | Little Group | €1,431,177 | 8.1% | 33.9% |
| 4 | Martin Group | €637,092 | 3.6% | 37.5% |
| 5 | Lopez-Reyes | €589,694 | 3.4% | 40.9% |
| 6 | Wall PLC | €476,622 | 2.7% | 43.6% |
| 7 | Burke, Armstrong and Morgan | €469,660 | 2.7% | 46.3% |
| 8 | Patterson, Riley and Lawson | €416,450 | 2.4% | 48.6% |
| 9 | Richards, Bell and Christensen | €328,165 | 1.9% | 50.5% |
| 10 | Wu-Jackson | €321,669 | 1.8% | 52.3% |
| 11 | Thompson, Contreras and Rios | €320,832 | 1.8% | 54.2% |
| 12 | Price-Gomez | €286,926 | 1.6% | 55.8% |
| 13 | Torres-Jones | €255,698 | 1.5% | 57.2% |
| 14 | Hahn Group | €253,148 | 1.4% | 58.7% |
| 15 | Montgomery-Peck | €214,469 | 1.2% | 59.9% |
Top 3 clients generate 34% of total revenue. This is a moderate concentration risk. If any of these three accounts churned, the revenue impact would be significant. The remaining 17 clients account for 66% of revenue, providing a reasonable baseline of diversification.
Portfolio-wide profit margin by month, January 2025 through January 2026.
The portfolio margin averaged around 53% for most months, with one clear outlier: May 2025 dropped to 27.0%. This likely reflects a one-time cost spike, a large project going over budget, or an unusually high proportion of low-margin work that month. The margin recovered immediately in June (60.3%), suggesting the dip was event-driven rather than structural.
January 2026 hit 68.2%, the highest point in the period. Worth investigating whether this reflects a genuine improvement in mix or simply lower activity (and therefore lower cost) in a seasonally quiet month.
EVALUATE
SUMMARIZECOLUMNS('BI_Common_Dim_Date'[month_name], 'BI_Common_Dim_Date'[year], 'BI_Common_Dim_Date'[month],
TREATAS({2025, 2026}, 'BI_Common_Dim_Date'[year]),
"Revenue",[Revenue - Total],"Cost",[Cost - Total],"Margin",[Profit - total - percentage])
ORDER BY 'BI_Common_Dim_Date'[year], 'BI_Common_Dim_Date'[month]A closer look at Client E, the only account operating at a loss.
Client E generated €589,694 in revenue but cost €645,574 to service, resulting in a €55,879 loss. The cost structure is the core issue: 695 hours worked versus only 810 hours billed, which looks reasonable on the surface. The problem sits in the rate structure or scope. Either the contract rate is too low relative to the internal cost of delivering the work, or there are significant unbilled components (managed services, licenses, infrastructure) consuming margin.
At -9.5% margin, every month this contract continues without adjustment increases the loss. Review the rate card, scope definition, and any fixed-price elements. Compare the internal hourly cost with the billed rate to identify the gap.
695 hours worked vs. 810 hours billed is unusual (more billed than worked). Verify whether billing includes pass-through items like licenses or hardware. If so, the labour component may be even more unprofitable than the headline number suggests.
This is the 5th largest client by revenue. Fixing the margin, even to 40%, would turn a €55.9K loss into a €236K profit. The relationship has scale. The pricing needs to reflect it.
-9.5% margin with €55.9K in losses over 12 months. This needs a contract renegotiation or service restructuring before the next renewal. At current rates, Client E costs more to serve than it pays.
Clients O (37.6%), P (38.6%), and Q (35.4%) are below the 50% target. They are profitable, but at rates that barely cover overhead and leave little room for investment. Pricing reviews or efficiency improvements on these accounts would have a measurable impact.
The highest margin in the portfolio. At €255.7K revenue and only €46.8K in costs, this is a model of efficient service delivery. Identify what makes this account work (contract type, service mix, team allocation) and see if the pattern applies to other clients.
The portfolio is healthy overall. €9.3M in profit from €17.6M revenue demonstrates a strong service business. The focus should be on protecting the top performers and fixing the outliers, not on wholesale changes to pricing or delivery.
Profit margin is calculated as (Revenue - Cost) / Revenue, expressed as a percentage. Revenue comes from billing items in Autotask PSA. Cost includes internal labour costs based on resource rates and hours worked. A margin of 53% means that for every euro billed, 53 cents is profit after direct costs.
Costs reflect the internal resource cost assigned to each billing item in Autotask. This includes labour at the resource's internal rate. It does not include overhead, rent, software licenses, or other indirect costs. The margin shown is a gross margin on direct service delivery.
Industry benchmarks from Service Leadership and ConnectWise put a healthy MSP gross margin between 50% and 65%. Anything below 40% on a per-client basis usually signals pricing issues, scope creep, or inefficient service delivery. This portfolio's 53% average sits right in the target range.
May 2025 showed a 27.0% margin, the lowest in the 13-month period. This type of single-month dip typically points to a large project going over budget, an onboarding cost spike for a new client, or a concentration of high-cost work in that month. The immediate recovery to 60.3% in June confirms it was a temporary event.
Yes. Connect Proxuma Power BI to your Autotask PSA, add an AI tool (Claude, ChatGPT, or Copilot) via MCP, and ask the same question. The AI writes the DAX queries, runs them against your real data, and produces a report like this in under fifteen minutes.
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.
See more reports Get started