A cross-source analysis mapping Microsoft 365 license counts against HubSpot deal pipeline revenue per client. This report shows how license volume relates to total client value and where licensing is a small fraction of the overall relationship versus where it dominates.
A cross-source analysis mapping Microsoft 365 license counts against HubSpot deal pipeline revenue per client. This report shows how license volume relates to total client value and where licensing is a small fraction of the overall relationship versus where it dominates.
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 cross-source analysis mapping Microsoft 365 license counts against HubSpot deal pipeline revenue per client. This report shows how license volume relates to total client value and where licensing is a small fraction of the overall relationship versus where it dominates.
Top-line numbers from Microsoft 365 licensing and HubSpot deal pipeline data.
How Microsoft 365 licenses are spread across the client base. One unmatched entity holds 99.3% of all licenses.
EVALUATE
TOPN(10,
FILTER(
ADDCOLUMNS(
VALUES(Bridge_All_Companies[company_id]),
"CompName", CALCULATE(MAX('BI_Autotask_Companies'[company_name])),
"TotalLic", [Total Licenses],
"LicUtil", [License Utilization %],
"Revenue", [Revenue - Total]
),
NOT(ISBLANK([TotalLic])) && [TotalLic] > 0
),
[TotalLic], DESC
)How effectively each client consumes the licenses assigned to them. Low utilisation means paying for seats nobody uses.
| Client | Total Licenses | Utilisation % | Status |
|---|---|---|---|
| Client D | 65 | 101.5% | Over-utilised |
| Client E | 1 | 100.0% | Fully consumed |
| Client B | 20,403 | 1.7% | Under-utilised |
| Client C | 1,513 | 0.9% | Under-utilised |
| Unmatched Entity | 3,234,204 | 0.12% | Near-zero usage |
EVALUATE
TOPN(10,
FILTER(
ADDCOLUMNS(
VALUES(Bridge_All_Companies[company_id]),
"CompName", CALCULATE(MAX('BI_Autotask_Companies'[company_name])),
"TotalLic", [Total Licenses],
"LicUtil", [License Utilization %],
"Revenue", [Revenue - Total]
),
NOT(ISBLANK([TotalLic])) && [TotalLic] > 0
),
[TotalLic], DESC
)Comparing Microsoft license volume to total revenue for each matched client. The revenue-per-license ratio reveals how dependent a client relationship is on licensing versus services.
| Client | Licenses | Revenue | Rev/License | Interpretation |
|---|---|---|---|---|
| Client E | 1 | $328,165 | $328,165 | Service-driven |
| Client D | 65 | $51,869 | $798 | Service-heavy |
| Client C | 1,513 | $286,926 | $190 | Balanced mix |
| Client B | 20,403 | $1,431,177 | $70 | License-heavy |
| Unmatched | 3,234,204 | $503 | $0.00 | No service value |
EVALUATE
ROW(
"TotalLicenses", [Total Licenses],
"ActiveLicenses", [Active Licenses],
"LicenseUtil", [License Utilization %],
"TotalDeals", [HubSpot - Deals Total],
"DealsWon", [HubSpot - Deals Won],
"ClosedRate", [HubSpot - Closed Rate],
"TotalRevenue", [Revenue - Total]
)The HubSpot pipeline that sits behind these revenue numbers. Understanding deal flow helps interpret whether license-heavy clients are growing or stagnating.
With 115 total deals and only 18 closed-won, the pipeline conversion rate sits at 15.7%. That is below the typical MSP benchmark of 20-25%. The revenue figure of $17.6M represents total pipeline value including open deals, which means the actual realized revenue is likely a fraction of this number.
For license-heavy clients like Client B, the question becomes: is the $1.4M in revenue primarily from recurring Microsoft licensing margin, or is there meaningful project and service work on top? The answer determines whether the client relationship is sustainable or at risk of being undercut by a direct Microsoft CSP competitor.
A single unmatched entity holds 99.3% of all licenses but generates only $503 in revenue. This is almost certainly a data quality issue in the Bridge table. These licenses are not linked to a real client record, making license-level reporting unreliable until resolved.
Client B has 20,403 licenses and $1.4M in revenue, but at $70 per license, the relationship leans heavily on Microsoft licensing margin. If this client can get the same licenses cheaper through another CSP partner, there is limited service value keeping them attached.
Client D generates $798 per license from just 65 seats. Client E has a single license tied to $328K in revenue. These are service-driven relationships where Microsoft licensing is almost irrelevant to the overall client value. These accounts are well insulated from CSP price competition.
The global utilisation figure is skewed by the unmatched entity. For matched clients, utilisation varies wildly: Client D is over-provisioned (101.5%), Client E is at 100%, while Client B and C sit below 2%. Low utilisation means money is being spent on licenses that nobody is using.
The central question of this report is straightforward: what portion of a client's total value comes from Microsoft licensing, and what comes from actual managed services? The answer varies dramatically across the client base.
Client B is the clearest example of a license-heavy relationship. With 20,403 seats, this is a large Microsoft tenant. The $1.4M revenue looks strong in absolute terms, but at $70 per license, it suggests most of that revenue is licensing margin rather than professional services. If another partner offers a 5-10% discount on CSP pricing, there is not enough service depth to prevent churn.
Client C sits in a healthier position. At $190 per license across 1,513 seats, there is a balanced mix of licensing and service revenue. The 0.9% utilisation rate, though, points to significant license waste. Right-sizing this tenant could save money without reducing service scope.
Client D and Client E represent the ideal. Their revenue-per-license ratios are so high ($798 and $328,165 respectively) that Microsoft licensing is just a rounding error in the relationship. These clients are sticky because of deep service work, not commodity licensing.
The unmatched entity with 3.2M licenses is a data problem, not a business problem. Until the Bridge table maps these licenses to real companies, any aggregate license metric is meaningless. Fix the bridge first, then re-run this analysis.
Concrete steps to improve license-to-revenue alignment and data quality.
Audit the Bridge_All_Companies mapping. The 3.2M unmatched licenses are either orphaned Microsoft tenants, test environments, or a data ingestion error. Assign every tenant to a client record or flag it as internal/test. This is the single highest-impact data fix for license reporting accuracy.
Client B uses 1.7% of 20,403 licenses. Client C uses 0.9% of 1,513 licenses. Schedule a license optimisation call with both clients. Identify unused SKUs, dormant accounts, and over-provisioned plans. The goal is not to reduce revenue but to build trust by saving clients money on seats they do not use.
Use the revenue-per-license ratio as a proxy for service depth. Clients below $100/license are license-dependent and at higher churn risk. Clients above $500/license are service-anchored. Tag every client in HubSpot with this score and use it to prioritise retention and upsell conversations.
License utilisation is the ratio of consumed (actively used) licenses to total active licenses. A rate of 100% means every purchased seat is being used. Below 50% typically signals over-provisioning or unused subscriptions.
Utilisation above 100% happens when consumed licenses exceed the active count, usually because of grace periods, trial extensions, or a timing gap between the license snapshot and the consumption snapshot. It means this tenant is at capacity and may need additional seats.
The Bridge_All_Companies table links records across multiple data sources (Autotask, Microsoft 365, HubSpot) to a single company identity. Without correct mappings, licenses and revenue cannot be attributed to the same client, which is why 3.2M licenses show as unmatched.
Total revenue from the HubSpot deal pipeline divided by the total Microsoft 365 license count for that client. A higher number means the client relationship is driven more by services than by licensing margin.
Not necessarily. Client E has just 1 license but $328K in revenue. Low license counts combined with high revenue indicate deep service relationships. The concern is the opposite: high license counts with low service revenue, because those clients are easily poached by cheaper CSP providers.
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