Cross-source analysis of Microsoft 365 license utilization against SmileBack satisfaction scores. Do clients with underutilized licenses give lower satisfaction ratings? Generated by AI via Proxuma Power BI MCP server.
Cross-source analysis of Microsoft 365 license utilization against SmileBack satisfaction scores. Do clients with underutilized licenses give lower satisfaction ratings? 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: Service managers, account managers, and MSP leadership tracking customer experience
How often: Weekly for trend monitoring, monthly for team reviews, quarterly for QBRs
Cross-source analysis of Microsoft 365 license utilization against SmileBack satisfaction scores. Do clients with underutilized licenses give lower satisfaction ratings? Generated by AI via Proxuma Power BI MCP server.
This report joins two independent data sources to answer a single question: is there a link between license waste and client dissatisfaction? The short answer is yes, but only at the extremes. Client D holds 20,403 Microsoft licenses at 1.7% utilization and scores the lowest CSAT among high-volume raters at 86.8%. Client S sits at 76.3% CSAT. Most clients maintain satisfaction above 90% regardless of license waste, but the outliers tell a different story.
Microsoft 365 license consumption across top 12 clients by total licenses assigned
Not a single client crosses 2% utilization. Client A dominates the total license count with over 3 million assigned, but only 2,941 consumed. Client B has 50,000 licenses and zero consumption. These numbers suggest bulk provisioning errors or inherited licensing from tenant migrations rather than intentional allocation.
| Metric | Count |
|---|---|
| Total | 3,249,734 |
| Consumed | 4,217 |
| Available | 3,245,517 |
EVALUATE ROW("TotalLicenses", SUM('BI_MicrosoftPartnerCenter_Subscribed_Skus'[total_units]), "ConsumedLicenses", SUM('BI_MicrosoftPartnerCenter_Subscribed_Skus'[consumed_units]), "AvailableLicenses", SUM('BI_MicrosoftPartnerCenter_Subscribed_Skus'[available_units]))SmileBack satisfaction scores shown as positive rate percentage. Scale: -1 (unhappy), 0 (neutral), 1 (happy). Positive rate = (avg + 1) / 2.
| Client | Avg Score | Ratings | Positive Rate | Risk Level |
|---|---|---|---|---|
| Client D | 0.736 | 382 | 86.8% | Watch |
| Client M | 0.794 | 384 | 89.7% | OK |
| Client N | 0.894 | 142 | 94.7% | OK |
| Client O | 0.894 | 104 | 94.7% | OK |
| Client P | 0.886 | 79 | 94.3% | OK |
| Client Q | 0.939 | 66 | 97.0% | OK |
| Client R | 0.806 | 62 | 90.3% | OK |
| Client S | 0.525 | 59 | 76.3% | At Risk |
| Client T | 0.840 | 50 | 92.0% | OK |
| Client U | 0.826 | 46 | 91.3% | OK |
| Client V | 0.600 | 45 | 80.0% | Watch |
| Client W | 0.750 | 44 | 87.5% | Watch |
Client D stands out as the highest-volume rater with 382 ratings but the lowest positive rate among that group at 86.8%. Client S at 76.3% is the overall worst performer, though with fewer ratings (59). Eight of the twelve clients sit comfortably above 90%, which means CSAT problems are concentrated in a handful of accounts rather than spread across the board.
EVALUATE
SUMMARIZECOLUMNS (
SmileBackRatings[CompanyName],
"AvgScore", AVERAGE ( SmileBackRatings[Rating] ),
"TotalRatings", COUNTROWS ( SmileBackRatings ),
"PositiveRate",
DIVIDE (
AVERAGE ( SmileBackRatings[Rating] ) + 1,
2,
0
)
)
ORDER BY [TotalRatings] DESCLinking Microsoft 365 provisioning data with SmileBack satisfaction scores where client overlap exists
Only one client appears in both the top-12 license holders and the top-12 CSAT-rated accounts: Client D. That single overlap carries the most telling data point in this report.
Client D holds 20,403 Microsoft licenses but only consumes 352 of them. That means 20,051 licenses sit unused. At the same time, their CSAT positive rate of 86.8% is the lowest of any client with more than 100 ratings. The connection is not necessarily causal, but the pattern fits: poor provisioning management often signals broader operational problems that spill over into support quality.
Clients who receive poorly provisioned environments tend to face more onboarding friction, more password reset tickets, and more "I can't access this" complaints. All of that feeds into lower satisfaction scores.
Clients classified by license waste (high/low) and CSAT score (high/low). Threshold: utilization <2% = high waste, CSAT <90% = low.
The Danger Zone contains the accounts that need immediate attention. Client D is the clearest case: significant license waste paired with below-average satisfaction. Client S lands here on CSAT alone (76.3%), though their license data was not in the top 12. The Watch quadrant holds clients with satisfaction below 90% but no clear licensing issue. The Review quadrant is the biggest group: clients wasting licenses but whose CSAT remains unknown or healthy.
EVALUATE
ADDCOLUMNS (
SUMMARIZECOLUMNS (
Clients[CompanyName],
"LicenseUtil",
DIVIDE (
SUM ( Microsoft365Licenses[ConsumedUnits] ),
SUM ( Microsoft365Licenses[TotalLicenses] ),
0
),
"CSATPositiveRate",
DIVIDE (
AVERAGE ( SmileBackRatings[Rating] ) + 1,
2,
BLANK ()
)
),
"Quadrant",
SWITCH (
TRUE (),
[LicenseUtil] < 0.02 && [CSATPositiveRate] < 0.90,
"Danger Zone",
[LicenseUtil] >= 0.02 && [CSATPositiveRate] < 0.90,
"Watch",
[LicenseUtil] < 0.02 && [CSATPositiveRate] >= 0.90,
"Review",
"Stable"
)
)
ORDER BY [Quadrant], [CSATPositiveRate] ASCEstimated wasted license spend for worst offenders. Assumes an average of $12/license/month for M365 Business Basic.
The numbers below are conservative estimates. Actual costs depend on the specific SKU mix (Business Basic, E3, E5), but even at $12/license/month the waste is staggering.
With 20,403 licenses at 1.7% utilization and the lowest CSAT among high-volume raters (86.8% positive rate from 382 ratings), Client D is the strongest signal that poor provisioning correlates with lower satisfaction. This account needs a joint license audit and service review.
Client S scores a 0.525 average on the SmileBack scale, translating to 76.3% positive rate. With 59 ratings this is a meaningful sample. Their license data was not in the top 12, but this CSAT level alone warrants investigation into what is driving dissatisfaction.
Every single client in the license dataset falls below 2% utilization. Yet most clients in the CSAT dataset score above 90%. This means license waste alone does not tank satisfaction. The problem surfaces when waste combines with other operational gaps.
Clients N, O, P, and Q all maintain positive rates above 94%, with Client Q reaching 97.0%. This proves that license waste does not automatically cause poor satisfaction. Good support execution can offset provisioning gaps, at least in the short term.
| Priority | Action | Owner | Timeline |
|---|---|---|---|
| P1 | Conduct a full license audit for Client D. Map unused licenses to specific SKUs and identify cancellation candidates. | License Manager | This week |
| P1 | Schedule a service review with Client S to identify root causes behind 76.3% CSAT. Check ticket history for patterns. | Service Delivery | This week |
| P2 | Run automated license reclamation for Client A (3M+ unused), Client B (50K unused), and Client E (20K unused). | M365 Admin | Next 2 weeks |
| P2 | Cross-reference full CSAT data with all license holders (not just top 12) to uncover additional Danger Zone accounts. | BI Analyst | Next 2 weeks |
| P3 | Establish a monthly license utilization threshold alert (flag any client below 5% utilization). | Operations | Next month |
| P3 | Build a combined dashboard that overlays license utilization with CSAT trends per client for ongoing monitoring. | BI Team | Next month |
SmileBack uses a three-point scale: happy (+1), neutral (0), and unhappy (-1). The positive rate converts the average score to a 0-100% scale using the formula (average + 1) / 2. An average of 0.736 becomes (0.736 + 1) / 2 = 86.8%.
This typically results from bulk provisioning errors, tenant migrations, or trial licenses that were never cleaned up. The Microsoft 365 admin center reports the total assigned count across all SKUs, including free trials and developer licenses. A proper audit would separate paid from free SKUs.
Not directly. License waste is a signal of poor provisioning hygiene, which often comes with other operational problems: messy onboarding, unresolved access issues, and reactive support. Those secondary effects are what actually lower CSAT. The correlation exists at the extremes but is not universal.
A healthy license utilization rate sits between 85% and 95%. Below 50% is a clear sign of over-provisioning. Below 10% indicates a systemic problem with license management. The clients in this report are all under 2%, which is extreme.
Yes. Connect Proxuma Power BI to both your Microsoft 365 tenant and SmileBack account. Then use Claude, ChatGPT, or Copilot via MCP and ask the same question. The AI writes DAX that joins license data with satisfaction scores and produces a report like this in under fifteen minutes.
The $36.4M/year figure assumes every unused license costs $12/month. In reality, many of those 3M+ licenses are likely free trial or bundled SKUs with zero marginal cost. The number is a worst-case ceiling. A real audit would separate paid from unpaid licenses to reveal the actual financial waste.
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