“Cross-Source CSAT vs SLA Proof”
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Cross-Source CSAT vs SLA Proof

Analysis and reporting on csat vs sla proof - satisfaction meets service levels for managed service providers.

Built from: Autotask PSA SmileBack Proxuma Power BI AI via MCP
How this report was made
1
Autotask PSA
Multiple data sources combined
2
Proxuma Power BI
Pre-built MSP semantic model, 50+ measures
3
AI via MCP
Claude or ChatGPT writes DAX queries, executes them, formats output
4
This Report
KPIs, breakdowns, trends, recommendations
Ready in < 15 min

Cross-Source CSAT vs SLA Proof

Analysis and reporting on csat vs sla proof - satisfaction meets service levels for managed service providers.

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 delivery managers, operations leads, and MSP owners tracking service quality

How often: Weekly for operational adjustments, monthly for client reporting, quarterly for contract reviews

Time saved
Pulling per-client SLA data from PSA manually takes hours. This report delivers the breakdown in minutes.
Client-level clarity
Portfolio averages mask the clients getting poor service. This report surfaces the specific accounts that need attention.
Contract evidence
Concrete SLA data per client gives you proof points for renewals, pricing adjustments, or staffing conversations.
Report categorySLA & Service Performance
Data sourceAutotask PSA · Datto RMM · Datto Backup · Microsoft 365 · SmileBack · HubSpot · IT Glue
RefreshReal-time via Power BI
Generation timeUnder 15 minutes
AI requiredClaude, ChatGPT or Copilot
AudienceService delivery managers, operations leads
Where to find this in Proxuma
Power BI › SLA › Cross-Source CSAT vs SLA Proof
What you can measure in this report
Summary Metrics
Correlation by Client
CSAT vs SLA Proof Trend (3 Quarters)
SLA Risk Quadrant
Ticket Detail by Priority
Service Desk Health Overview
Key Findings
Strategic Recommendations
Frequently Asked Questions
Correlation
SLA Met Rate
CSAT Score
AI-Generated Power BI Report
Cross-Source CSAT vs SLA Proof

Analysis and reporting on csat vs sla proof - satisfaction meets service levels for managed service providers.

Demo Report: This report uses synthetic data to demonstrate AI-generated insights from Proxuma Power BI. The structure, DAX queries, and analysis reflect real MSP data patterns.
1.0 Summary Metrics
Correlation
87.7%
10,178 ratings from SmileBack integration
SLA Met Rate
90.2%
67,521 tickets from Autotask service desk
CSAT Score
+12.0%
CSAT rose from 78.3% to 87.7% alongside strong SLA
Outliers
3
High SLA, low CSAT
View DAX Query - Summary Metrics
EVALUATE ROW("CSATAvg", [CSAT - Average Rating], "CSATLastYear", [CSAT - Average Rating - Last Year], "CSATTotalRatings", [CSAT - Total Ratings], "ResolutionMet", [Tickets - Resolution Met %], "SameDayRes", [Tickets - Same Day Resolution %], "FirstHourFix", [Tickets - First Hour Fix %], "ClosureRate", [Tickets - Closure Rate %], "TotalTickets", [Tickets - Count - Created], "HoursWorked", [Tickets - Hours Worked])
2.0 Correlation by Client

Breakdown of satisfaction meets service levels across managed clients.

Lewis LLC
0.84
Martin Group
83
Wall PLC
71
Ramos Group
59
Hahn Group
47
Anderson Group
35
ClientCorrelationSLA Met RateCSAT ScoreOutliersStatus
Lewis LLC191.2%94.2%3Good
Martin Group183.9%86.7%3Good
Wall PLC176.6%79.1%3Warning
Ramos Group169.3%71.6%2Warning
Hahn Group162.0%64.1%2Critical
Anderson Group154.7%56.5%2Good

Lewis LLC leads across most metrics in this analysis. Hahn Group shows the weakest performance and should be flagged for a dedicated review. The gap between top and bottom performers suggests an opportunity to standardize processes across the portfolio.

View DAX Query - Correlation by Client
EVALUATE
SUMMARIZECOLUMNS(
    BI_SmileBack_CSAT[company_name],
    "Correlation", COUNTROWS(BI_SmileBack_CSAT),
    "SLA Met Rate", CALCULATE(COUNTROWS(BI_SmileBack_CSAT), BI_SmileBack_CSAT[status] = "Active")
)
ORDER BY [Correlation] DESC
3.0 CSAT vs SLA Proof Trend (3 Quarters)

How satisfaction meets service levels has evolved over the past three quarters.

Q1 2026
87.4%
Q4 2025
84.2%
Q3 2025
81.8%
QuarterPrimary MetricIssuesCoverageChange
Q3 202581.8%41278.4%Baseline
Q4 202584.2%38782.1%+2.4%
Q1 202687.4%34285.7%+3.2%

The portfolio shows steady improvement over three quarters, with the primary metric increasing from 81.8% to 87.4%. This 5.6 percentage point gain reflects ongoing optimization efforts. To maintain this trajectory, continue the current remediation cadence and expand coverage to newly onboarded clients.

View DAX Query - CSAT vs SLA Proof Trend (3 Quarters)
EVALUATE
SUMMARIZECOLUMNS(
    BI_SmileBack_CSAT[snapshot_month],
    "Correlation", COUNTROWS(BI_SmileBack_CSAT),
    "Rate", DIVIDE(CALCULATE(COUNTROWS(BI_SmileBack_CSAT), BI_SmileBack_CSAT[is_successful] = TRUE()), COUNTROWS(BI_SmileBack_CSAT))
)
ORDER BY BI_SmileBack_CSAT[snapshot_month] ASC
4.0
SLA Risk Quadrant
Mapping clients by ticket volume and SLA compliance.
HIGH RISK
4 entities
Performance significantly below portfolio average. Immediate action required.
MODERATE RISK
7 entities
Performance below target but stable. Review within 2 weeks.
LOW RISK
12 entities
Performance above target level. Standard monitoring sufficient.
NOT ASSESSED
3 entities
Insufficient data available for risk assessment.

The risk matrix shows that most entities fall in the low-risk category, but the high-risk group demands immediate attention. The moderate-risk group shows a declining trend that could escalate without intervention.

5.0
Ticket Detail by Priority
Granular breakdown of ticket handling times.
CategoryItemsPrimarySecondaryStatus
Category A23494.2%14Healthy
Category B18789.3%20Review
Category C15691.7%13Healthy
Category D9886.7%13Review
Category E6782.1%12At Risk
Category F4595.6%2Healthy

The detailed breakdown shows clear performance differences. The bottom two categories require targeted action to improve overall portfolio health.

6.0
Service Desk Health Overview
Key health indicators for the service desk.
92.4% health score
Portfolio Health
87.3% of 100%
Coverage
23 action items
Open Items

Overall portfolio health is strong at 92.4%, but the 87.3% coverage rate suggests that roughly 1 in 8 entities is not fully monitored. The 23 open action items represent a manageable backlog if addressed within 2 weeks.

7.0
Key Findings
!

Performance Gap Requires Attention

The gap between top and bottom performers is wider than expected. The bottom 20% scores more than 25 percentage points below the portfolio average, indicating structural issues that require targeted intervention.

!

Declining Trend in Moderate Risk Group

Entities in the moderate risk category show a declining trend over the past quarter. Without intervention, 3-4 of these entities may shift to the high-risk category within 60 days.

Top Performers Remain Consistent

The top 30% of the portfolio maintains stable performance above target, indicating current best practices are effective and can serve as a model for the rest.

8.0
Strategic Recommendations

1. Conduct a targeted review of all high-risk entities within 2 weeks. Document the root cause for each entity and create a remediation plan with clear deadlines and accountable owners.

2. Implement automated monitoring for the moderate-risk group. Set thresholds that trigger an alert when performance drops 5 percentage points below target, enabling early intervention before entities slip into high risk.

3. Schedule this report monthly as part of the QBR process. Use the trend data to verify that improvement initiatives are delivering measurable results across multiple quarters.

9.0
Frequently Asked Questions
What does Correlation measure?

Correlation tracks the key performance indicator for satisfaction meets service levels. It is calculated based on data from SmileBack, Autotask PSA and refreshed daily.

How often is this report updated?

Data syncs every 24 hours from SmileBack, Autotask PSA. The report reflects the most recent complete data set.

What should we do about poor performers?

Schedule a dedicated review for any client falling below the portfolio average. Create an action plan with specific remediation steps and follow up within 2 weeks.

Can we use this in QBR presentations?

Yes. This report is designed to be QBR-ready. Export the key metrics and trend data to include in your quarterly business review slide deck.

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