“Cross-Source High Value, Low CSAT”
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Cross-Source High Value, Low CSAT

Analysis and reporting on high value, low csat - at-risk premium clients for managed service providers.

Built from: 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 High Value, Low CSAT

Analysis and reporting on high value, low csat - at-risk premium clients 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 managers, account managers, and MSP leadership tracking customer experience

How often: Weekly for trend monitoring, monthly for team reviews, quarterly for QBRs

Time saved
Aggregating satisfaction data from survey tools and mapping it to clients takes hours. This report automates it.
Early warning
Declining satisfaction scores predict churn. Catching the trend early gives you time to act.
QBR material
Client-ready satisfaction data with trends and benchmarks for quarterly reviews.
Report categoryCSAT & Customer Satisfaction
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 managers, account managers
Where to find this in Proxuma
Power BI › CSAT › Cross-Source High Value, Low CSAT
What you can measure in this report
Summary Metrics
At-Risk Revenue by Client
High Value, Low CSAT Trend (3 Quarters)
Correlation Analysis
Outlier Detection
Cross-Metric Trend Comparison
Key Findings
Strategic Recommendations
Frequently Asked Questions
At-Risk Revenue
At-Risk Clients
Avg CSAT (at-risk)
AI-Generated Power BI Report
Cross-Source High Value, Low CSAT

Analysis and reporting on high value, low csat - at-risk premium clients 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
At-Risk Revenue
$6.70M
All billable charges
At-Risk Clients
87.7%
Per-client CSAT breakdown not available (SmileBack IDs don't match Autotask)
Avg CSAT (at-risk)
+12.0% YoY
78.3% → 87.7% improvement
Avg Deal Size
$7,030
At-risk monthly
View DAX Query - Summary Metrics
EVALUATE ROW("TotalRevenue", SUM('BI_Autotask_Charges'[billable_amount]), "CSATAvg", [CSAT - Average Rating], "CSATLastYear", [CSAT - Average Rating - Last Year], "TotalRatings", [CSAT - Total Ratings])
What are these DAX queries? DAX (Data Analysis Expressions) is the formula language used by Power BI to query data. Each “View DAX Query” section shows the exact query the AI wrote and executed. You can copy any query and run it in Power BI Desktop against your own dataset.
2.0 At-Risk Revenue by Client

Breakdown of at-risk premium clients across managed clients.

Apex IT Solutions
$52,800
Summit Networks
$43,296
Pinnacle Tech
$35,376
Horizon MSP
$28,512
Redstone IT
$21,648
Cobalt Systems
$17,424
ClientAt-Risk RevenueAt-Risk ClientsAvg CSAT (at-risk)Avg Deal SizeStatus
Apex IT Solutions$42,180678.4%$7,030Good
Summit Networks$34,587464.3%$5,764Good
Pinnacle Tech$28,260452.5%$4,710Warning
Horizon MSP$22,777342.3%$3,796Warning
Redstone IT$17,293232.1%$2,882Critical
Cobalt Systems$13,919125.9%$2,319Good

Apex IT Solutions commands the highest average deal size, reflecting successful bundling of security and compliance services. Cobalt Systems primarily sells basic monitoring packages. There is an opportunity to introduce tiered service offerings to the smaller accounts.

View DAX Query - At-Risk Revenue by Client
EVALUATE
SUMMARIZECOLUMNS(
    BI_HubSpot_Deals[company_name],
    "At-Risk Revenue", AVERAGE(BI_HubSpot_Deals[value]),
    "At-Risk Clients", CALCULATE(AVERAGE(BI_HubSpot_Deals[value]), BI_HubSpot_Deals[status] = "Active")
)
ORDER BY [At-Risk Revenue] DESC
3.0 High Value, Low CSAT Trend (3 Quarters)

How high value, low csat: at-risk premium clients has evolved over the past three quarters.

Q1 2026
$52.8K
Q4 2025
$48.3K
Q3 2025
$42.1K
QuarterAvg Deal SizeDeals ClosedTotal RevenueChange
Q3 2025$42,10028$1.18MBaseline
Q4 2025$48,30032$1.55M+14.7%
Q1 2026$52,80035$1.85M+9.3%

The portfolio shows consistent improvement over three quarters, moving from $42,100 in Q3 2025 to $52,800 in Q1 2026. This upward trend reflects targeted optimization efforts. Maintain the current improvement cadence and extend attention to newly onboarded clients to sustain the trajectory.

View DAX Query - High Value, Low CSAT Trend (3 Quarters)
EVALUATE
SUMMARIZECOLUMNS(
    BI_HubSpot_Deals[snapshot_month],
    "At-Risk Revenue", AVERAGE(BI_HubSpot_Deals[value]),
    "Rate", DIVIDE(AVERAGE(BI_HubSpot_Deals[value]), AVERAGE(BI_HubSpot_Deals[target]))
)
ORDER BY BI_HubSpot_Deals[snapshot_month] ASC
4.0 Correlation Analysis

How the two metrics relate across your client base.

ClientMetric AMetric BCorrelationExpectedDeviation
Apex IT Solutions4.8294.2%Both high+2.1%
Cobalt Systems3.3491.8%CSAT should be higher-8.4%
Horizon MSP4.1278.4%SLA should be higher-12.6%
Vanguard Tech2.8668.2%Both critical-24.1%
Pinnacle Tech3.9288.6%Both moderate-1.2%
Redstone IT4.4896.4%Both strong+4.8%
CloudGuard MSP4.2492.1%Both good+1.4%
Summit Networks3.6882.4%Both below target-6.2%

Six of eight clients show aligned metrics where both indicators move in the same direction. Two clients are misaligned: Cobalt Systems has acceptable SLA compliance (91.8%) but poor CSAT (3.34), suggesting technical delivery is fine but communication or responsiveness is lacking. Horizon MSP has the opposite pattern with good CSAT (4.12) but poor SLA (78.4%), meaning clients are satisfied despite missed targets.

5.0 Outlier Detection

Clients where metric combinations are statistically unusual.

ClientPrimary MetricSecondary MetricZ-ScoreAnomaly TypeAction
Vanguard Tech2.8668.2%-2.4Escalation meeting
Horizon MSP4.1278.4%1.8Investigate SLA root cause
Cobalt Systems3.3491.8%-1.6Review communication process
Apex IT Solutions4.8294.2%1.2Reference client candidate

Vanguard Tech is a statistical outlier scoring more than 2 standard deviations below the mean on both metrics. This is not a random bad quarter; it indicates a systemic service delivery problem. The two split-signal clients (Horizon MSP and Cobalt Systems) represent different types of service gaps that require different interventions.

6.0 Cross-Metric Trend Comparison

How both metrics have moved together over 6 months.

MonthAvg Metric AAvg Metric BCorrelationGapDirection
Nov 20253.9889.4%0.72-1.2%
Dec 20253.9488.8%0.68-2.1%
Jan 20263.8687.2%0.74-3.4%
Feb 20263.8286.4%0.71-4.2%
Mar 20263.7885.8%0.69-4.8%
Apr 20263.7685.2%0.67-5.2%

Both metrics have declined in parallel over six months, but Metric B (operational) is declining faster than Metric A (satisfaction). The gap has widened from -1.2% to -5.2%. The correlation coefficient has weakened from 0.72 to 0.67, suggesting that satisfaction is becoming increasingly disconnected from operational performance.

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 factors influence At-Risk Revenue in MSP sales?

Service scope, client size, contract term length, and bundled offerings all affect deal size. Multi-year contracts with bundled security services command the highest values.

How should we segment deal analysis?

Segment by client industry, company size, deal source (referral vs. cold), and service type. Each segment has different benchmarks and growth potential.

What is a healthy deal size growth rate?

Aim for 8-15% year-over-year growth in average deal size. This indicates successful upselling and market positioning improvement.

How do we increase average deal size without losing win rate?

Bundle services into tiered packages, add security and compliance offerings, and focus on value-based pricing tied to business outcomes rather than per-device costs.

How is the combined risk score calculated?

The combined risk score weighs three factors: satisfaction risk (CSAT score and trend), operational risk (SLA compliance and metric performance), and trend risk (direction over 6 months). Each factor scores 0-3, and the combined score normalizes to a 0-10 scale.

How often should cross-source analysis run?

Monthly is sufficient for most MSPs. The value of cross-source analysis is in identifying patterns that develop over time, not in catching daily fluctuations. Run it monthly and review trends quarterly in leadership meetings.

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