This report combines Autotask PSA ticket data, SmileBack CSAT scores, and contract metadata to flag clients showing early signs of churn. It scores each account on four dimensions - declining ticket volume, falling satisfaction, upcoming contract expiry, and shrinking monthly recurring revenue - then ranks them by overall risk.
This report combines Autotask PSA ticket data, SmileBack CSAT scores, and contract metadata to flag clients showing early signs of churn. It scores each account on four dimensions - declining ticket volume, falling satisfaction, upcoming contract expiry, and shrinking monthly recurring revenue - then ranks them by overall risk.
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: Account managers, MSP owners, and service delivery leads
How often: Monthly for client reviews, quarterly for QBRs, on-demand when client signals change
This report combines Autotask PSA ticket data, SmileBack CSAT scores, and contract metadata to flag clients showing early signs of churn. It scores each account on four dimensions - declining ticket volume, falling satisfaction, upcoming contract expiry, and shrinking monthly recurring revenue - then ranks them by overall risk.
EVALUATE
ROW(
"ManagedClients", COUNTROWS(
FILTER(BI_Autotask_Companies,
BI_Autotask_Companies[is_active] = TRUE()
&& BI_Autotask_Companies[company_type] = "Customer"
)
),
"HighRiskClients", COUNTROWS(
FILTER(BI_Autotask_Companies,
[Churn Risk Score] >= 3
)
),
"AvgCSAT90d", CALCULATE(
AVERAGE(BI_SmileBack_Ratings[rating]),
DATESINPERIOD(BI_SmileBack_Ratings[created_date],
TODAY(), -90, DAY)
),
"ContractsExpiring90d", COUNTROWS(
FILTER(BI_Autotask_Contracts,
BI_Autotask_Contracts[end_date] <= TODAY() + 90
&& BI_Autotask_Contracts[end_date] >= TODAY()
)
)
)| Status | Count | % |
|---|---|---|
| Active | 1,377 | 72.9% |
| Inactive | 512 | 27.1% |
Client A and Client B both trigger all four churn indicators. Their CSAT scores sit well below the 87% portfolio floor, ticket volumes are dropping fast (a sign the client may be moving support elsewhere), MRR is modest, and both contracts expire within a month. These two accounts need immediate outreach.
EVALUATE SUMMARIZECOLUMNS('BI_Autotask_Contracts'[contract_status_name], "ContractCount", COUNTROWS('BI_Autotask_Contracts'))The gap between high-risk and low-risk clients is over 21 percentage points on CSAT. High-risk clients are not just slightly unhappy - they sit in a completely different bracket. The medium-risk tier is where intervention has the most potential: a 3pp drop is recoverable with focused attention.
EVALUATE
SUMMARIZECOLUMNS(
"RiskTier", SWITCH(
TRUE(),
[Churn Risk Score] >= 3, "High Risk",
[Churn Risk Score] = 2, "Medium Risk",
"Low Risk"
),
"AvgCSAT", AVERAGE(BI_SmileBack_Ratings[rating]),
"ClientCount", DISTINCTCOUNT(
BI_Autotask_Companies[company_id]
),
"CSATChange6m",
CALCULATE(
AVERAGE(BI_SmileBack_Ratings[rating]),
DATESINPERIOD(BI_SmileBack_Ratings[created_date],
TODAY(), -90, DAY)
) -
CALCULATE(
AVERAGE(BI_SmileBack_Ratings[rating]),
DATESINPERIOD(BI_SmileBack_Ratings[created_date],
TODAY() - 180, -90, DAY)
)
)Client A's ticket count dropped from 48 to 28 in a single quarter. For a client with an MRR of only €2,180, that volume used to represent healthy engagement. The sudden drop, combined with a CSAT of 72%, strongly suggests they are already evaluating alternatives.
| Client | Expires In | MRR | CSAT | Renewal Status |
|---|---|---|---|---|
| Client A | 14 days | €2,180 | 72% | No response |
| Client B | 22 days | €4,750 | 68% | No response |
| Client H | 31 days | €5,200 | 76% | In discussion |
| Client C | 45 days | €6,420 | 79% | In discussion |
| Client G | 61 days | €2,560 | 93% | In discussion |
| Client D | 78 days | €1,890 | 71% | No response |
Six contracts expire within 90 days without a confirmed renewal. Client A and Client B have not responded to outreach at all. Client H and Client C are at least in discussions, but both have CSAT scores below 80%. The combined MRR at risk from these 6 contracts is €23,000/month.
High-risk clients account for 13.8% of total MRR (€38,200 out of €277,700). That is not catastrophic on its own, but the medium-risk tier adds another €61,400. If even half of the medium-risk clients tip into high risk over the next quarter, the total exposed MRR jumps to nearly €70,000 - roughly 25% of the portfolio.
Client A and Client B both show declining tickets, low CSAT, shrinking MRR, and expiring contracts with no renewal response. These accounts have a high probability of leaving within 30 days. Combined MRR at immediate risk: €6,930/month.
The 11 high-risk clients average 73.8% CSAT, compared to 95.2% for low-risk clients. This gap has widened by 4 points over the last 6 months. The satisfaction decline started before the ticket volume drop, suggesting unresolved service issues are the root cause rather than reduced IT needs.
Six contracts expire in the next 90 days where the client has either not responded to outreach or is still in early-stage discussions. Three of these clients (A, B, D) have not replied to a single renewal email. The remaining three are in conversation but show below-average satisfaction scores.
1. Schedule executive outreach for Client A and Client B this week. Both accounts expire within 30 days and have gone silent on renewal conversations. A phone call from the account manager or a senior leader is the only realistic intervention left. Prepare a retention offer: a free QBR, a service review, or a short-term discount on the next contract period.
2. Run service recovery calls for all clients with CSAT below 80%. There are 7 clients in this bracket. The goal is not to sell anything - it is to listen. Ask what went wrong, document the issues, and commit to specific fixes with timelines. Clients who feel heard are less likely to leave, even when their scores are low.
3. Build a monthly churn risk dashboard in Power BI. The DAX queries in this report give you the raw scoring logic. Automate the four-indicator model (ticket trend, CSAT trend, MRR change, contract expiry) and set up alerts when any client crosses the threshold from medium to high risk. Catching a shift early gives you 60-90 days to act instead of 14.
Each client is evaluated on four binary indicators: (1) ticket volume declined more than 15% quarter-over-quarter, (2) 90-day CSAT is below 80%, (3) contract expires within 90 days without confirmed renewal, and (4) MRR decreased in the last 6 months. The score is simply the count of triggered indicators, ranging from 0 to 4. A score of 3 or higher is classified as "high risk."
For managed service clients, regular ticket submission shows active engagement with your support team. When a client suddenly stops logging tickets, it rarely means everything is running perfectly. More often, they have started directing support requests to a competing MSP, handling issues internally, or have simply disengaged. A drop of 15% or more in a single quarter is a reliable early warning sign.
The report pulls from two primary sources: Autotask PSA (via BI_Autotask_Companies, BI_Autotask_Tickets, and BI_Autotask_Contracts) and SmileBack CSAT (via BI_SmileBack_Ratings). MRR data is derived from BI_Autotask_Contracts using the contract value divided by the contract duration in months. All data is refreshed through the Power BI MCP server connection.
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