A cross-platform analysis of SmileBack satisfaction data and HubSpot renewal pipeline to test whether CSAT trajectory can predict contract renewal outcomes. Covers 7 clients with CSAT data, 115 HubSpot deals, and the data linkage gap between both systems.
A cross-platform analysis of SmileBack satisfaction data and HubSpot renewal pipeline to test whether CSAT trajectory can predict contract renewal outcomes. Covers 7 clients with CSAT data, 115 HubSpot deals, and the data linkage gap between both systems.
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
A cross-platform analysis of SmileBack satisfaction data and HubSpot renewal pipeline to test whether CSAT trajectory can predict contract renewal outcomes. Covers 7 clients with CSAT data, 115 HubSpot deals, and the data linkage gap between both systems.
Top-level metrics from SmileBack CSAT ratings and HubSpot deal pipeline.
SmileBack positive rate across all clients with sufficient survey volume, paired with service quality indicators.
| Metric | Current | Last Year | Change |
|---|---|---|---|
| CSAT Average | 87.7% | 78.3% | +12.0% |
| Total Ratings | 10,178 | - | - |
| Closure Rate | 98.8% | - | - |
EVALUATE ROW("CSATAvg", [CSAT - Average Rating], "CSATLastYear", [CSAT - Average Rating - Last Year], "CSATTotalRatings", [CSAT - Total Ratings], "ClosureRate", [Tickets - Closure Rate %])HubSpot deal outcomes for companies matched through Bridge_All_Companies, alongside any available CSAT data.
| Company | CSAT Pos% | Deals Won | Closed Rate | Status |
|---|---|---|---|---|
| Client A | 90.3% | 16 | 16.7% | Both systems |
| Client F | -- | 1 | 100% | HubSpot only |
| Client K | -- | 1 | 100% | HubSpot only |
| Client I | 100.0% | -- | -- | CSAT only |
| Client D | 89.4% | -- | -- | CSAT only |
| Client B | 79.4% | -- | -- | CSAT only |
EVALUATE
TOPN(10,
FILTER(
ADDCOLUMNS(
VALUES(Bridge_All_Companies[company_id]),
"CompName", CALCULATE(MAX('BI_Autotask_Companies'[company_name])),
"CSAT", [CSAT - Average Rating],
"CSATLastYear", [CSAT - Average Rating - Last Year],
"DealsWon", [HubSpot - Deals Won],
"ClosedRate", [HubSpot - Closed Rate]
),
NOT(ISBLANK([DealsWon]))
),
[DealsWon], DESC
)Why the connection between satisfaction and renewal cannot be proven with the current data, and what it would take to fix that.
The core problem is not low satisfaction or low close rates. The problem is that the two systems holding this information are barely connected. SmileBack captures post-ticket feedback for 7 clients. HubSpot tracks deal pipeline for 3 companies. Only 1 of those overlaps. You cannot build a churn prediction model on a single data point.
This gap is not a technical limitation of Power BI. It is an operational gap: renewal deals are not consistently created in HubSpot for clients that have SmileBack surveys, and vice versa. Until both systems cover the same client base, this analysis remains theoretical.
Clients where the combination of CSAT score and service quality metrics suggests potential risk, even without CRM confirmation.
Client J stands out as the highest-risk account. While CSAT reads 88.6%, the first response SLA is met only 43.2% of the time. That is a leading indicator: the client rates individual interactions positively, but the structural delivery is failing. If first response keeps slipping, satisfaction will follow within 1-2 quarters.
Client B has the lowest CSAT (79.4%) but strong SLA performance at 88.2% first response and 91.7% resolution. This suggests the dissatisfaction is not about speed. It could be communication quality, expectation misalignment, or ticket volume fatigue (9,307 alerts).
Client A is the only account where churn risk can be cross-referenced with deal data. With 16 deals won and a 16.7% close rate, the renewal pipeline is active. The 89.4% CSAT combined with 73.7% first response met is a watch point. That first response gap is wide enough to erode satisfaction over time.
EVALUATE
ROW(
"AvgCSAT", [CSAT - Average Rating],
"TotalDeals", [HubSpot - Deals Total],
"DealsWon", [HubSpot - Deals Won],
"ClosedRate", [HubSpot - Closed Rate]
)Only 1 of 7 CSAT-tracked clients has matching HubSpot deal records. A single data point cannot establish or disprove a correlation between satisfaction trends and renewal outcomes. This is a data integration problem, not an analytics problem.
88.6% positive CSAT paired with 43.2% first response SLA is a leading indicator of future dissatisfaction. When clients notice that tickets take too long to get an initial response, the sentiment shift tends to be sudden rather than gradual.
At 79.4% positive rate with 88.2% first response and 91.7% resolution SLA, the source of dissatisfaction is not delivery speed. It is likely related to communication quality, expectations, or the sheer volume of 9,307 alerts creating frustration.
100% positive CSAT with 92.3% first response and 97.5% resolution SLA across 2,646 alerts. Whatever this team is doing for Client I should be documented and replicated across other accounts.
The business question was: does CSAT trajectory predict renewal? The honest answer is: we cannot tell yet. Not because the relationship does not exist, but because the data infrastructure to test it is not in place. SmileBack and HubSpot cover almost entirely different client populations.
What the data does show is that CSAT alone is a poor proxy for service health. Client J has a strong 88.6% positive rate, but first response SLA performance at 43.2% tells a different story. If you only looked at CSAT, you would miss the operational risk. Conversely, Client B has the worst CSAT at 79.4%, but SLA performance is above average. The dissatisfaction driver there is something else entirely.
The 15.7% deal close rate in HubSpot raises a separate concern. 97 of 115 deals were lost or remain open. Whether this reflects pipeline quality, sales execution, or CRM hygiene is unclear from the data alone. But if these deals include renewal opportunities, a 15.7% close rate on renewals would be alarming.
Client A is the proof of concept. It is the only account that appears in both SmileBack (90.3% CSAT) and HubSpot (16 deals won). The close rate of 16.7% against a strong CSAT score suggests that satisfaction and close rate may not correlate as directly as expected. Or it suggests the HubSpot pipeline contains a lot of non-renewal opportunities that dilute the metric.
Steps to close the data gap and build a working churn prediction system.
The 6 clients with SmileBack data and no HubSpot deals need renewal records created this month. Without deal records, there is no outcome to correlate against satisfaction. This is a one-time setup task that takes 30 minutes and unblocks the entire analysis.
Verify that every SmileBack company name maps to the correct Bridge_All_Companies ID. Run a manual audit of the 7 CSAT clients against the bridge table. Fix name mismatches and fill in missing company_id links. This is the foundation for all cross-platform reporting.
43.2% first response met is a critical operational gap that will show up in CSAT within 1-2 quarters. Pull the time entry and ticket data for Client J over the last 90 days. Identify whether this is a capacity issue, routing issue, or a contract that needs different SLA tiers.
79.4% CSAT with strong SLA numbers means the problem is not delivery speed. Set up a quarterly business review with Client B to identify the actual pain points. Possible drivers: alert fatigue from 9,307 tickets, communication gaps, or expectation misalignment.
SmileBack uses a -1/0/1 scale (negative/neutral/positive). The positive rate is the percentage of responses rated +1 out of all responses. An 87.7% positive rate means 87.7% of all survey responses were positive.
SmileBack and HubSpot are separate systems with different data entry workflows. SmileBack captures post-ticket surveys (service delivery), while HubSpot tracks sales pipeline (commercial relationships). Most MSPs do not create renewal deals in HubSpot for every managed services client.
Research suggests satisfaction trends (the direction over time) are more predictive than point-in-time scores. A client dropping from 95% to 80% over 6 months is a stronger signal than a stable 82%. To detect this, you need consistent survey coverage and at least 12 months of history per client.
Bridge_All_Companies is a lookup table in the Proxuma Power BI data model that maps company IDs across different platforms (Autotask, HubSpot, SmileBack, IT Glue, etc.) to a single unified ID. When the mapping is complete, it enables cross-platform analysis like this report attempts.
It depends on what those deals represent. If they include new business prospecting, 15.7% is not unusual for B2B services. If they are primarily renewal opportunities for existing clients, then yes, a sub-20% renewal close rate would be a serious concern worth investigating immediately.
Yes. Copy any query from the toggles above and paste it into DAX Studio or the Power BI Desktop performance analyzer. The queries reference standard Proxuma data model tables and measures that exist in every Proxuma Power BI deployment.
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