Cancelled Customers
The Cancelled Customers report shows every service cancellation in a date range, along with the reason, how long that customer stayed, and how they rated your service. You can view cancellations broken down by reason, by team, or as individual records. Use this report to spot patterns, identify which reasons are most common, and see whether early churn is a growing problem.
This report is Powered by MaidSense, MaidCentral's AI-assisted analytics engine.
Navigate to Reports → Cancelled Customers to open this report.
Who Can Access This
| Role | Access |
|---|---|
| Administrator | Full access |
| Office | Full access |
| HR Admin | Full access |
| Payroll Admin | Full access |
| Sales | Full access |
| Technician | Not available |
Page Overview
The page has three main areas:
- KPI summary cards — four at-a-glance totals for the selected period
- Charts — Cancellation Trend and Tenure Distribution (collapsible)
- Tabs — Reason, Team, and Data views for the cancellation records
Set the Date Range
The report defaults to the last 3 months.
- Click the date range picker in the toolbar
- Choose a start and end date
- The page refreshes automatically
You can look backward as far as your data goes — just adjust the range to cover the period you want to analyze.
KPI Summary Cards
Four cards appear at the top of the page once data loads:
| Card | What It Shows |
|---|---|
| Total Cancelled | Total number of cancellations in the date range |
| Early Churn (<60 days) | Customers who cancelled within 60 days of their first service, plus the percentage of total cancellations |
| Avg Tenure | Average number of days (or months/years) customers stayed before cancelling |
| Avg Bill Rate | Average bill rate of cancelled customers |
The Early Churn card is interactive. Click it to filter the Data tab to show only early churn records. Click it again to clear the filter. A ring highlight on the card indicates the filter is active.
Early churn is a key signal — customers who cancel within the first 60 days are most likely to point to onboarding or first-impression problems rather than long-term service issues.
Charts
Two charts appear side by side below the KPI cards. Click Charts to collapse or expand this section. Your preference is not saved between sessions.
Cancellation Trend by Reason
A line chart showing how many cancellations occurred over time, with one line per cancellation reason. Hover over any point to see the exact count for that date and reason. Use this chart to see whether certain reasons are growing or shrinking over time.
Tenure Distribution
A donut chart showing what percentage of cancelled customers fall into each tenure bucket:
| Bucket | What It Means |
|---|---|
| < 3 Months | Cancelled within 3 months of first service |
| 3-6 Months | Stayed 3 to 6 months |
| 6-12 Months | Stayed 6 to 12 months |
| 1-2 Years | Stayed 1 to 2 years |
| 2-5 Years | Stayed 2 to 5 years |
| 5+ Years | Long-term customer, stayed over 5 years |
Hover over any segment to see the count and percentage for that bucket.
Tabs
Three tabs appear below the charts. Switch between them to see different views of the same data.
Reason Tab
A table showing every cancellation reason with a breakdown by tenure bucket. Columns show the count of cancellations for each tenure range:
| Column | Description |
|---|---|
| Reason | The cancellation reason recorded on the customer's account |
| < 3 Months | Cancellations in this tenure range |
| 3-6 Months | Cancellations in this tenure range |
| 6-12 Months | Cancellations in this tenure range |
| 1-2 Years | Cancellations in this tenure range |
| 2-5 Years | Cancellations in this tenure range |
| 5+ Years | Cancellations in this tenure range |
| Total | Total cancellations for this reason |
| % | Percentage of all cancellations |
A Total row at the bottom shows the sum for each tenure column.
Team Tab
A table showing how many cancellations are associated with each team, along with a visual distribution bar:
| Column | Description |
|---|---|
| Team | Team name |
| Distribution | A progress bar showing the team's share relative to the highest-count team |
| Count | Total cancellations for this team |
| % | Percentage of all cancellations |
Use this tab to see whether cancellations are concentrated on specific teams, which may point to service quality or scheduling issues.
Data Tab
The full grid with one row per cancelled customer. If the Early Churn filter is active (triggered by clicking the KPI card), only early churn rows appear here.
| Column | Description |
|---|---|
| Customer | Customer name and property name |
| Lead Source | How the customer originally found you |
| Scope Group | The service set type group for their service |
| Client Since | The date of their first service |
| Cancellation Date | The date their service was cancelled |
| Default Teams | The teams assigned to this customer |
| Frequency | How often they were scheduled (weekly, bi-weekly, etc.) |
| Bill Rate | The bill rate at the time of cancellation |
| Reason | The cancellation reason |
| Avg Scorecard | Average star rating across all their survey responses |
| Last Scorecard | Their most recent survey rating and response label |
| Early Churn | An Early badge appears if they cancelled within 60 days |
| Tenure | How long they were a customer (e.g., "8 months", "2.5 years") |
The Notes column (visible in the export) contains any notes recorded on the cancellation ticket.
Export to CSV or Excel
Click Export in the toolbar and choose CSV or Excel to download the currently visible records.
The export can include these columns:
- Customer, Property, Lead Source, Scope Group, Client Since, Cancellation Date, Default Teams, Frequency, Bill Rate, Reason, Avg Scorecard, Last Scorecard, Early Churn, Tenure (Days), Tenure Bucket, Notes
When you export from the Data tab, a column you hide there is left out of the file, and so are rows removed by a column filter. The file's Property column comes with the Customer column, and its Tenure (Days) and Tenure Bucket columns both come with the Tenure column. Exporting from the Reason or Team tab includes every column.
The file is named cancelled-customers-YYYY-MM-DD.csv (or .xlsx) using today's date.
If the Early Churn filter is active when you export, the file only includes early churn records. Turn off the filter first if you want all cancellations in the file.
Tips
- Start with the Reason tab to see which cancellation reasons are most common — then switch to Tenure to see if those same reasons tend to happen early or late in the customer relationship.
- Click the Early Churn card to quickly isolate customers who cancelled within 60 days. A high early churn rate usually points to first-impression or onboarding problems.
- Use the Tenure Distribution chart to understand whether you're losing customers early or after long tenures. Each requires a different response.
- Check the Team tab if cancellations are higher than usual — a team with a disproportionate share may need attention.
- Look at Avg Scorecard in the Data tab to see which cancelled customers had poor scores before leaving. Low scores alongside a cancellation may point to unresolved complaints.
- Widen the date range to 6 or 12 months to get enough data for the trend chart to show meaningful patterns.
- Export before a retention review to share a full list of recent cancellations with reasons and tenure data with your leadership team.
Troubleshooting
| Issue | What to Check |
|---|---|
| No data showing | Confirm the date range includes periods with cancellations. The default is the last 3 months. |
| Early Churn filter is on but not obvious | Look for the ring highlight on the Early Churn KPI card. Click it again to clear the filter. |
| Reason tab shows no data | Cancellation reasons are pulled from contact tickets. If no reasons were recorded on cancellations, the tab may be empty. |
| Team tab shows "Unassigned" rows | Some cancelled customers may not have had a default team assigned. |
| Trend chart is flat or empty | If cancellations are spread over a wide date range or few records exist, the trend line may appear flat. Try narrowing the range. |
Related Articles
- Scorecard Results — Review survey responses and scores from cancelled customers
- Analytics Suite and Specialized Reports — Overview of all specialized report types