How to Access the Appointments Dashboard
Locate the Reports section in the top navigation toolbar. Click Reports, hover over Insights Hub, and select Appointments. This dashboard surfaces key appointment metrics that help you evaluate scheduling performance and operational efficiency.
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Overview
The Appointments Dashboard is your central place to review appointment-related performance across your practice. This dashboard provides visibility into scheduling efficiency, appointment outcomes, inquiry conversions, staff utilization, and patient behavior so you can identify trends and optimize operations.
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Using the Dashboard
Dashboard Controls and Navigation
At the top of the Accounting Dashboard, you’ll find global controls that apply to the entire report.
Use the Filter (funnel) icon to filter the dashboard by:
Location
Date range
Select the up arrow icon to export the full dashboard as a PowerPoint or PDF, making it easy to share financial insights with owners, managers, or accounting teams.
Review the last updated date and time to confirm when the dashboard was most recently refreshed. Accounting dashboards update automatically every few hours.
Widget-Level Filtering, Exporting, and Drill-Down
Each widget includes its own interaction options:
Expand arrow to open the widget view
Funnel icon for widget-level filtering
Table icon to display data in table format
Ellipsis menu for export options
Individual widgets can be exported as CSV, Print, PowerPoint, or Excel. You can also click directly on metrics within widgets to drill down by location or employee, helping trace financial activity back to its source.
Year-Over-Year Comparisons
Some widgets display a percentage with an upward or downward arrow. These indicators represent year-over-year comparisons that dynamically adjust based on the selected date range. For example, filtering to the current month compares results to the same month last year.
More information on how to use the dashboard controls:
Section-Specific Metric Overview
Top-Level Appointment Metrics
In the top row of the dashboard, you’ll see New Inquiries. These are clients who have been added to the system but have not been scheduled within the selected time frame.
You’ll also see your Number of Consultations and Appointments Scheduled. It’s important to note that the system recognizes a consultation only when the Consultation box is checked in the service configuration. If this feature is not being used, the consultation widgets will not pull data.
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Appointments Completed Metrics
Next, you’ll see Appointments Completed. These are appointments that have been checked in and checked out. If an appointment is not checked out, it will not be counted as completed.
Along with that, you’ll see the Percentage of Appointments Completed, which shows how many scheduled appointments were successfully completed within the selected time frame.
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Appointments Over Time
Below that is the Appointments Over Time widget. This shows appointment activity across the selected time period, broken down by:
Completed appointments
Cancellations
No-shows
Scheduled to be completed
Scheduled-to-be-completed appointments include appointments that have been scheduled but have not yet occurred, as well as appointments that were checked in but not checked out.
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Inquiry Conversion Over Time
You’ll also see Inquiry to Appointment Over Time and Inquiry to Consultation Over Time. These widgets show how many conversions have occurred during the selected time period.
Inquiry to Appointment measures inquiries that went on to book an appointment
Inquiry to Consultation measures inquiries that specifically booked a consultation
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Appointment Behavior and Efficiency Metrics
You can also review:
Average appointments per customer
Average days between appointments
No-show rate
Cancellation rate
Average time spent in room
The no-show rate and cancellation rate widgets are especially useful to drill into, allowing you to view these metrics by location and employee to identify trends or opportunities for improvement.
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Appointments by Service Type
The First Scheduled Appointments by Service Type widget shows a breakdown of first booked appointments by service type based on the selected time frame.
You’ll also see Return Appointments by Service Type, which shows returning clients by service ID. It’s important to note that service type in these widgets represents the Service ID.
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Staff Utilization
The Staff Utilization metric is calculated by comparing an employee’s scheduled working hours to their actual appointment time.
For example, if an employee has 6 scheduled work hours but 8 hours of appointments scheduled during the same day, the staff utilization metric will increase. This helps you understand how much of an employee’s scheduled time is being filled by appointments.
You can select this report to drill down by employee, and you can continue clicking to drill down further. Just remember to click more than once to continue drilling.
Beside this, you’ll see a Staff Utilization Over Time graph, allowing you to track utilization trends across the selected period.
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Wait Time and Scheduling Patterns
The Average Wait Time is calculated based on the appointment start time versus the check-in time. If clients are typically checked in late or only checked in at the end of the day, this will impact this report.
The Average Number of Appointments by Day and Time of Day calculates the average appointment volume based on both the day of the week and the time of day, helping you identify peak scheduling periods.
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Key Appointment Metrics by Service Type
The Key Appointment Metrics by Service Type widget breaks down each service type by:
Scheduled to be completed
Completed appointments
Average days to next appointment
Cancellations and cancellation rate
No-shows and no-show rate
Average days to next appointment represents the average number of days between services.
You can select any service type to drill down by location, and then click again to drill down by employee.
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FILTERS - ALL DASHBOARDS
Filter
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Expected Behavior
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Current -> This Week
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Data will show current week, Sunday-Saturday
ex. If today’s date is a Friday, this filter would show data from the most recent Sunday to Friday
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Current -> This Month
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Data will show from all days in the current calendar month
ex. If today’s date is in January, this filter would show data from January
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Current -> This Quarter
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Data will show from all days in the current calendar quarter
ex. If today’s date is in Q2, this filter would show data from Q2
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Current -> This Year
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Data will show from all days in the current calendar year
ex. If today’s date is in 2026, this filter would show data from 2026
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To Date -> Week-to-Date
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Data will show from previous Sunday to current day
ex. If today’s date is a Thursday, this filter would show data from the current Sunday to Thursday
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To Date -> Month-to-Date
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Data will show from first day of the current calendar month to the current day
ex. If today’s date is the 15th of the month, this filter would show data from the 1st of the month to the 15th
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To Date -> Quarter-to-Date
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Data will show from first day of the current calendar quarter to the current day
ex. If today’s date is in January, this filter would show data from January
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To Date -> Year-to-Date
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Data will show from first day of the current calendar year to the current day
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Previous -> Previous Week
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Data will show from the previous week Sunday to Saturday
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Previous -> Previous Month
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Data will show from the previous calendar month
ex. If today’s date is in January, this filter would show data from December
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Previous -> Previous Quarter
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Data will show from the previous calendar quarter
ex. If today’s date is in Q2, this filter would show data from Q1
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Previous -> Previous Year
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Data will show from the previous calendar year
ex. If today’s date is in 2026, this filter would show data from 2025
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Next -> Next Week
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Data will show from the upcoming Sunday to the following Saturday
ex. If today’s date is a Thursday, data show from the upcoming Sunday to the following Saturday
Note: Phase 1 foundational dashboards do not respond to this filter
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Next -> Next Month
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Data will show from all days of the next calendar month
ex. If today’s date is in January, this filter would show data from February
Note: Phase 1 foundational dashboards do not respond to this filter
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Next -> Next Quarter
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Data will show from all days of the next calendar quarter
ex. If today’s date is in Q1, this filter would show data from Q2
Note: Phase 1 foundational dashboards do not respond to this filter
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Next -> Next Year
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Data will show from all days of the next calendar year
ex. If today’s date is in 2025, this filter would show data from 2026
Note: Phase 1 foundational dashboards do not respond to this filter
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Last -> Last Hour
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Data will show starting from the current hour to as many hours as selected back
ex. If “Last 3 Hours” is filtered, data will show for the current hour and the 2 hours prior, if “Last 1 Hour” is filtered, data will show for the current hour
NOTE: currently the dashboards update every few hours, so this filter is not recommended at the current refresh cadence
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Last -> Last Day
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Data will show starting from the current day to as many days as selected back
ex. If “Last 3 Days” is filtered, data will show for the current day and the 2 days prior, if “Last 1 Day” is filtered, data will show for the current day
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Last -> Last Week
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Data will show starting from the current week to as many weeks as selected back
ex. If “Last 3 Weeks” is filtered, data will show for the current week and the 2 weeks prior, if “Last 1 Week” is filtered, data will show for the current week
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Last -> Last Month
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Data will show starting from the current month to as many months as selected back
ex. If “Last 3 Months” is filtered, data will show for the current month and the 2 months prior, if “Last 1 Month” is filtered, data will show for the current month
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Last -> Last Quarter
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Data will show starting from the current quarter to as many quarter as selected back
ex. If “Last 3 Quarters” is filtered, data will show for the current quarter and the 2 quarters prior, if “Last 1 Quarter” is filtered, data will show for the current quarter
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Last -> Last Year
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Data will show starting from the current year to as many years as selected back
ex. If “Last 3 Years” is filtered, data will show for the current year and the 2 years prior, if “Last 1 Year” is filtered, data will show for the current year
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APPOINTMENTS DASHBOARD
KPI
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Calculation
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New Inquiries
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Count of total unique inquiries made to practice
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Consultations
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Count of total unique appointments where the appointment is marked as a consultation
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Appointments Scheduled
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Count of unique appointments that are scheduled to be completed
Note: Scheduled to be completed is an appointment that is on the schedule but has not been checked out yet and is not a no-show/cancellation
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Appointments Completed
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Count of appointments where the appointment was finished as expected (i.e. not a no-show or cancellation and has been checked out)
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% Appointments Completed
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Count of appointments completed / Count of all appointments (scheduled to be completed, no-shows, cancellations, appointments completed)
Note: Appointments completed are appointments where the appointment was finished as expected (i.e. not a no-show or cancellation and has been checked out). Scheduled to be completed is an appointment that is on the schedule but has not been checked out yet and is not a no-show/cancellation
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Appointments Over Time
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Count of appointments shown by date and appointment classification (i.e. completed, scheduled to be completed, no-shows, cancellations)
Note: Scheduled to be completed is an appointment that is on the schedule but has not been checked out yet and is not a no-show/cancellation
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Inquiry to Appointment Over Time
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Total number of unique inquiries converted to appointments / Total number of unique inquiries
Note: An inquiry is considered converted when an appointment occurs after the inquiry creation date and the appointment is not a no-show or cancellation
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Inquiry to Consultation Over Time
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Total number of unique inquiries converted to consultations / Total number of unique inquiries
Note: An inquiry is considered converted when an appointment marked as “consultation” occurs after the inquiry creation date and the consultation is not a no-show or cancellation
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Avg. Appts Per Customer
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Total unique appointments / Total unique customers
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Avg. Days Between Appts
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Sum of the days until next scheduled appointment / Count of unique customers with a next appointment scheduled
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No Show Rate
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Count of appointments that were a no-show / Count of all appointments (scheduled to be completed, no-shows, cancellations, appointments completed)
Note: Appointments completed are appointments where the appointment was finished as expected (i.e. not a no-show or cancellation and has been checked out). Scheduled to be completed is an appointment that is on the schedule but has not been checked out yet and is not a no-show/cancellation
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Cancellation Rate
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Count of cancelled appointments / Count of all appointments
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Avg. Time Spent in Room
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Sum of initial and complementary time scheduled for an appointment in minutes, averaged across all appointments
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First Scheduled Appointments by Service Type
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Count of appointments where customer has never been seen by practice before, shown by the Service assigned to that appointment
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Return Appointments by Service Type
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Count of appointments where customer has been seen by practice before, shown by the Service assigned to that appointment
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Staff Utilization
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Staff time in appointments / Total scheduled working time
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Average Wait Time
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Minutes between scheduled appointment start time and actual check in time, averaged across all appointments
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Staff Utilization Over Time
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Staff time in appointments / Total scheduled working time, shown over time
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Average Number of Appointments by Day and Time of Day
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Aggregation of count of unique scheduled appointments within the selected date range, grouped by day and hour of the day where the appointment is scheduled to be completed
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Key Appointment Metrics by Service Type
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Peak Demand Forecasting by Day
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A projection of count of appointments completed
The forecast is calculated by using statistical models that take into account outcomes spanning over 90 days of past data and customer behavior on appointments, seasonality, and expected error rates to extend the historical patterns 90 days into the future
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