Peak times and ticket volume
In short: The Volume report counts how many tickets come in during a period and shows when it is busy: per time period, per hour of the day and per day of the week, with a heatmap of day by hour. You can use it to plan your staffing and opening hours.
Where to find this
Go to Analytics > Volume. The page is called Peak Moments, with the addition Ticket Volume in the title, and has the subtitle Identify peak moments, busiest hours, and weekly patterns.
Who: from the Team lead role. For accounts with several organisations, you choose with Organisation which ones are included; if you choose nothing, all organisations you have access to are included.
The Peak Moments report (menu Analytics > Volume) with the four cards, the trend chart and the charts per hour and per weekday.
What is counted
A ticket counts at the moment of the first customer message. If a ticket has no customer message (for example a ticket a colleague created themselves), the ticket’s creation date counts. All times are in your browser’s local time.
Filters
Choose the filters and click Refresh.
| Filter | Meaning | Default |
|---|---|---|
| Date range | The period. Quick buttons 7d, 30d, 90d, 180d and YTD, or your own start and end date. | Last 30 days |
| Group by | The size of the time periods in the trend chart: Auto, Daily, Weekly or Monthly. With Auto, aishaa chooses hourly up to 48 hours, daily up to 180 days, weekly up to 540 days and monthly above that. | Auto |
| Organisation | Only for accounts with more than one organisation. | All organisations you have access to |
| Channel | Only tickets from the chosen channels. | All channels |
aishaa remembers per user the date range (quick buttons only), the grouping and the chosen organisations. That choice also applies to the Response times and Topics reports.
The four cards
| Card | Meaning |
|---|---|
| Total tickets | The number of tickets in the period that match the filters. |
| Peak bucket | The time period with the most tickets, with date, time and number. |
| Peak hour(s) | The three hours of the day with the most tickets, for example 10:00, 11:00 and 14:00. |
| Peak weekday(s) | The three weekdays with the most tickets. |
Charts
The report consists of four charts. Each chart uses the same filters as the cards above it.
Trend
The Trend chart (Ticket volume over time, grouped by the selected interval.) shows the number of tickets per time period as the Tickets line. If you choose Daily, Weekly or Monthly yourself under Group by, there is a second line, Forecast, for the coming time periods: 14 days, 8 weeks or 6 months. With Auto there is no forecast. The titles of the Peak bucket card and the Trend chart include the grouping, for example (Daily).
The forecast is a moving average, not a model that knows about seasons or campaigns: aishaa takes the average of the last time periods (7 days, 4 weeks or 3 months) and continues that average as a flat line. Use the line as an indication of the normal level, not as an exact forecast.
By hour of day (local)
The bar chart By hour of day (local) (Busiest hours (local time)) shows the number of tickets per hour, from 0 to 23. The busiest hours are marked as Peak, the others as Other.
By day of week (local)
The bar chart By day of week (local) (Busiest days (local time)) shows the number of tickets per weekday, with the same Peak and Other marking.
Weekly heatmap (day x hour)
The Weekly heatmap (day × hour) (Ticket volume by day of week and hour (local time).) is a grid of seven days by 24 hours. The busier a cell, the fuller the colour. Below the grid is a scale from the lowest to the highest value. Hover over a cell to see the day, the hour and the number.
The Weekly heatmap (day x hour) at the bottom of the Volume report, with the busiest cells in the fullest colour.
How aishaa determines a peak
A time period, hour or weekday counts as a peak if the number of tickets is at least one and a half standard deviations above the average. If no moment is above that, aishaa marks the highest point as the peak.
Good to know
- Under Group by, this report has no option without grouping.
- The times follow your browser’s time zone. A colleague working in a different time zone sees different hours.
- A short date range (for example 7 days) gives an erratic heatmap; choose 30 days or more for a reliable weekly pattern.
- Without data you see No data for selected range. or No hourly data.; if loading fails, Failed to load peak moments.
- There is no export of this report. See Sharing figures without an export.