Timeline filters | Description | Example |
Last 24 Hours | Displays data for the previous 24 hours from the current time | If the user generates the report at 3 PM on March 28, the lifecycle report will show data from 3 PM on March 27 to 3 PM on March 28. |
Today | Shows data from 12:00 AM to the current time on the same day. | If the user generate the report at 2 PM on March 28, it will show data from 12:00 AM to 2 PM. |
Yesterday | Displays data for the entire previous day (from 12:00 AM to 11:59 PM). | If the user generates the report on March 28, this filter shows data from March 27. |
Last 7 days | Includes data from the previous 7 calendar days, including today. | On March 28, this filter covers data from March 22 to March 28. |
Last 30 days | Includes data from the previous 30 calendar days, including today. | On March 28, this filter covers data from February 27 to March 28. |
Current week | Displays data from the start of the current week (Monday) to the current time. | On Thursday, March 28, this filter shows data from Monday, March 25, to March 28. |
Last week | Displays data for the previous calendar week (Monday to Sunday). | On March 28, this filter shows data from March 18 to March 24. |
Current month | Shows data from the 1st of the current month to the current time. | On March 28, this filter covers March 1 to March 28. |
Last month | Displays data for the entire previous month. | On March 28, this filter shows data from February 1 to February 28. |
Custom | User can define a specific date range from two given date setters. one will be the start date and another will be the end date. | User can select March 1 in the start date date setter and March 15 in the end date date setter to filter out the records from March 1 to March 15. |
Group by | Description | Example |
Tickets ID | Displays the report by individual ticket IDs as the lifecycle details will be Status updated from, Status updated to, and Duration for each ticket. This helps the user understand how a specific ticket moved through each stage, identify where it spent the most time, and investigate delays in resolution. | The user can analyze why a high-priority ticket remained On Hold for over 3 hours before being addressed, possibly due to awaiting approval from a manager or pending information from another department like billing. |
Status updated from | Displays the report based on the status from which the ticket was updated to understand where the tickets are coming from and how those transitions are impacting resolution time. | If the tickets are frequently moving from the Waiting on Customer status after a long hold, it may mean that the customers are not responding quickly so that you could send automated follow-ups to reduce delays. |
Status update to | Displays the report based on the status the ticket moved to from a previous status to understand where the tickets are being routed and whether they often end up in the same status, such as On Hold or Escalated. | If many tickets are being updated to Escalated and show a long duration afterward, this could highlight a process gap where frontline agents escalate too quickly or senior teams take longer to respond. |
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