Average Ticket Handling Time - Ticket & Annotations Report

Index:

1. Introduction 
2. Average ticket handling time
3. Metric

Introduction

Discover the most important charts for analyzing the STILINGUE Conversations service operation 

One of the highlighted objectives within the Reporting area of STILINGUE Conversations is the ability to combine service data for practical analysis. This is possible by understanding how some of the charts work. 

Learn how to access this area by clicking here to read the guide. 

Average Ticket Handling Time 

This metric is calculated using a simple average with the sum of all service interactions within the applied date range, regardless of when the conversation started. 

If it is necessary to analyze two or more different ticket handling times (average) generated separately in different date filters, it is important to calculate the average between them. For this, a weighted average is used, where the weight is the number of ticket in each period. 

Example: 

Day 1 - 70 ticket completed

Time: average of 15 minutes per ticket

Day 2 - 5 ticket completed 

Time: average of 20 minutes per ticket

Using data from the two days, it is possible to perform the following calculation by converting the average time to seconds:

[ (70 ticket x 900s ) + (5 ticket x 1200s ) ] / 70 ticket + 5 ticket 

= (63000s + 6000s) / 75 ticket 

= 69000s / 75 ticket 

= 920s per ticket or 15.33 min (15min19s) per ticket.

Note:  If you do not have a Calendar registered in the General Settings, the Average Ticket Handling Time will be calculated based on the system's default calendar, which covers the following period:

Monday to Friday - 00:00 to 23:59 (does not include Saturday and Sunday).

Metric

The metric adds up the status change times between: 

This chart represents the average ticket handling time, with the reference being the status annotation date.   

The percentage value below the main number refers to the variation in average ticket handling time compared to the previous filter. 

The bars in the ATHT chart illustrate the temporal variation of the value on a day-to-day basis. For instance, if the filter spans more than a month, only the last month will be considered. The displayed bars are sample references showing the proportion of ATHT in the filtered period, but they are not realistic.

The purpose of displaying the chart is to provide the customer with a visual source to identify any service pattern in the specific period. If there is any period that deviates from the norm, the customer can narrow down the filter to the indicated period and investigate the details about this outlier curve.

Important Note: In the event of issues or conversations that become obstructed (i.e., with excessive delays at any point during the service), the service flow—and consequently the AHT (Average Handling Time)—may be affected. This happens because the AHT is calculated as the sum of all completed interactions, and any variation in the duration of a single interaction can directly impact the final result.

For more information, visit the discussion on the subject at our community or videos on our channel. 😃