Overview Dashboard
The overview dashboard is placed under the Popular Dashboards. It is the default dashboard that is displayed when a user navigates to the Analytics module > Dashboards.
The dashboard displays data that helps support managers manage their daily operations efficiently. They can monitor the current number of open tickets, number of unassigned tickets, overdue tickets, and more, and take necessary actions to speed up the resolution process.
Note: The filter by duration is not applicable for the KPI cards.
A further breakdown of the data gives insights on the average ticket handling time, traffic analysis, and happiness rating, which can be used to optimize the existing customer service processes to foster long-term customer satisfaction.
The dashboard includes four important components:
- Ticket stats
- Traffic analysis
- Average handling time
- Happiness rate
Filter by duration
Select any of the following duration from the top left to filter all widgets on the overview dashboard. Individual widget filtering is not available.
- Last 24 Hours
- Today
- Yesterday
- Last 7 days
- Last 30 days
- Current week
- Last week
- Current month
- Last month
- Custom
Ticket stats
- New Tickets: Number of new tickets created in the selected duration.
- On Hold Tickets: Number of tickets that are in the On hold status.
- Closed Tickets: Number of tickets closed tickets within the selected duration.
- Backlog Tickets: The average number of tickets that were not closed by the end of the day.
A graphical representation of ticket statistics that gives users first-hand information on the number of New Requests, On Hold requests, Closed tickets, and Backlog tickets.
The time when the tickets were raised is displayed in the x-axis, and the ticket count is displayed in the y-axis.
Users can click on the legends to view the tickets under each category. Hovering on the graph will display the ticket count for each timeline.
Traffic analysis
The number of tickets raised through each channel, including web, channel support, email, WhatsApp, phone, and chat, is displayed in this widget.
By analyzing this data, managers can identify the channels that receive the highest number of tickets, and assign agents accordingly to ensure quick and effective response times. It can also indicate the mode of communication preferred by the customers, using which business can improve their customer engagement programs. For example, if most of the users are comfortable with chat and not channel support, the managers can reallocate a few agents to handle the volume of chats in order to enhance user experience.
Users can select the channels to view channel-wise tickets. Hovering on the chart will display the ticket count for the selected channels. The data can be viewed in donut graph or tabular format.
Average handling time
Customers expect quick and efficient support, and it is crucial for the organizations to provide timely resolution and adhere to the FRT and SLAs.
The following metrics can be tracked :
- First response time - Time taken to send the first response after the ticket was created.
- Response time - Average time agents take to respond to all customer queries.All the replies sent in a thread are calculated.
- Resolution time - Average time agents take to resolve a ticket. The resolution time is calculated from the time the ticket is created to the time the ticket is marked as closed.
Users can change the display type to Table from the drop-down.
Happiness rating
Customer ratings are important to assess the support team's performance. This graph displays the percent of customers who gave positive, neutral, and negative ratings to the service.
A positive rating percentage indicates that the customer is satisfied with the support offered, and the negative percentage indicates that the customer is unhappy with the support.
Managers can assess customer satisfaction using these metrics. This can help the team improve their performance, resulting in a higher customer satisfaction rate.
Users can change the display type to Table from the drop-down.
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