This metric shows the number of tickets that have missed their due date, segmented by priority level (low, medium, high, urgent).
With Databox you can track all your metrics from various data sources in one place.
Used to show comparisons between values.
Databox is a business analytics software that allows you to track and visualize your most important metrics from any data source in one centralized platform.
To track Overdue Tickets by Priority using Databox, follow these steps:
The Created Tickets metric in Freshdesk measures the total number of new support requests submitted by customers over a certain period of time.
The Hours Tracked metric in Freshdesk measures the time spent by agents on each ticket, providing insights into productivity, customer satisfaction, and performance evaluation.
The Billable Hours by Company metric is a measurement of the total hours worked on billable tasks per company. It indicates the revenue generated by each company and helps in evaluating profitability and resource allocation.
The Pending Tickets metric represents the number of support tickets that are awaiting action or response from agents or customers. It is a key indicator of workload and efficiency in customer support operations.
The Resolved Tickets by Company metric in Freshdesk shows the number of tickets resolved by each company, providing a measure of customer satisfaction and support team performance for individual companies.
The Resolved Tickets by Source metric shows the number of support tickets that have been resolved within a specific time frame, grouped by the source from which they originated (e.g. email, phone, chat, social media).
Resolved Tickets by Priority metric categorizes the resolved tickets based on their priority and shows their count, helping in monitoring and improving the resolution times of high-priority tickets.
The Contacts by State metric provides a breakdown of the number of contacts in each state or region, allowing businesses to analyze customer distribution and tailor their support accordingly.