What Is Average Ticket Resolution Time?
The average ticket resolution time is the average duration it takes for a support team to resolve a customer support ticket - from the moment it is submitted to the moment it is successfully resolved.
Average Ticket Resolution Time Formula
To calculate the average ticket resolution time, divide the total time taken to resolve each ticket by the number of tickets resolved. While finding this number may seem straightforward, grasping its significance requires consideration of industry benchmarks, a competitive analysis, and establishing clear goals. Without these, the average ticket resolution time lacks context. Once a benchmark is established, you can track and see where you stand in relation to your goals.
Key Lessons Learned from Gathering This List
Building in-house platforms equipped with AI tools can significantly improve average ticket resolution time.
Implementing automated workflows is crucial for companies dealing with multiple support ticket requests over multiple departments.
Dealing with diverse communication channels, if not properly optimized, can lead to customer support inefficiencies.
Disconnected solutions and the use of multiple tools can slow down ticket resolutions.
Here’s how 4 companies improved their average ticket resolution time:
Uber built an in-house platform to reduce its average ticket resolution time
Handling hundreds of thousands of daily tickets spanning 400+ cities worldwide, Uber's Customer Obsession team utilizes five distinct customer-agent communication channels. These channels operate seamlessly on an in-house platform called COTA, integrating customer support ticket context for quick and easy issue resolution.
COTA uses machine learning and natural language processing (NLP) techniques to help Uber’s agents deliver better customer support. Leveraging its Michelangelo machine learning-as-a-service platform on top of its customer support platform, COTA enables quick and efficient issue resolution for the vast majority of its inbound support tickets.
Here’s how it works:
Directly from their blog; The COTA system architecture is composed of a seven-step workflow:
Once a new ticket enters the customer support platform (CSP), the back-end service collects all relevant features of the ticket.
The back-end service then sends these features to the machine-learning model in Michelangelo.
The model predicts scores for each possible solution.
The back-end service receives the predictions and scores and saves them to our Schemaless data store.
Once an agent opens a given ticket, the front-end service triggers the back-end service to check if there are any updates to the ticket. If there are no updates, the back-end service will retrieve the saved predictions; if there are updates, it will fetch the updated features and go through steps 2-4 again.
The back-end service returns the list of solutions ranked by the predicted score to the front end.
The top three ranked solutions are suggested to agents; from there, agents make a selection and resolve the support ticket.”
Using this seven-step workflow, COTA can reduce ticket resolution time by over 10 percent while delivering service with similar or higher levels of customer satisfaction.
Read the full article here.
By automating workflows, Brastel reduced ticket handling time by up to 39%
Brastel, a Tokyo-based telecommunications company set up 20 automated workflows and reduced its ticket handling time by up to 39% using HelpDesk.
Brastel provided customer support through a call center, but this proved insufficient as customers wanted to stay in touch through various communication channels based on their location.
However, in experimenting with numerous communication channels to satisfy its customers, employees had to navigate between tabs and multiple browser windows, marking the start of the struggle.
Working through it:
First, Brastel opted for LiveChat and combined all the social media channels they used into one interface to facilitate real-time message management. Next, they applied KnowledgeBase to gather the internal team's knowledge. With KnowledgeBase, the support team wrote help center articles and created useful FAQs for customers.
Everything seemed to work flawlessly until the support team noticed that a closer examination was needed for asynchronous communication and email support tickets. The ticket form provided in LiveChat became inadequate for Brastel because they were unable to customize email templates, add domains, collaborate on a ticket as a team, or establish ticket groups.
Switching to HelpDesk, The Brastel Remit team set up more than 20 automated workflows to communicate with customers and effectively manage the identity validation process. With automated workflows, Brastel’s cut down on routine procedures such as wasting time searching for emails leading to a major improvement in average ticket resolution time.
Here’s a link to the full case study.
Cymax Group reduced their response times by centralizing multichannel customer support
Cymax Group, a leading eCommerce technologies and services provider, reduced their average ticket resolution time by gaining comprehensive visibility across all communication channels with eDesk.
Managing hundreds of thousands of SKUs distributed across various marketplaces posed a growing challenge in delivering optimal customer experience. Cymax Group found it increasingly difficult to monitor response times and uphold expectations by manually logging into and overseeing message portals for each channel independently. Recognizing the need for a centralized system came about as the company tried to align with the evolving needs and expectations of its customer base in a rapidly expanding market.
Consolidate messages from multiple marketplaces into a single inbox.
After exploring different alternatives, Cymax Group decided to implement eDesk, a platform designed specifically for eCommerce. eDesk’s centralized inbox has helped the team at Cymax Group to revolutionize its workflows. With eDesk’s dashboard view, Cymax Group has comprehensive visibility across all communication channels, resulting in reduced response times and improved productivity.
Read the full article here.
Jeffco Public Schools reduced its average ticket resolution time from 3 weeks to 3 days by gathering the right data
Jeffco Public Schools, one of the largest in Colorado with over 50 central administrative departments was suffering from a ticket resolution time from 3 weeks to a month before switching to Freshworks.
The support teams at Jeffco were using a combination of disconnected solutions, shared inboxes, a homegrown Knowledge base, and a homegrown chat tool. This led to long ticket resolution time due to siloed processes and multiple tools that agents used across teams. Tickets weren’t often resolved for three weeks or even a month.
What prompted change:
Jeffco had used Oracle's PeopleSoft CRM for 10 years but realized they needed more. Agents didn’t have the information they needed on the support ticket. They were missing a lot of data points to resolve a ticket efficiently.
Jeffco chose Freshservice as their solution and also integrated Freshchat with it. With Freshworks, Jeffco reduced its average resolution time to 3 days by streamlining processes across its 30 departments, auto-assigning tickets, and using custom form fields for gathering critical information.
Read the full case study here.
Transforming Customer Support for Swift Solutions
Dealing with slow ticket support is a universal frustration and improving average ticket resolution time is crucial for both customer satisfaction and operational efficiency. These real-world case studies showcase actionable strategies for companies seeking to revamp their customer support processes and improve their average ticket resolution time, and just some of the tools available to help.