Are you noticing decreased customer satisfaction? Are your customer service teams feeling stressed or overwhelmed? This could indicate that you’re taking too long to respond to customer tickets (increasing customer frustration) and overwhelming your support team with a backlog of tickets that could be better resolved through other channels or processes.
Optimizing your mean time to resolution (MTTR) greatly benefits both your customer and internal support teams. However, first, you need to understand what issues could benefit from a reduced resolution time and take steps to resolve these faster.
In this article, we’ll explain MTTR’s importance for your customer support teams, strategies to improve ticket resolution time, and how to identify issues to focus MTTR reduction.
- What is mean time to resolution (MTTR)?
- How to calculate MTTR
- Mean time to resolution benchmarks
- How to choose the right issues to reduce MTTR
- Strategies to improve MTTR
- Example solutions to decrease resolution time
- How can customer satisfaction software help decrease mean time to resolution?
What is mean time to resolution (MTTR)?
MTTR is a customer support metric used to measure the time between a customer support incident report and its resolution. This service desk metric helps businesses learn where and how to optimize their support services to best serve their customers.
90% of customers expect an “immediate” (less than 10 minutes) response when they contact you.
You can calculate MTTR to understand which issues take the longest to resolve. Based on this data, your customer service team can take steps to shorten average resolution time when it’s in their customer’s best interest, ultimately improving customer and brand satisfaction.
How to calculate MTTR
Before calculating your mean time to resolution, you must first define clear beginning and endpoints. For example, the beginning point for a ticket could be when the issue is picked up by an agent or by the timestamp on a submitted ticket. The endpoint could be when the agent hangs up the call, or when they have completed the post-call paperwork or actions. Delineate clear start and end points that work for your business.
Then, calculate the mean time to resolution for a given period using this formula:
|Total resolution time / # of issues = MTTR
Using the above formula, add the total time spent on all tickets and divide it by the number of tickets to get your mean resolution time.
Example: Let’s assume you have five calls with the below durations:
- 5 minutes
- 5 minutes
- 2 minutes
- 10 minutes
- 8 minutes
Your formula would be:
|30 minutes / 5 issues = 6 minutes MTTR
Mean time to resolution benchmarks
Many businesses make the mistake of seeing a “long” MTTR time and instantly want to shorten it. However, not all issues can benefit from shorter resolution times. More complicated matters may naturally require more time to resolve (due to the steps involved). Standard issues, like resetting passwords or updating account settings, shouldn’t take as long.
While there are many variables, including your customer’s expectations and the type of issue, you should aim for the following average resolution times:
- Phone (3-7 minutes): Most customers expect fast responses to phone help desk tickets. They chose this channel to contact you because they expected a quick resolution before they hung up.
- Email (24 hours): Generally, customers won’t email urgent issues. As such, they expect that emails are only responded to during business hours but expect you to answer the next business day if the same day is impossible.
- Self-Service Options (instant): If you have self-service options like a knowledge base or chatbot, people expect their answers to be easily found in these systems immediately.
- Live chat (10 minutes): Many lose interest if waiting on hold on a live text chat for too long.
- Social Media (instant or 24 hours): If you’ve set the expectation of fast responses to support queries on social media, your customers likely expect to wait no more than 10 minutes for your response to a tagged post or direct message. Otherwise, they expect their query to be answered during business hours or the next day if needed.
How to choose the right issues to reduce MTTR
Not every user issue is a good candidate for reducing your mean time to resolution. In some cases, a longer time to resolution is necessary due to:
- The complexity of the issue (many non-negotiable steps are required to solve)
- Customers preferring to speak to a live agent for resolution (and don’t want to tell a chatbot).
An example of good issues to reduce MMTR are simple issues with a standard fix. If the issue can be easily resolved through an automated system (like a helpdesk article or chatbot prompt), then it’s a likely candidate for reducing the time to resolution. These issues may include password resetting, updating account details, or updating the credit card on file.
Strategies to improve MTTR
When you have identified the issues you want to shorten resolution times for, here are some strategies to try:
Improve ticket prioritization
Review your process for triaging and prioritizing tickets. For example, low-priority tickets may be pushed to the end of your list, even though they may be quick to solve once opened. These normally quick-resolution tickets rack up time as they sit unanswered while an agent deals with bigger issues, which can inflate your time to resolution numbers.
Instead, review how you are prioritizing and distributing tickets to team members. You could create a customer support team that gets all the low-priority or quick-resolution tickets so they don’t get forgotten while other teams deal with the bigger tickets. Or you could deflect these tickets to a self-service option so the customer doesn’t have to wait.
👉Learn which of your tickets cost the most time and money with our Ticket Driver Report. Get your report now.
Customer service automations can help you instantly decrease the average time spent on help desk tickets. For example, when submitting a ticket, AI can review the contents and send the customer a pre-written email with links to commonly asked questions (such as password reset or login troubleshooting). Using an AI chatbot is an automation that can quickly answer customer queries, saving your live agents for VIP issues that require more advanced troubleshooting or support.
👉Is your chatbot optimized as well as possible to reduce customer frustrations and improve ticket resolution times? Learn how to evaluate your chatbot performance.
Fix recurring issues
Look at the types and topics of the support tickets you get most often (regardless of their mean time to resolution). Are there recurring issues you can resolve at the source (such as fixing a bug on a payment page)? If rectified, these issues won’t take up any more space and time in your support queue.
Review support workflows
Are there other ways you can help your support teams increase efficiency? Look at the workflow of your support team and look for ways to optimize, automate, or eliminate steps.
Here are some strategies that can help you optimize your support workflows:
- Update support scripts.
- Create an internal knowledge base.
- Provide additional support training for staff.
- Ask for more information in ticket reports so agents don’t have to ask.
- Review escalation procedures so time isn’t wasted bouncing the call from person to person.
Add a ticket deflection strategy
Are you receiving recurring tickets that have simple resolutions? Look at deflecting those help desk tickets to a customer self-service option like a knowledge-based article, video, or resource. You can identify these issues by analyzing the text of incoming support tickets and automatically sending the customer a link to the desired resolution.
Be careful with deflection strategies, as the customer may still need or want to talk to a support agent. Always provide a way for the customer to continue and speak with an agent.
Listen to customer feedback
Consider customer feedback when determining which issues could benefit from a decrease in MTTR. For example, your VIP customers may enjoy personalized, human support more than your first-time customers who would rather solve their issues without speaking with anyone.
You can gather targeted feedback on customer thoughts regarding resolution time and satisfaction by having customers complete a short survey after their support interaction while the situation is still top of mind. Keep this survey short at one or two questions to help increase response rates.
👉 Understand your customer’s voice like never before. Learn about Idiomatic’s AI-driven customer feedback analytics to dive deep into customer feedback data and improve your MTTR strategies. Learn More
Increase real-time monitoring
Use real-time monitoring to alert you to increases in mean time to resolution before they get out of control. With AI-powered monitoring of your customer service tickets and calls with a platform like Idiomatic, you can get notified of an increase in specific categories or topics so you can take action to resolve the root issue or prepare your teams to deal with them promptly.
For example, you may get alerted that your meantime to resolution is the highest it’s been in 30 days. When you look at why, you can see that the last three days had many customers reporting that their monthly account summary emails displayed the wrong information, requiring agents to spend extra time combing through invoices. Based on this, you can see a clear solution and make the fix to bring your MTTR back to your company’s acceptable averages.
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Example solutions to decrease resolution time
Below are five common roadblocks that increase time to resolution, and potential solutions to resolve them:
|First response time is too slow. (If ticket submission time is used as a ticket’s beginning point.)
|Customer service conversations are too long.
|Customer problems are unique and complex.
|The same issues keep arising and inflating your average resolution times.
|Internal work time between calls is long.
How can customer satisfaction software help decrease mean time to resolution?
We’ve seen many businesses miss a huge opportunity when calculating their MTTR. Some companies look at their overall resolution time but don’t have the data to dig deeper to see customer issues ranked by their MTTR. With this level of granular data, you get more specific insights into where inefficiencies or customer satisfaction exist so you can take action to correct or improve them.
An AI-driven customer feedback analytics platform like Idiomatic helps you identify which issues cause the most user dissatisfaction and why. Idiomatic gathers customer feedback data from all your sources, including chatbots, help desk tickets, service calls, app reviews, and social media comments, and analyzes it at scale. You can then view all ticket data, sorted by topic volume, cost and other metrics in an easy-to-read dashboard to dig deeper to see how these tickets impacted customer satisfaction scores. This data can serve as a basis to find which recurring issues could be diverted to other support channels to decrease the time to resolution. It can also help you measure the ROI of changes based on help desk ticket data.
Lowering MTTR generally increases overall customer happiness, but not every issue benefits from this strategy. The ability to examine your tickets by type or specific question can help you identify which are good candidates for reducing the mean time to resolution and increasing customer happiness. To help in this analysis and actions to reduce resolution time, Idiomatic can:
- Identify customer issues (collection of tickets with the same issues) that result in high MTTR, so you know what to fix.
- Help you triage tickets and route them to the best-qualified agent to respond.
- Monitor spiking ticket volumes and alert you to issues so you can nip them in the bud, before they impact your ticket resolution times, and decrease customer satisfaction.
- Segment your customer and ticket data to see what variables or audiences contribute to longer mean time to resolutions.
Optimize your MTTR with Idiomatic’s customer satisfaction software. Request a free, no-obligation demo to understand your customer support performance in-depth.