“I talked to an agent yesterday, but I still need help…”
Your customers want to avoid contact center conversations that start like this.
But, when they’re unable to achieve their goals, they’ll go to great lengths to get the answers they need. And, for your customer service team, that can mean countless conversations, chats, and emails that can artificially inflate your call volume numbers.
In your customer’s ideal world—and, yours too—every request would be solved on the first customer support interaction. We don’t live in a perfect world, but there are steps you can take to improve an important metric: first call resolution.
So, what exactly is first call resolution (or “FCR,” for short)?
First call resolution—sometimes referred to as “one call resolution” or “first contact resolution” on omnichannel customer experience teams—is the rate at which support tickets are resolved on the first call or contact (chat, email, etc.). First call resolution rates are typically expressed as a percentage of all calls a support team handles.
To calculate the first call resolution rate for your company, divide the number of support tickets that were resolved on the first contact by the total tickets from the same period. (If your company routinely deals with complex or technical requests that cannot reasonably be solved on the first interaction, you may want to exclude those from the total number of tickets.) Expressed as a formula, your FCR rate looks like this:
For example, let’s say that customers opened 1,200 tickets last month and 600 were resolved on the first contact. You guessed it—your first call resolution rate is 50%. Not bad, but you definitely have room for improvement!
Remember, FCR is concerned with one thing and one thing only: whether or not the customer’s issue is resolved on the first interaction. Note that FCR does not factor in the efficiency of the first call or contact. This means that improving FCR may come at the expense of other efficiency-based metrics, such as AHT (average handle time). Solving a customer’s problem on the first interaction means that your agents will need to spend more time clarifying questions, getting to the root cause of an issue, and checking for other problems. In the short term, FCR may actually lead to a slower support process—but one that’s much better for your customers, your agents, and your CSAT rating! ⭐⭐⭐⭐⭐
If FCR has an inverse relationship with AHT and other efficiency-based metrics, why spend any time thinking about it? Good question! Here are three big reasons:
Customers dread being placed on hold, getting transferred to other agents, and explaining their situations over and over again. Forcing customers to expend a lot of energy is not a good idea. And, doing so will only erode your CSAT (customer satisfaction) score in the long run. In fact, one support metric—the Customer Effort Score (CES)—actually measures customer satisfaction in terms of the ease or difficulty of the interaction.
Key takeaway: Customers want easy—not difficult. They want one interaction with support, not a bunch. Give customers what they want, and you’re sure to see a boost in CSAT.
Highly satisfied customers become loyal customers. Frustrated customers, on the other hand, are far more likely to shop for alternatives and churn. Having customers jump through hoops to resolve their issues provides a poor experience, which is a big reason why people get frustrated and leave.
Key takeaway: Solving issues on the first call reduces friction and sets the stage for long-term relationships.
Say what? Yes, you read that right. Improving FCR can actually have a positive impact on agent productivity. But, what about FCR’s inverse relationship with AHT and other efficiency-based metrics? It all comes down to perspective. Is your goal to “handle” customers in the least amount of time possible? (That’s what AHT basically measures.) Or, are you in the business of helping customers achieve their goals so that they become brand advocates? Pressuring agents to close out tickets as quickly as possible helps no one—including your agents.
Your agents want to make a difference. They want to help customers become more successful and feel fully satisfied with the experience. Prioritizing first call resolution encourages agents to do exactly that. It also unleashes their creativity to identify opportunities to efficiently serve customers, which leads to process improvements and long-term value.
Key takeaway: Focusing on first call resolution increases support agent efficiency by aligning their actions with their desire to help your customers. It also leads to healthier internal conversations that elevate the team’s productivity.
So, what’s a “good” FCR rate? Well, the answer could vary depending on your industry, business, and support model. Having said that, there are no first call resolution best practices that apply across the board.
According to research from MetricNet, a leading source of online benchmarking data, 74% is about average. That being said, MetricNet also noticed a wide variance in the data set. Some service desks scored in the low 40% range, while high performance teams scored up to 94%. The difference? The data shows that top support teams are highly skilled, well-trained, and possess the right tools to deal with almost any customer request.
Industry standards aside, experienced customer service leaders realize the importance of tracking FCR data for their specific companies and industries. Start by collecting reliable data from your support operations and compare it to industry-specific best practices. Let data guide your decision-making for improving FCR.
Speaking of improving FCR, here are a few approaches that have worked well for our clients:
Customers don’t have perfect knowledge of your products and services. As a result, they often use words that describe the pain that they’re experiencing instead of the underlying problem. Your agents need to know how to ask the right questions to get to the root cause of the issue. Doing so reduces the chance that a customer will call back in the future, thus improving FCR.
Sometimes, a customer engages in a repeat call because they simply forgot to ask a related question. That’s why it’s a good idea to send follow-up emails that contain helpful documentation. Many customers prefer a self-service support model, and online documentation aligns with that preference. Getting answers from a help site is much faster and more convenient for the customer—and eliminates unnecessary interactions with your support team.
To thrive, your support agents need more than a basic online ticket management system. Smart customer service leaders empower agents by implementing a variety of tools that elevate productivity, streamline learning management, and encourage customer self-help. For example, WP Engine recently integrated their online knowledge management solution using QA data from MaestroQA to close knowledge gaps and increase agent performance. An appeasement chart is another excellent tool that helps agents provide resolutions and prevent further escalations.
Now that we understand what FCR is and how we should improve it, we need the last piece in the puzzle—data.
Data helps answer these questions: What’s your next move? Should you scrap your current training program and start all over? (Answer: Not just yet!) Do you need a better knowledge management system? More workflows and better emails? Before you make any big changes, go back to your support data and check for (and eliminate) any experience blindspots.
Tracking FCR is a good idea, but it will not eliminate your experience blindspots. Here’s why:
If you’re like most support teams, you probably use CSAT and/or Net Promoter Score (NPS) to measure customer satisfaction. As we’ve already discussed, focusing too much on efficiency-metrics—like AHT—can actually detract from the customer experience. And, although FCR is arguably superior to AHT, at the end of the day it’s still an efficiency metric that can be manipulated. Not every ticket can be resolved on the first interaction. However, if agents are overly focused on first call resolution, they may take undesirable actions that artificially lower FCR at the expense of customer satisfaction. Keeping a customer on hold for 20 minutes to avoid a transfer defeats the purpose! ⏰
That’s where trustworthy QA data comes in handy:
Agent Adherence: QA serves as a check to ensure that your agents are following your FCR best practices. So, as you start to implement programs aimed at boosting your FCR rate, you can have confidence that agents aren’t gaming the system just to make their stats look good.
Maximizing FCR: QA data is key for surfacing new insights to further increase FCR. Check out how popular ridesharing service, Lyft, increased their FCR rates by using QA data to identify product and policy knowledge base enhancements.
360-Degree Insights: Last, but certainly not least, QA data enriches all of your other metrics and helps you get the full story behind agent performance. For example, QA data might surface new coaching opportunities for an agent with a high FCR rate but low CSAT score (read: the agent tends to rush through tickets without getting to the bottom of the problem)..
Looking for reliable QA insights to help your support team elevate the customer experience and boost your FCR rates?