First Contact Resolution - is it the right metric?
2 Aug 2024
6 min read
Is First Contact Resolution the best way to judge AI in customer service?
Is First Contact Resolution the best way to judge AI in customer satisfaction?
When ranking the metrics of success in customer service, first contact resolution (FCR) rate comes near the top of most lists. Getting a high FCR score in a call center means that you are preventing one of the most frustrating events for both customer and agent: repeat tickets.
Repeat tickets can effectively kill good customer service. Having customers come back time and again means that the number of tickets goes up, meaning more work for your customer service team. Customers who contact you again are rarely more happy than the last time they spoke to you, so you can start to erode a good reputation.
So when it comes to using AI and automation to enhance your customer service, a natural expectation is that it will improve your First Contact Resolution rate. This is not always the case though, but even if it doesn’t, it doesn’t mean that AI is bad. Let us explain.
What is First Contact Resolution?
Quite simply, first call resolution rate is the proportion of your tickets that are solved the first time a customer contacts you. It’s also known as first call resolution, or first touch resolution. This means that the customer has not had to contact you again, nor have your agents had to investigate and follow up.
Difference between Call Resolution and FCR
Call resolution and First Call Resolution (FCR) are two related but distinct metrics used to measure the effectiveness of a contact center. Call resolution refers to the percentage of customer inquiries or issues that are resolved, regardless of the number of calls or interactions required to resolve them. On the other hand, FCR specifically measures the percentage of customer inquiries or issues that are resolved on the first call or interaction.
While call resolution provides a broader view of a contact center’s ability to resolve customer issues, FCR focuses on the efficiency and effectiveness of resolving issues on the first call. A high FCR rate indicates that a contact center is able to resolve customer issues quickly and efficiently, reducing the need for repeat calls and improving customer satisfaction.
How can you improve First Contact Resolution generally?
Leaving AI to one side for a moment, the general way that you can improve first contact resolution is by ensuring that your agents have all the tools at their disposal to be able to solve the majority of cases in one customer call.
For instance, if a customer wants to change an order that has not been shipped, then your agents need to be able to edit the order while on the phone with the customer. Or, if a customer wishes to return an item, the agent should be able to access a returns portal or platform and issue the customer with a new return label and clear instructions on next steps.
In other cases, it could mean ensuring that the agent has clarity on what the processes and policies are for most common circumstances so that they don’t have to check with a supervisor, or go away and investigate.
Effective customer relationship management practices enable agents to resolve customer inquiries efficiently on the first interaction, thereby contributing to customer satisfaction and loyalty.
Another key factor is that any action the agent takes actually happens. So if an order is amended by the agent, it needs to be picked up by the warehouse team and the change effected. Otherwise the wrong order gets shipped and the customer has to contact them again.
So, ensuring access to systems, clear policies, and making sure that your tech is integrated effectively are all ways you can start to improve FCR for your customer service team members.
Challenges in Achieving High FCR Rates
Achieving high FCR rates can be challenging for contact centers, especially those with complex products or services. Some common challenges include:
Lack of training and support for customer service representatives: Without proper training, agents may struggle to resolve issues on the initial call.
Insufficient resources and technology: Outdated systems can hinder an agent’s ability to provide quick and accurate solutions.
High volume of calls and inquiries: Overwhelmed agents may not have the time to thoroughly address each issue, leading to repeat calls.
Complexity of customer issues: Some problems require multiple interactions to resolve, which can lower FCR rates.
Limited visibility into customer interactions: Without a clear view of past interactions, agents may miss critical information needed to resolve issues promptly.
To overcome these challenges, contact centers can invest in training and development programs for their customer service representatives, implement advanced technology and tools to streamline issue resolution, and focus on providing a positive customer experience.
Is a high FCR ever a bad thing?
It can be. Let us explain.
Imagine that your team gets 100 tickets a day. Some of those tickets are customers asking very simple questions that your team can answer without thinking or checking, understanding why the customer called in the first place. The sort of questions you get asked every day, like “What waist size are the medium trousers?” or “Do you do Next Day shipping?” and so on.
Most of those questions can be answered first time, thus you get a higher FCR score.
But, a lot of those questions could be answered by having that information clearly displayed on a PDP (Product Detail Page) or a FAQ or shipping page.
If you implement changes that allow customers to find the answers themselves then you might cut the number of tickets you get to 80 a day, but they will be more complex. That means your FCR goes down, but your team has less work, so on balance things are in a better place.
So why might FCR not be a good measure of AI's effectiveness in a contact center?
It depends if you measure FCR when a customer reaches a customer service agent, or when a customer chooses to interact with any self-service or AI solution.
If you choose to measure it only when a customer service agent gets involved, then the AI will reduce your call center's FCR by solving the simpler, slam dunk type questions.
If you choose to include any occasion when a customer asks a question, then you may not move the dial at all.
That’s because when deploying a sophisticated AI agent, such as DigitalGenius, you’re looking to replicate what your agents are doing. If you do this successfully, then the AI is just doing what the agent was doing anyway.
The only way you increase FCR is if the AI makes fewer mistakes, or if it can do things that the agent is unable to do.
We believe that an AI should make fewer mistakes than a human. And our solution can do things which agents are unable to such as provide up to date estimates on delivery timelines. However, these may not move the needle that much when it comes to FCR.
Agent Training for Effective FCR
Agent training is critical to achieving high FCR rates. Customer service representatives need to have the skills and knowledge to resolve customer issues efficiently and effectively. Some key areas of training include:
Product and service knowledge: Agents must understand the products and services they support to provide accurate information.
Communication and interpersonal skills: Effective communication can help resolve issues more quickly and build rapport with customers.
Issue resolution and problem-solving skills: Agents should be adept at identifying solutions and resolving issues on the first call.
Time management and prioritization skills: Efficiently managing time ensures that agents can handle more calls without compromising quality.
Technology and software skills: Familiarity with contact center software and tools is essential for quick and accurate issue resolution.
Contact centers can provide ongoing training and development programs to help customer service representatives improve their skills and knowledge, leading to higher FCR rates and improved customer satisfaction.
Measuring an AI's FCR rate
Where first call resolution rates are helpful in considering AI is when you assess the ability of the AI to resolve issues on the first contact.
To do that, you’ll need to be sure that you know when a customer interacts with your AI and then goes on to speak to an agent. If you are unable to track the whole journey, then you can ascertain how effective the AI is by asking customers if they were able to solve their issue using your AI customer service solution.
On the other hand, if you use an AI agent as a first port of call, but allow customers to move seamlessly to a customer service agent, then you can measure how often the agent has to step in.
Impact of FCR on Customer Journey
FCR has a significant impact on the customer journey. When customers are able to resolve their issues on the first call, they are more likely to be satisfied with their experience and loyal to the brand. On the other hand, when customers experience repeat calls and unresolved issues, they are more likely to become frustrated and disloyal.
By focusing on FCR, contact centers can improve the customer journey by:
Reducing wait times and resolving issues quickly: Enhancing the overall customer experience.
Providing a positive and efficient customer experience: Leading to higher customer satisfaction.
Building trust and loyalty with customers: Satisfied customers are more likely to return and recommend the brand.
Improving customer satisfaction and retention: Happy customers are less likely to switch to competitors.
Reducing the cost of acquiring new customers and improving revenue growth: Loyal customers contribute to long-term business success.
By prioritizing FCR, contact centers can create a more positive customer journey, ultimately leading to increased customer satisfaction and business growth.
So is FCR a good metric when thinking about AI?
The bottom line is that adding an AI is almost certainly not going to improve your First Contact Resolution rate in call centers. If you measure FCR only from when the customer speaks to a human agent, then adding AI agents will mean that many of the simpler queries are taken away from agents, meaning they have a higher complexity and therefore a higher likelihood of needing to be solved in two or more contacts.
Effective handling of customer calls can significantly impact overall customer satisfaction and operational efficiency.
You could consider it a single contact, if and when a customer is handed over seamlessly from an AI agent to a human agent, contributing to overall customer service success. In this case, your FCR is likely to remain flat.
There are some ways AI can improve things, by making fewer mistakes, by being able to connect the dots between what customers are asking and what data you have, or by doing things agents cannot do, leading to more first call resolutions.
One thing is certain though. Adding a sophisticated AI Concierge like DigitalGenius will have many other benefits:
Reduced First Response Time
Reduced Average Handle Time
Fewer Tickets Handled by Agents
Round the Clock Ticket Resolutions
Smaller Backlogs, and Reduced Repeat Phone Calls
Improving customer interactions is crucial to minimize poor customer service and enhance overall customer satisfaction.
And of course you can use FCR as a measure of how successful the AI agent is. Two different AI solutions could have a very different FCR depending on the approach, so it is still a decent metric to compare different solutions.
If you want to improve your customer service using AI, speak to our support team today.
