Customer service requires a balance between humans and machines.
Your support team is always ready to jump in and solve customer issues. On the other hand, you’ve got machines or tools that can deflect basic issues. How many issues you deflect and whether a high deflection rate is good depends on your goals.
If your goal is to push customers toward self-service support, then deflection rate is crucial. Companies like Facebook or WordPress make speaking with a live person nearly impossible. They rely heavily on their knowledge base to manage their customer service at scale. But that doesn’t always sit well with customers when they can’t find answers in their help centers.
A high deflection rate would be great if they could deflect issues with artificial intelligence (AI) through chat, email, or over the phone and keep their customers happy.
Some customers might always feel best when they pick up a phone and talk to a person who answers after one ring. But few businesses can afford that luxury. Monitoring deflection rate is about striking a balance between deflection and customer satisfaction.
What is a Deflection Rate?
Deflection rate is a customer experience (CX) metric that measures how many customer requests are solved through self-service tools, like a chatbot or knowledge base, without needing help from a live agent.
Say a customer comes to your website, decides they like your product, and heads to your pricing page. They have a question about a subscription plan. They open your chatbot and ask for help; a well-trained, highly conversational AI-powered chatbot provides an immediate answer.
That customer feels satisfied with the interaction and continues with their purchase without ever needing to speak to a person. That’s a deflected issue. Your deflection rate measures the percentage of deflected issues against the total number of issues you face.
Take Kickfin, a platform facilitating cashless tip-outs for restaurants, bars, and hotels. The company struggled to scale customer support as its client base grew in both volume and extended hours.
Their small support team needed a way to handle frequent, repetitive inquiries without overwhelming agents. And they needed to make late-night customers feel like they were dealing with a live person.
They implemented Forethought Solve and deflected over 2000+ tickets after implementation. They also achieved a 72% self-serve, which measures totally deflected issues, as well as those that start with a chatbot and end up with an agent.
This allowed Kickfin’s agents to shift focus to handling complex, high-priority issues, optimizing their workflow and keeping customers satisfied.
Why is Deflection Rate Important?
Measuring your deflection rate is important because it measures how well your self-service tools are doing (or not doing) the heavy lifting for your support team.
Let’s say you run a content platform. You’ve got two types of clients: transactional clients who buy articles as a package and retainer clients who require more hands-on attention. In this scenario, you want your in-house team to spend most, if not all, of their time on the second group. Deflection rate would be an important metric to measure so you could determine how well you’ve done that.
What Can You Do with Deflection Rate?
Your deflection rate can help you decide which self-service tools you need and how to improve them.
Say you manage customer service for a SaaS company that offers project management software. You notice a high volume of issues from customers asking, “How do I reset my password?” and “How do I export a report?” You know you’ve got knowledge base articles on those topics, which might indicate that your help center isn’t as effective as it should be. Or, if you don’t have them, you know you need them.
You’ll then be able to measure how many of those issues are deflected once improvements are made. This goes for improving your product, too. Maybe customers are reporting the same software bug or broken feature, which could indicate a product issue that needs immediate attention.
Forma, for example, is a benefits platform that spentding too much time on repetitive support requests foth companies and employees. They used Forethought Solve to significantly improve their deflection rate.
After implementation in January, over 13,800 people contacted their team, and 5,081 tickets were solved. Over time, Forma’s deflection rate steadily improved from 30% in October to 39% by March.
For Forma, deflecting these routine inquiries meant their team could provide better, more personalized service to the customers who needed it most, boosting both efficiency and customer satisfaction.
This is the power of a high deflection rate. When it grows, you don’t just reduce your team’s workload; you ensure your team is spending time where it counts.
How Does Deflection Rate Compare to Other CX Metrics?
Deflection rate is important, but depending on your goals, it should be considered alongside other key metrics like customer satisfaction score (CSAT), first response time (FRT), and others.
Sometimes, they’ll correlate. You may be able to increase CSAT with an automated agent that answers customers’ questions instantly. Who wants to wait in a queue for a live agent if they can easily get answers to questions like “What are your hours of operation?” from an automated agent?
We’ll walk through how deflection rate can influence other key metrics and vice versa.
Download our CX Metrics Guide for a deep dive into the 18 most important CX metrics.
Customer Satisfaction Score (CSAT)
CSAT measures customers’ happiness with an interaction or experience with your company, usually through a survey. After a customer service interaction, customers may receive an email asking them to rate their experience from 1 to 10. The percentage of customers who give a positive rating, usually 9 or 10, determines your CSAT score.
Faster responses increase CSAT. 90% of customers rate an “immediate” response as essential when they have a customer service question. Certain tools, like a chatbot, that deflect issues from your team solve simple issues on-demand without making customers wait for a live agent.
Say you work for a bank. Your team spends a lot of time answering repetitive questions like “What’s my account balance?” You start using automated agents to deflect issues. Instead of waiting in a long queue with bad music for a live agent, customers get instant answers to their questions and feel more satisfied. Increasing your deflection rate also increased CSAT in this scenario.
It’s worth noting that increasing the deflection rate could lower CSAT if your tools work poorly, so you should monitor this when implementing new solutions.
First Response Time (FRT)
FRT measures how quickly your team responds to a customer’s help request. If you’re using an automated agent, responses are instant. In that case, increasing your deflection rate directly correlates with decreasing FRT.
Your agents no longer need to rush to address every issue. They can focus on the most critical tickets, knowing the initial inquiries have already been handled.
This could work well in an e-commerce setting. You might use an automated agent to respond to routine inquiries about shipping, returns, or product availability, knowing that every ticket gets an instant reply. Those who need to talk to an agent will be routed accordingly.
Customer Retention and Churn Rates
Your customer support team plays a crucial role in keeping your customers happy and determining whether or not they decide to stay.
Customer retention rate is one way to measure impact, tracking the percentage of customers you keep over a given period. Churn rate is another, tracking the percentage of customers who leave during that same time. When churn is high, it’s often a sign that something is wrong—whether it’s dissatisfaction, unresolved issues, or frustration with the service.
While improving your deflection rate could increase churn. A chatbot that gives incorrect or poor answers could deter customers from staying loyal. When done right, deflection could positively impact retention and churn by providing quick resolutions to simple problems.
Say you work in tech and want to deflect repetitive questions like “How do I integrate this feature?” You don’t want to just deflect tickets; you want to deflect them and ensure customers are still satisfied. If you’re successful, you’ll retain customers. If you’re unsuccessful, they’ll likely churn.
Other Self-Service Metrics
The whole point of deflection is to let customers serve themselves and lighten the load on your team. But deflection is just one part of self-service. You’ll also want to measure other self-service metrics that work alongside deflection rate to make your team more efficient while keeping customers happy.
Self-Serve Rate (SSR)
SSR is similar to deflection rate. It measures the percentage of issues where customers use self-service tools like chatbots, FAQs, or a knowledge base. These issues may be passed along to a live agent. For example, a customer might start with an automated chatbot but eventually escalate to a live agent.
When measured together, Deflection rate and SSR show how well your self-service tools work. SSR tells a story about how often they’re being used, whereas deflection rate tells a story about how effective they are.
Completion Rate
Completion rate measures the percentage of customers who complete a task using self-service tools without abandoning it. A high deflection rate could correlate with a high completion rate.
But if your completion rate is low, it could mean that your customers are hitting roadblocks, so you deflect fewer issues. They might be starting a process but not finishing, which frustrates them.
Maybe a customer is trying to use your FAQ or chatbot to return a product but ends up abandoning the process and reaching out to your team anyway. You ultimately want them to be able to do so with self-service tools, which would reflect in both a high completion rate and deflection rate.
Self-Serve Error Rate
Self-serve error rate is the percentage of times customers encounter an error while using self-service tools. Whenever your chatbot provides the wrong answer or a customer comes across outdated information in your knowledge base, that’s an error. A high error rate can be a huge source of frustration for customers.
A high self-serve error rate could result in a low deflection rate. If customers frequently encounter incorrect information when troubleshooting an issue, they’ll leave unsatisfied and probably get routed to an agent. When self-service tools work reliably, customers are more likely to continue using them, keeping your deflection rate high.
Deflection Rate is an Important Metric for Companies Who Want to Prioritize Self-Service Support
There is no one-size-fits-all answer to whether deflection rate is the most important metric to measure. But if the goal is to grow self-service, deflection rate is one of several essential metrics to track as part of a larger strategy.
By improving deflection rate, companies can free up resources, allowing support teams to focus on complex issues and spend resources more efficiently.
This makes it vital for businesses aiming to maximize the effectiveness of their customer service teams through self-service solutions.
Want to improve efficiency and reduce the load on your support team? Optimizing your deflection rate with AI-powered solutions can help.
