So you just bit the bullet and ordered a new leather couch online, after spending weeks dreaming about how you’ll outfit your mid-century modern living room.
Then the day arrives: But post-unboxing, reality sets in and it’s nothing like the photos. The leather’s already stained and ripped—it looks like a group of feral cats must have laid claim to the couch before it made it to your door.
Obviously, this is not acceptable. But the real question is, what is worse: Taking in a couch that already looks threadbare, or trying to deal with the company’s return process to get a replacement?
A lot of consumers would probably say they’d rather hold on to the falsely-advertised couch than bother to deal with a return. That’s because they don’t trust the customer support process and would rather eat their losses now than waste extra time on a process that still may not deliver results.
Building a strong customer experience is crucial for winning brands—Microsoft’s global customer experience survey found that 94 percent of respondents said that customer service was “very” or “somewhat” important in their choice of loyalty to a brand.
But many businesses have lost the plot when it comes to customer support, and they’re paying the price. In this article, we’ll take a look at what customers hate about customer support—and how brands can use artificial intelligence and machine learning to improve the customer experience from start to finish.
Problem: No opportunity for customers to help themselves through self-service
Today’s consumers want to answer their own questions. They don’t want to wait 15 minutes to get on the phone with a customer support agent who may not even have the solution to their problem—they want easy access to a knowledge base to resolve issues independently in real-time. In the Microsoft survey, respondents overwhelmingly expected access to self-service customer support, with a full 92 percent of respondents aged 18 to 34 expecting self-service options.
Solution: Build an easy-to-use self-service support option to understand what customer queries arise most frequently and guide customers in the right direction.
The solution should use natural language processing to understand the customer’s true intent to find the right information in your knowledge base. Rather than having to wait to chat with a customer support agent, the customer should be able to express their issues in everyday language to find the precise answer to their common question.
Problem: The customer support agent doesn’t have contextual knowledge.
There’s nothing worse than getting passed around to three or four different agents and having to repeat your issue from scratch each time, but that’s unfortunately common in today’s customer experience. The Microsoft survey found that customer support agents had access to the history of previous customer issues less than half the time, even though 76% of customers expect agents to have access to the history of their customer journey.
Solution: Route customers to the right team based on the situation.
If the customer doesn’t have a simple problem that can be resolved through self-service, she needs to talk to a human agent—but it’s important that you provide her with the right customer support agent who will be able to easily resolve her problem. By using self-service as the first point of interaction, you can instantly gain better context around the customer support request and route it to the most appropriate team. That means your customer should be able to resolve her problem within one customer support interaction, instead of getting shuffled around from one customer support agent to another.
Problem: Customers have to wait before talking to a customer support agent.
If a customer needs to contact customer support, they don’t want to wait 24 hours or more for an email response. They’d like to use chat or phone support to resolve their issues in real-time. But agents are often so backed up that supposedly real-time channels like chat and phone force customers to spend time waiting on hold to engage with customer service teams, and they don’t always have a lot of patience. Two-thirds of respondents in a study said that they wouldn’t wait any longer than two minutes on hold for phone support, and 13 percent of respondents said that no amount of wait time was acceptable.
Solution: Decrease your customer support ticket volume
When your customers are experiencing long hold times, it can be expensive to add additional agents to handle additional support requests. Instead of hiring more agents, you can reduce support ticket volume by using AI technology to assess your customer needs and streamline your customer service interactions. Those customers with simple requests can often solve their own problems via self-service, freeing up your agents to focus on the customers with more complex problems that require a human touch. Simply adding a self-service layer to your customer service process is likely to reduce call and chat support hold time significantly: After implementing Solvvy, the meditation app Calm was able to generate a 50% self-service rate, which cut response time in half for the customers who contacted support to talk to a human agent.
When it comes to customer satisfaction, it still helps to provide access to a human touch. That’s why so many brands get it wrong by going all-in on AI technology like chatbots, which make it next to impossible to talk to a human agent when you have a difficult question that can’t be answered by artificial intelligence. Instead, look at building a process with multiple touchpoints in the customer journey: Customers can start with self-service to answer simple questions, but if they can’t find an answer easily, they can instantly connect with a customer support agent over chat or voice support. Because they’re able to provide context upfront, the request will be routed to the correct team, and the customer won’t be sent down one of those endlessly frustrating rabbit holes of repeating her story to multiple agents and continually getting passed along to someone else. Used wisely, artificial intelligence can become an organic part of the customer service process—it’s there to facilitate and streamline customer interactions, and to make it faster and easier for customers to connect with the right support agents when they need extra help. With the right tools, you can turn the customer support experience from something to dread into something delightful for your customers.