Leveraging Artificial Intelligence for Customer Service—Without Losing the Human Touch

Customers have high expectations for brands—and that includes customer service. According to Forrester Research, 67% of adults feel that the most important thing a company can do to provide good customer service is value their time. And when it comes to making a purchase, Gartner found that 64% think customer service is actually more important than price. Furthermore, the number one reason a customer switches products or services is because they feel unappreciated by the brand.

But the cost of human support is high—according to Forrester Research, it can cost a company as much as $12 per contact depending on the channel. So how do companies meet high customer expectations while still making them feel valued? Introducing Artificial Intelligence (AI) into its operations is one way companies can control costs while upping their customer service game, without losing the human touch that makes customers feel appreciated.

Relegate the mundane

Everyone has had the experience of needing a simple question answered by a brand, only to dread having to jump through customer service hoops just to get someone on the phone who may or may not have the answer. Conversational chatbots can make these conversations more seamless. Not only do conversational platforms help cut costs by 30%, they also can help your customer service scale and your agents have more meaningful and productive conversations with your customers when it matters the most.

Amazon, for instance, uses chatbots to leverage the data the company collects on all of its customers about their past orders. By programming chatbots with information about the customer’s past preferences, you can have conversational platforms interact with customers up to the point where an agent is needed. Then, once the conversation is transferred to an agent, the agent can pick up where the chatbot left off. This way, when it comes time for human interaction, the customer and the agent can have a more productive conversation without the customer having to repeat the information they provided to the chatbot.

Eventually you can program your chatbot to not only acquire customer information, but also recommend the actions customers and agents should take next. If a customer simply needs a common question answered about a product they already purchased, the chatbot can direct them to a FAQ without an agent getting involved. All of these interactions can be automatically tagged in the system, so they’re easy to track and reference, while also improving future recommendations. Besides streamlining processes, think of how much happier you’ll make your customer service agents—and happy customer service agents means happier customers.

Automate business processes

Consider this: Every minute you add back to an agent’s day by eliminating tedious tasks translates into more conversations per existing agent, while also giving them the time they need to handle high-value customers or go deeper on complex questions without feeling rushed. So how do you find more minutes in the day? Robotic process automation (RPA) can be used to handle the necessary, but routine tasks that keep support agents from interacting with customers in meaningful ways. RPA can track user actions within an application to complete a task and then perform the task, working across multiple digital systems. It can range from automatically replying to emails to routing conversations.

A global insurance provider has deployed RPA for a wide-variety of purposes from streamlining policy renewals to speeding customer claims. In one instance, RPA is taking information from customer communications with the company and matching it with the appropriate claims forms. Taking a process that once took 4 minutes down to 42 seconds. KPMG estimates that companies using RPA to automate business processes can reduce costs by up to 75%.

Turn agents into specialists

According to IBM, 80% of tier 1 support inquiries can be handled by a chatbot and elevated to a human agent if necessary. In the past, automated phone systems performed data dips, moving customers through a phone tree (“press 1 for a current reservation”) without handing the agent any information that the phone system captured. AI eliminates this unnecessary process. If a customer is calling about a product that’s discontinued, for example, there might not be a need for a human agent to talk to the customer only to relay that same information.

By using AI to capture information about the customers, and then passing customers and the information collected to agents only when absolutely necessary, agents can have more meaningful conversations and become more knowledgeable about the areas of the business that matters. If a customer still wants to talk to a human even after discovering their product is discontinued, the agent can immediately begin the conversation by offering recommendations for other products the customer may like. AI doesn’t eliminate the need for humans (as many people incorrectly assume when they hear talk of using AI in customer service). Instead it augments the human team and allows them to be better at their jobs.

Better management, better business

Gone are the days of randomly auditing customer service calls. By using AI to monitor your support operations, you can predict when conversations will start to go south allowing managers to intercede accordingly. AI can also help monitor which responses result in reopened tickets. If response A, for instance, tends to resolve inquiries quickly, but response B results in the ticket repeatedly being opened, the system can recommend you eliminate response B in order to set your agents up for success. Managers and executives can use the data generated by AI to oversee customer service operations in both clearer and more efficient ways—and this is a win for everyone.

Integrating AI into your customer service isn’t about replacing humans. Rather, it is about arming your customer service agents with the information they need to have more meaningful conversations with your customers, and using data to personalize your customers’ experience with your brand. Build an incremental strategy to roll out AI in your organization and use analytics to leverage the data collected. By using AI to build a more complete view of a customer’s relationship with the brand, companies can meet the high customer expectations for exemplary customer service and come across as anything but artificial.

Ready to learn how Kustomer can help you drive personalized, efficient, and effortless customer service? Discover AI trends in this customer service webinar.


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