How AI is Changing Customer Service

When you think of how artificial intelligence (AI) applies to customer service, you might remember the last time you called a company asking for help. You had to deal with a robotic voice asking you to say “one” or “two,” depending on who you wanted to speak to, and it probably wasn’t the smoothest experience. 

The days of unintuitive and frustrating call directories are becoming a thing of the past. The latest in customer service AI are called virtual agents, and they are far more advanced than the call directories we know. Their mission? To make your customer’s life easier. If a machine can interpret the intent behind their phone call, it can give them an answer faster and more efficiently than a human agent. This could prove to be a better experience for everyone: the customer can get basic answers right away without having to wait for a free agent, while your company can reserve live agents for more complicated customer support issues and can save money by being more efficient. 

Virtual support agents signal a change in customer experience. Gartner predicted that by the end of this year, customers would manage 85% of the relationship with an enterprise without interacting with humans. 

This transition is becoming a reality because of all of the progress in machine learning. Machine learning refers to AI systems’ ability to learn and improve from experience without being explicitly programmed. It does this by analyzing historical data captured during actual interactions.  

As the technology behind AI quickly improves, new opportunities for growth and revenue surface for businesses. 

Using AI for Customer Service

With all that said, the application of AI in customer service is one of the areas with the most potential. This is because factors like speed and accuracy have a big impact on customer satisfaction. AI systems have an advantage compared with humans in getting the right answers, faster. Not to forget the fact that AI systems are always open, and can spend as much time with a customer as they need to close an issue. Artificial intelligence helps businesses engage with more significant numbers of customers without sacrificing the quality of the interaction. 

The most important attributes of the customer experience are fast response times and consistency

For example, chatbots, like those on Facebook Messenger, enable businesses to promptly respond to customer messages and increase the number of customers they can communicate with at once. Customer service representatives of the future will adopt an “instructor” role to their virtual co-workers and potentially vice versa.

Businesses are using AI to offer customer support in other ways as well. Using natural language processing, companies can handle tickets using AI entirely to automate more complex tasks – think handling flight changes or cancellations. 

Using AI to Deliver Faster Responses and Save Human Agents Time

There’s a clear winner from using AI in customer support, and that’s customer satisfaction in the form of getting faster answers. Customers hate waiting because it’s frustrating. AI can handle commonly asked questions and provide answers to the customer directly or offer a link to the right article from the knowledge base. Besides giving faster answers, virtual agents are on call 24/7, so customers can get the answer they need at any time. 

AI is also saving time for human agents. For example, at the image editing company Pixelz, a chatbot qualifies leads, and connects potential customers with Pixelz’s (human) sales department — all through a simple bot on their website. Prequalified leads are 40% more likely to be willing to engage with salespeople, according to an article from [247].ai published by the MIT Sloan Management Review.

 Pixelz uses a chatbot to qualify leads according to the value they might bring to the company.

 Pixelz uses a chatbot to qualify leads according to the value they might bring to the company.

Suggesting Articles to Assist Agents

How much time are agents searching for information compared to actually helping customers? Probably too much time. A survey from Salesforce to 3,500 customer service professionals concluded that 64% of agents with AI chatbots are able to spend most of their time solving complex problems, versus 50% of agents without AI chatbots.

One of the ways AI is saving time in customer service is by automatically recommending helpful articles to assist agents and then presenting them with suitable recommendations to help customers. 

Say a customer calls your support team, asking about an issue with your software. Once the call is routed to the agent, what should that agent do? Based on data from previous similar interactions, the AI can suggest articles that have solved similar cases in the past. As the agent begins typing the information into the case, the AI will produce recommended articles. This is especially useful for recent hires. They often spend a lot of time searching for information until they have the experience to know which articles solve each specific problem. 

Atlassian is one of the companies using AI to suggest article recommendations based on keywords. The company’s Customer Support and Success division is home to some 450 staff who work with customers in the form of technical product support. Looking for ways to scale efficiently in the context of customer support, they used AI to reduce both internal and customer effort by surfacing the right information at the right time – in turn, unlocking team performance. 

Using Case Classification to Get a Ticket to the Right Agent

Say you receive an email from a client asking about a feature of your booking system for her restaurant. If this is an email, you probably don’t know too much about who the customer is. Until recently, companies had a team dedicated to manually reading these emails and routing them to the appropriate agents. That’s a lot of time that could be spent actually providing customer support. With case classification, the AI can read this email, find that it’s a simple product question, and then route it directly to the product support team. Now that ticket gets into the hands of the right person faster. 

Atlassian uses natural language processing to recognize what the customer is talking about and route the ticket to the appropriate agent.

Atlassian also benefits from using this technology with their support team. Whenever a new ticket comes in, an automatic classification occurs using natural language processing and machine learning. Through an integration with Jira Service Desk, the company saves significant time when triaging its queues. 

Using Chatbots to Handle More In-Depth Inquiries

Chatbots are already a common sight on many websites – it’s an easy way to respond to basic queries. However, there’s a lot of space for chatbots to get more sophisticated. 

Chatbots use AI to understand what people are saying and decide how to respond. And while that means it can quickly tell your customers when your store opens – it also means there might be instances where your business can benefit from automating complex processes. Especially if you’re looking to scale, delegating specific tasks to chatbots can save your business money. According to Chatbots Life, companies will save 2.5 billion customer service hours using chatbots by the end of 2023.

Dutch airline KLM, for example, uses AI to handle both repetitive questions and to answer complex queries. They offer support in five service channels, Facebook, Messenger, Twitter, WhatsApp and WeChat, and seven languages.

KLM’s chatbot offers support in five service channels, including Facebook Messenger.

Using natural language processing and unifying data from multiple sources, chatbots can rapidly resolve repetitive queries at scale, even tasks typically handled by humans, like flight changes or refunds. Automated resolutions solve customer’s challenges without friction, no matter if the query is coming through Facebook or WhatsApp – a chatbot can live wherever customers are in their journey. 

With chatbots, you can automate your tickets to solve the customer’s issue end-to-end, quickly and without ever involving an agent. 

AI in Customer Service – a Win-Win for the Future

Virtual service agents will keep on improving the customer experience. As all of the examples above demonstrate, the AI-driven evolution of customer support is not about replacing human agents — it’s about giving them the tools to work smarter. 

Human-machine cooperation is the future of customer service. Companies are designing entire customer journeys in which virtual agents and people work together. When machines handle repetitive, day-to-day tickets so agents can focus on more complicated issues, your team can give more valuable service and customers are more satisfied — and that’s the main goal of any customer support team. 

Want to read more on how you can implement practical AI solutions today? Check out our recent article on AI solutions for customer service. 

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