11 Examples Of AI In Customer Service

By Ruth Favela

The world of customer service is changing and will only continue to do so. Customers expect more than ever before, and we know exactly what it’s like — we’re customers too.

We want answers as fast as possible with the most up-to-date information available, and if we can’t get it right when we want it then we’re going to be disappointed, and we’ll tell you.

Meeting customers’ demands has always seemed like the biggest undertaking, until now. Thanks to emerging technologies such as conversational AI powered by machine learning and natural language processing, customer service has transformed for the better and we’re just getting started.

To give you more insight into the power AI has for customer service, here are 11 examples of how AI is changing and making an impact on customer service.

Conversational AI

Artificial intelligence makes conversational artificial intelligence possible. AI is the automated part of a support process while conversational AI is the “conversation” part of the interaction.

Conversational AI is something we’re all hearing about these days, and for good reason — it’s a term used to describe chatbot interactions that are powered by more than decision trees and if/then statements set up by a helpdesk admin. Conversational AI for customer support is designed to interact with your customers in a much better and more accurate manner. 

A lot has been possible through conversational AI, with increases in self-service and the ability to offer 24/7 support. Customer support has become more sophisticated and easier to conduct on both the customer and support agent sides. 

Chatbots

One of the most common uses of AI in customer service is customer service chatbots. Businesses use chatbots for a variety of reasons with automating customer support interactions being number one. Support teams use chatbots to automate the most repetitive and redundant customer support inquiries.tThis includes information for routine questions about personal accounts, order status, and product or service usage, plus much more depending on a business’s industry. 

When support teams implement AI into their customer support journey, they not only improve the customer experience, they also improve the agent experience. When you remove redundant and repetitive work, you free up agent time for them to focus on more complex tasks or escalated tickets. AI helps support teams save time and costs.  

Assist Agents

In today’s customer support world, AI can be used on both the customer-facing side and the agent-facing side. AI can help automate repetitive customer inquiries that send customers canned responses containing the information they seek. When a support query and question can’t be automated those tickets then get sent to agents who get hard at work sifting through mountains of past ticket history and their internal company wiki to find the correct information for that question, which often takes time.

This knowledge search can be automated for agents. With AI, agents can get assistance surfacing the knowledge they need to answer tickets and resolve them much faster. With the right AI tool integrated into a support agent’s helpdesk reps can have an AI assistant at the ready all day long.  By providing an agent assist tool, support agents can reduce Time to Resolution, Average Handle Time, CSAT, and more.  

24/7 Self Service

AI can help improve self-service rates; customer self-service rate refers to the rate that customers are able to identify and find the support they need without relying on a customer service agent. With the help of AI customers can consult chatbots that automatically produce the information they are seeking. The right AI tool for customer support embeds into a support agents helpdesk and learns from a company’s historical data including past tickets, internal company wikis, external-facing knowledge bases, agents notes, and more. This information helps customers self-serve and get the information they need without agent interference. 

Sentiment Analysis

With the rise of technology being used more and more within customer support, the tech being used is becoming smarter. These days we can use AI to help with sentiment analysis to identify how a customer feels within their customer support ticket request. The right AI tool can recognize when a customer is upset, angry, happy, or neutral, allowing for the proper agents to resolve those queries. The right customer support AI tools are powered by machine learning and natural language processing that work together to analyze data and produce information accurately to customers. 

Natural Language Processing

As mentioned, artificial intelligence works in conjunction with other technologies to make chatbots and automated customer interactions possible. One of these technologies that goes hand-in-hand with AI is Natural Language Processing (NLP). Natural language processing is a branch of artificial intelligence that uses machine learning algorithms to help computers understand natural human language.

NLP is an umbrella term that encompasses any and everything related to making machines able to process natural language, whether it’s receiving the input, understanding the input, or generating a response. This means that most support interactions require NLP to process information and respond accordingly. 

Machine Learning

Just as important as NLP is Machine Learning (ML). Machine learning makes it possible for an AI application to learn and improve from experience without explicit programming. Machine learning is what allows for continued improvement, which is highly important in customer support. 

With this technology, AI helps chatbots become better. As the AI learns, responses for customer needs improve and the automated responses become even more consistent and concise. 

Automate Ticket Creation

Sending in customer support tickets can be overwhelming and sometimes confusing to customers. Customers who are seeking support are often looking for a chat widget, a “Contact Us” form, or a company email they can reach out to with their questions and concerns. 

AI can help automate ticket creation by allowing customers to submit questions via a chatbot widget that is designed to deflect repetitive customer support tickets and create tickets for those that can’t be automatically answered. AI can help streamline this process and helps both agents and customers. 

Automate Ticket Routing

One of the most mundane and redundant tasks within customer support is ticket routing, which can be automated with the help of AI. Many support teams still have manual ticket routing in place meaning that an agent, or two or three, is manually labeling incoming support tickets with labels regarding the individual need. 

Sometimes tickets are routed via tiers, urgency, product, or team priority and without AI this is all done repeatedly, over and over again, all day long. AI can automate ticket routing based on how tickets have been previously routed and remove one of the biggest bottlenecks in customer support. 

Automating Email Responses

If AI can automate individual chatbot inquiries, then it can automate your email responses too! With the help of NLP and ML, AI tools can help agents automate email responses by assisting them with surfacing the correct information when resolving customer support tickets via email. With AI, agents can have access to a widget that sits on top of their helpdesk and will surface the correct information for customer questions they’re responding to based on previously answered tickets and company data. 

Leveraging Data For Customer Service Improvements

The best thing that AI allows support organizations and their businesses to do is to leverage their knowledge and data for customer service improvements. AI works best when it can ingest all data possible, whether it’s data in the form of past customer tickets, internal knowledge found in agent notes, Google Docs, Jira, or Confluence, or data collected in past customer success reports. It all helps AI work more effectively.

AI can help pool all company knowledge together so that support teams have one single source of knowledge to pull information from. By leveraging data for customer service improvements, support teams can have the most accurate and up-to-date information to answer support tickets, which can help improve resolution times and customer satisfaction. 

What Are Some Examples of AI that Businesses Can Use Now? 

There are many examples of AI that businesses can get started with now. Support teams can use AI to automate ticket tagging, automate ticket creation, improve self-service, use Machine Learning and Natural Language Processing, automate email replies, and leverage all company knowledge and data. When support teams implement the right AI platform solution they can improve both the customer experience and the agent experience at the same time. 

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