How AI Transforms Customer Self-Service: Unraveling the Power of Intelligent Knowledge Bases

By Machielle Thomas

One of the key ways businesses can improve and maintain their relationship with customers is by having an efficient, robust customer support system. Artificial intelligence (AI) has revolutionized what customer support can be and do for customers in need of information and help. Customer service AI provides customers an avenue to conduct their own self-service with ease and resolution.

According to the Harvard Business Review, a whopping 81% of customers actually prefer self-service methods to resolve their queries over talking to a customer representative. 

How, then, are customers able to rely on self-service customer support to help solve their problems? This is where the power of intelligent knowledge bases comes into play. 

Ahead, we’ll unpack how customer service AI impacts support, what exactly AI-powered intelligent knowledge bases are and their benefits, and what to consider before implementation. 

What is customer service AI support? 

Customer service AI allows customers to find answers for their issues or queries without the need of speaking to a live agent. With the power of AI, customer service becomes more customer self-service. Customer service AI can show up for customers in a number of different ways but a primary path is through virtual assistants, or chatbots. 

Chatbots greet customers, ask them a series of questions, or find information based on the questions typed into the chat window. Virtual assistants like these can also escalate queries and complex issues to a live agent if need be, and send out technicians or set-up appointments with in-person service agents.

Much of these capabilities are helped with AI-powered intelligent knowledge bases particular to that product, service, or business that can help serve up the right information to customers.

Next, let’s dig into what that is and how it helps customer support AI. 

What are AI-powered intelligent knowledge bases?

An intelligent knowledge base in AI essentially captures all the relevant human expert knowledge in an effort to support problem-solving, decision-making, and facilitate options for customers. AI powers the mechanisms in machines to have or gain knowledge. Knowledge bases are one part here, with intelligence being the second that applies whatever that knowledge is.

AI-knowledge bases include: 

  • A consistent voice for customers because all of the virtual agents are using the same data sets to extract information
  • The relevant content customers need to help make decisions and solve problems
  • Collaborative effort to improve service and keep serving up and processing pertinent, relevant information to customers based on feedback loops and user
  • Information is siloed into centralized repositories for customer service AI agents to retrieve what they need to help support customers. 

For example, an ecommerce software-as-a-service (SaaS) may offer a chatbot virtual agent to help customers with queries about the product they’re using. The knowledge base offered here is all of the data and information about and from the company, while the intelligence aspect processes it for the customer. 

5 key benefits of intelligent knowledge bases in customer self-service

A knowledge base in customer service AI helps businesses provide better information and service, while eliminating any friction for customer self-service with AI tools.

Below are the 5 key benefits of using intelligent knowledge bases in customer self-service. 

Improved response time 

It’s no secret that customers want speed when it comes to answering their queries. With the modern digital world running at a fast pace, customer service AI needs to do so, too. Knowledge bases provide AI with information pulled from an enormous data set that helps customers get the answers they need and fast. 

Less wait times for answers to questions—or escalations to live, ready agents for more complex problems—are incredibly valuable for businesses. Not only are more queries answered in a shorter amount of time, customers appreciate that their time is a consideration.

Personalization and tailored solutions 

Sometimes customers use AI-powered customer service technologies to gain more insights into a product or service. Knowledge bases have the capability to serve up articles or product recommendations and give it to a customer. By personalizing the experience with such insights, this feature of AI-powered knowledge bases can not only increase product awareness and adoption, but provide the customer with something they hadn’t even considered yet. 

Streamlined operations and workflows

There are a number of processes that can be automated. Eliminate manual or laborious workflows and tasks with AI. Tag articles, product information with AI, or link content and product and service information together so that they can be served up to customers based on keywords used.  

Data-powered service experience

Knowledge bases work off of the information that’s accessible from a company. That can be anything from information about product and services, to billing information, to how to buy or return a product. Data is going to be the most important part of this customer service AI piece. By pulling from large data sets, the AI will be able to process and serve up the most relevant information that the customer needs to get to a resolution. 

Relevant, current content

Generative AI often works by making predictions from large data sets, and using intelligent knowledge bases in customer service AI tools means to serve up the most timely and relevant content a customer may need. It’s important to keep content up-to-date and have similar topics linked to keep a consistent experience.

What to consider when using knowledge bases in customer support organizations

Now that you know what knowledge bases in AI are and where they benefit both customers and customer service teams, there are a few considerations to know before implementing this technology. 

  1. Track performance. 

Your AI’s efficacy is important to measure and track. For instance, say customers are dropping off from the chatbot at a specific point before the query can be solved. Tracking and measuring this will help teams understand what they need to keep customers happy, and use the AI assistant through to the end.

  1. Keep content updated and create a lot of it. 

Your AI is only as good as the information you feed it. You cannot rely on the technologies alone to get you there. Do regular maintenance checks on your most used articles or pieces of content and information to ensure they are as up-to-date as possible.

In addition to that, and this is especially helpful through tracking, notice where there are gaps in information that can be solved by the creation of net new content. This information will help you understand what new pieces of information need to be made that can help customers get to a resolution faster and with clarity.

  1. Always ask for feedback. 

Customer feedback is the gift that keeps on giving. Rely on what your customers tell you about the experience to improve any parts of the customer service AI journey from content to speed to workflows and processes. 

Dive in.

Interested in generative AI for customer support? Check out this guide to learn about the 3 key pillars you need to get started.

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