Complete Guide to Knowledge Base Chatbot for Customer Support

Delivering a great customer experience isn’t just about responding to their support queries faster. It’s about providing them with accurate information that helps them find a solution to their concerns. This is where a well-structured knowledge base comes in alongside AI-powered chatbots. 

In this post, we’re going to share all about knowledge base chatbots and how to deploy them for your business. 

What is a knowledge-based chatbot? 

A knowledge base chatbot is an AI-powered virtual assistant for customer support agents. It uses a repository or knowledge base of articles, FAQs, guides, and other resources to address common customer issues through engaging conversations. 

But unlike traditional chatbots that rely on pre-defined rules or scripts, knowledge-based chatbots leverage natural language processing and machine learning to retrieve relevant information in real-time during a live interaction. This helps the business bridge the gap between customers and the knowledge base, creating a high-value conversation. 

What are the types of knowledge base chatbots? 

There are two primary types of knowledge-base chatbots: 

1. Rule-based FAQ chatbots 

These knowledge base chatbots rely on predefined rules to provide responses to customers. They typically rely on specific keywords or patterns provided as user input and are pretty straightforward to implement. 

The most common use case for rule-based FAQ chatbots includes addressing repetitive queries with limited variability. They are best suited for businesses with low maintenance needs and fewer customer query variations as they struggle to handle complex interactions. 

2. AI-based FAQ chatbots 

AI-based knowledge base chatbots leverage natural language processing and machine learning to interpret user input more accurately. They are able to read the context, semantics, and intent of queries to personalize responses to customers. 

These chatbots are easily scalable and can manage complex queries like multi-turn conversations, recommending solutions, or even upselling and cross-selling products based on user behavior. 

How do knowledge-based chatbots work? 

Knowledge base chatbots combine AI and a well-structured knowledge base to enable intelligent automation for customer support. This typically includes: 

• Natural language processing – The chatbot uses NLP to understand the intent and context of a query. It then identifies the relevant keywords, phrases, and the overall meaning of the question to find relevant information. 
• Query matching – Once the intent is identified, the chatbot automatically searches the knowledgebase for relevant articles, how-to guides, case studies, and other information. 
• Response generation – The chatbot then retrieves the best-matching content and formats to respond to the customer query. If the AI chatbots leverage GenAI, they are also capable of phrasing responses and step-by-step instructions for agents to use. 
• Continual learning – Knowledge-based chatbots analyze customer feedback, identify gaps in the knowledge base,e and adapt their responses to improve accuracy over time. 

What are the benefits of using a knowledge-based chatbot? 

Here are some of the benefits of integrating your knowledge base and chatbot solution: 

• Improve customer satisfaction – Knowledge base chatbots empower customers by creating an intuitive self-service tool. This reduces the number of touchpoints needed to resolve an issue, saving time and effort on both the business and customer’s parts. 
• Increase service efficiency – These chatbots can handle a significant volume of repetitive and common queries. This frees up human agent time to focus on complex queries and customer relationship management, bringing efficiency into the process. 
• Minimize response time – Since knowledge base chatbots are available 24/7, customers can get immediate responses to queries. This continuous availability helps build trust in the brand, improve conversion rate and reduce customer churn by addressing concerns before escalations. 
• Omnichannel consistency – With proper integrations, knowledge base chatbots can help offer a consistent user experience across channels. They can track and recall customer interactions to create a unified conversation, reducing the back and forth. 

What are the use cases of knowledge-based chatbots?  

Knowledge-based chatbots have a wide range of applications across industries. Some of them are: 

• 24/7 customer support – Provide instant responses to frequently asked questions and common queries like troubleshooting, return/ refund policies, etc, even outside business hours. 
• Onboarding and training – Knowledge-based chatbots can be used to onboard new employees and customers. This includes introducing them to your products, services, or internal processes by providing relevant instructional materials. 
• eCommerce assistance – These chatbots can answer product-related questions, helping customers make informed purchases. This can include queries about policies or even personalized product recommendations. 
• Healthcare – Knowledge base chatbots can be used to offer patients quick access to information about symptoms, treatments, medication guidelines and post-appointment assistance. 
• Financial services – The chatbots are capable of guiding customers through complex financial decisions about products, and answering queries around account management or loans. 
• Technical support – Knowledge-based chatbots can assist users with technical issues. They can provide the relevant step-by-step troubleshooting process from the knowledge base. 
• HR and internal assistance – These chatbots can act as virtual assistants for HR and employees, answering questions about leave policies, payrolls, and other internal policies. 

How to implement a knowledge-based chatbot?  

Deploying a knowledge-base chatbot with solutions like Auralis AI is easy. Here’s a quick step-by-step on the same: 

1. Define objectives – Start by identifying the goals or the objectives you’d like to address with the chatbot. This could include wanting to reduce the number of customer support queries, improving response times, increasing self-serve adoption and similar. 
2. Assess your knowledge base – Ensure that your knowledge base is up-to-date and well-organized. It should include all the assets that can potentially help address common queries in different formats – text, videos, step-by-step. 
3. Choose the right platform – Select an AI-powered solution for customer support that will integrate seamlessly with your existing knowledge base tools. It should also help you create custom workflows to automate and create unique customer experiences. 
4. Cross-collaboration – Train both human agents and your chatbot to collaborate. Set dos and don’ts, guidelines and real customer interactions to refine accuracy of co-pilots. 
5. Test and optimize – Ensure the chatbot is able to understand user queries and provide accurate responses. Deploy the chatbot category-wise, collect feedback, identify gaps and optimize performance. 
6. Leverage AI insights – Don’t just monitor customer support performance. Dig deeper into conversations to uncover customer insights and sentiments, identify gaps in resolution processes, and update the knowledge base. 

Conclusion 

Knowledge-based chatbots are just another step towards running well-integrated functions to deliver positive customer experiences. 

With the help of solutions like Auralis AI, businesses can leverage advanced and customized AI workflows for support teams. This includes setting up custom integrations with knowledge base solutions like Zendesk, Freshdesk, Gorgias, and many others. 

To know more about knowledge-based chatbots, book a demo.