Content Map
What is a Knowledge Base Chatbot?
Benefits of Knowledge Base Chatbot
Knowledge Base AI Chatbot Use Cases
How to Build a Knowledge Base Chatbot
Limitation of AI Knowledge Base Chatbot
The emergence of conversational AI has paved the way for the chatbot market to grow significantly, with an expected compound annual growth rate of 23.3%, as reported by Grandview Research. Driven by the urge to dominate the market with faster assistance services, various businesses have used AI chatbots as cost-effective and optimized solutions.
However, insightful AI-driven decisions depend on quality and accurate data, contributing to the widespread use of a structured knowledge base. Integrating AI and knowledge bases allows for reliable and instant answers to customers, effortlessly guiding them to the company’s products and services.
The article will explain how AI chatbots and knowledge bases can work together to streamline customer services and business operations. Moreover, businesses can comprehend the process of building an AI knowledge-based chatbot and the potential limits that affect performance.
A chatbot is an AI-driven computer program that generates human-like conversations through text or voice-based interfaces using natural language processing (NLP). The input-output model allows users to communicate with digital devices and search for relevant answers to their queries.
Meanwhile, a knowledge base provides self-service support to help customers and employees find needed information. As an online library, it grants users access to large amounts of data on products, services, and company procedures, mitigating the requirements of human agents. Examples of AI knowledge base software include Notion, Zendesk, Zoho Desk, and Guru.
Combining these two solutions results in an AI knowledge-based chatbot that can analyze and interpret user queries based on available content about the companies’ resources. This chatbot type guarantees natural-sounding responses with high accuracy and relevance. Also, when the knowledge base data is insufficient to resolve a query, the system can pass the issue to a human agent for expert assistance.
Depending on the businesses’ needs and the complexity of the content source, there are five types of knowledge-based chatbots: FAQs, Decision Tree, Generative AI, Hybrid, and Contextual.
A knowledge-based chatbot benefits businesses by optimizing the service experience for administrators, agents, and customers. Here are a few key benefits of implementing an AI chatbot connected to the available knowledge base:
When you already have traditional knowledge bases, such as FAQs, articles, or documents, you can use an AI-powered knowledge base chatbot in real-world applications within minutes. Indeed, integrating a chatbot with your knowledge base requires minimal effort—just a few clicks—using a suitable Generative AI provider.
The available data stored in the knowledge base can guide the chatbot in delivering accurate and relevant answers to user queries via email and messaging. Simultaneously, the machine learning algorithm can humanize generated information to make it more comprehensive and user-friendly. However, the chatbot still needs continuous NLP training and knowledge base updates to address more complex questions.
If businesses lack a knowledge base, they can use Generative AI to generate help center articles based on simple prompts. By inputting a few key points, artificial intelligence can automatically generate detailed and informative articles for the AI chatbot to access.
An AI knowledge base chatbot offers 24/7 support for customers and allows users to access information instantly across multiple time zones. As pre-trained on billions of fundamental user interactions, the chatbot can identify underlying intent and provide contextually relevant responses tailored to the brand’s tone of voice.
AI chatbots can support multilingual answers regardless of whether they are connected to a monolingual base. Moreover, by identifying data-driven insights into customer behavior, businesses can address customers’ most impactful issues and develop a conversation flow to assist them efficiently. For example, accessing data gathered in order management and e-commerce tools will help businesses comprehend customer context to provide personalized customer support.
The capability of enhancing users’ experience via multilingual and around-the-clock support can reduce response time, increase efficiency, and boost customer satisfaction. In fact, AI-powered knowledge-base chatbots can save users more time and effort by allowing them to access the company’s information with fewer touchpoints. They can also concurrently follow up where they left off regardless of the platform for ongoing support.
Chatbot technology enhances customer support’s efficiency while preventing human agents from manually responding to a large volume of users’ queries. The Customer Experience Trends Report 2024 proved the ongoing trends in applying chatbot solutions, with 44% of agents reporting using AI bots to accelerate their work.
According to Stanford University and MIT researchers, the widespread use of AI chatbots results in an average 14% increase in employee productivity. Indeed, the business’s internal team can automate most repetitive queries with a knowledge base regardless of less technical expertise, accelerating the working process and enhancing customer satisfaction.
Besides improving performance, AI chatbots also create new job positions, such as chatbot developers, analytics, data collection, chatbot strategists, and conversation designers.
AI knowledge base chatbots can assist customers and internal staff effortlessly accessing the company’s documents. Additionally, various industries, such as healthcare, education, and e-commerce, have leveraged these tools to provide customers with relevant items and information.
The following sections will highlight how businesses can integrate AI powered knowledge bases into the operation system.
Knowledge base chatbots can help employees update the latest company policies and clarify their considerations in minutes. Specifically, chatbot tools enhance employee support with these practices:
In real-world examples, our Neurond Assistant supports employees with relevant answers to their questions related to People & Culture and IT support. By clarifying their considerations about company policies, regulations, compensation, benefits, and technical-related issues, the Neurons Assistant chatbot helps solve the daily duties of HR staff, focusing them on more strategic and engagement tasks.
AI chatbots can support agents handling customers’ queries during the buying journey. Indeed, 24/7 ongoing support, even outside working hours, can cover the most common questions about the company’s products and services, resulting in improved customer satisfaction.
It can also increase agent efficiency by reducing the volume of repetitive inquiries and calls. Moreover, businesses can continuously improve customer service quality by collecting customer feedback on the knowledge base content.
AI chatbots can use numerous types of knowledge base content to respond to users’ queries. They include troubleshooting guides, a glossary of terms, how-to articles, tutorial videos, and summarized documents.
Knowledge base healthcare chatbots kept everyone safe and vaccinated during the COVID pandemic. The digital healthcare experience has granted patients the flexibility to schedule appointments, monitor medication administration, and address common inquiries.
Moreover, it provides initial mental health support by connecting patients with relevant health resources and evidence-based psychoeducation regarding their conditions. This first line of help prevents patients from feeling isolated.
The knowledge base chatbot frees up their time to handle patients’ routine inquiries, letting them work on more complex tasks. Additionally, it can gather patients’ feedback to help providers improve the quality of care and optimize treatment plans.
The knowledge base chatbot adapts to diverse learners’ requirements by offering personalized approaches and multiple human languages. In addition to learning at school, students can access the chatbot to consolidate knowledge with AI-driven practice quizzes.
As virtual tutors, the NLP-based chatbot can help students understand complex concepts and strategize a suitable learning roadmap to improve their academic performance. Moreover, it enables learners to access accurate and relevant information about campus resources and register for courses.
Chatbot applications can benefit educators in many ways. It assists them in automatically creating assignments and providing relevant feedback tailored to students’ learning progress.
Based on data on student interactions, the chatbot can identify learning patterns to improve teaching methods and curriculum design. It also suggests an effective channel for teachers to communicate with students about important reminders and announcements.
For example, Georgia State University has leveraged the Pounce chatbot to help pupils on its Perimeter College and Atlanta campuses access school admissions, financial aid, and course registration.
The building process involves preparing a knowledge base and training the chatbot. Here are the seven steps that can help you ensure the chatbot’s effectiveness before practical applications:
1. Choose a knowledge base software:
The platform should be easy to use, with plenty of customization options to adapt to diverse business needs. Also, considering its compatibility with the current technology infrastructure is essential to ensure smooth integration.
2. Identify information included in the knowledge base:
You should research to identify common customer questions and define which should be included in the knowledge base. This step allows the AI chatbot to cover all information about customers’ primary needs, enhancing their satisfaction.
3. Set up the knowledge base:
You can implement this step by creating structured categories and subcategories and writing informative articles that address users’ common questions. The articles should be easy for users to find and navigate.
4. Integrate chatbot with knowledge base platform:
You’ll need a genAI API (Open AI or Google AI Platform) to connect the chatbot with the knowledge base platform. Remember to choose suitable tools and techniques tailored to the applications’ specific requirements and the complexity of the knowledge base.
5. Review and update articles in the knowledge base:
Optimize knowledge base articles regularly to ensure users receive accurate and insightful answers. To help customers and bots scan content quickly, use simple language and format the articles logically. Since bots can’t understand images and videos, textual explanations are essential in conjunction with screenshots and other supporting visual materials.
6. Evaluate chatbot performance to make needed adjustments:
Tracking key customer service metrics enables businesses to improve their AI knowledge bases. Some key statistics that you should focus on include:
Applying AI knowledge-based chatbots poses a few challenges that prevent businesses from making the most of it. Here are some issues that you should consider when implementing this chatbot type:
The article introduces the benefits of AI knowledge-based chatbots, along with their widespread use cases and comprehensive building guides. Despite the positive impacts of enhancing customers’ experience with 24/7 personalized support, building an AI knowledge-based chatbot is still challenging. This is the result from its high dependency on knowledge management base quality and staff expertise.
With 15 years of experience across different domains, the Neurond team specializes in analyzing businesses’ issues to develop comprehensive AI implementation approaches. Indeed, the Neurond Assistant chatbot, which we designed, is a well-performed example of a knowledge-based chatbot that brings all the employees together on one page to enhance consistency and overall productivity. Contact Neurond now for a consultation on how we can help you choose the best AI solutions.
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