Chatbot knowledge base 2024: definition & best practices

Overview:

Though AI-powered chatbots serve as an increasingly capable tool for businesses today, they still require human guidance, particularly in the implementation stage. A knowledge base is where bots acclimate with a business, identifying the most common questions, organizational processes, brand identity, and more.

To deliver a frictionless and personalized customer experience (CX) for end-users, you must ensure that your base is stocked with as much relevant information as possible and that your chatbot can always access this data. Deploying a chatbot without sufficient knowledge is akin to building a library without books. Just as a library relies on its collection of literature to fulfill its purpose of providing resources to visitors, a chatbot depends on its knowledge base to realize its role of assisting users.

Today, we’ll look at what a chatbot knowledge base involves, why it’s important, and how to tailor it to best serve your company.

What is a chatbot?

A chatbot is a computer program designed to simulate conversation with human users, typically over the internet or through messaging platforms. These programs utilize artificial intelligence (AI) techniques, such as natural language processing (NLP) and machine learning, to understand user prompts conversationally. These bots can be used for various applications, including customer service, information retrieval, and entertainment.

One of the key features of chatbots is their ability to understand users' natural language inputs. Through NLP algorithms, bots can interpret the meaning behind messages, allowing them to generate appropriate responses. This enables individuals to interact with them like how they would communicate with another person, promoting more user-friendly communication.

Chatbots are quickly becoming one of the most commonly used automation tools by businesses today; usage has increased by an astounding 92% since 2018.

What is a chatbot knowledge base?

A chatbot knowledge base is the repository of information that a bot can access to respond to user queries. It functions as the backbone of the chatbot, providing the necessary data for generating accurate and relevant responses. The knowledge base is typically structured to allow the bot to retrieve information to address user inquiries effectively and quickly.

For instance, an organization in the healthcare sector may organize a vast array of medical information from journals, textbooks, clinical guidelines, and expert opinions. This information could encompass various aspects of healthcare, including medical conditions, treatments, preventive care, and emergency procedures. Regular audits should be conducted to ensure that the base remains aligned with the latest medical research and best practices.

Why should you integrate your knowledge base with your chatbot?

Providing your chatbots with a sufficient knowledge base lays the foundation for their effectiveness and ultimately their growth. With it, your bot can understand your brand identity, what your customers are looking for, and how to tailor interactions to unique user segments.

Quick and accurate responses to customer inquiries

By storing vast amounts of data ranging from frequently asked questions (FAQs) to in-depth details related to a business’s offerings, a knowledge base empowers chatbots to access relevant information instantly. When a user interacts with a bot, it scans their query and retrieves corresponding information from the base, allowing it to respond promptly with accurate answers.

The structured organization of the knowledge base also enhances the chatbot's ability to provide pertinent responses. Information within the knowledge base is categorized based on topics, keywords, or intent, enabling the bot to identify the most applicable content for each query. As a result, customers receive personalized responses that directly address their inquiries, minimizing the likelihood of misunderstandings.

90% of users can answer their questions in 10 or fewer messages when utilizing chatbots; this wouldn’t be possible without a robust knowledge base.

Increased efficiency and customer satisfaction

Chatbots can improve customer satisfaction by offering reliable support around the clock, regardless of human availability. Unlike traditional support channels with limited operating hours, bots can assist 24/7, guaranteeing timely responses to inquiries at any moment. Knowledge bases ensure that these chatbots possess the resources to resolve a wide range of issues autonomously, as human agents may not always be available.

Additionally, by standardizing responses, knowledge bases help maintain high consistency across all interactions. Customers appreciate the reliability of the information provided by the chatbot, knowing that they can trust its responses to be accurate and up-to-date. With real-world agents, users sometimes receive conflicting information from one conversation to the next.

Enhanced automation

By categorizing data based on topics, keywords, or intent, chatbots can efficiently retrieve relevant information and execute predefined actions. For instance, bots can automate order tracking, appointment scheduling, payment processing, and basic troubleshooting steps. This automation streamlines workflows, reduces manual intervention and enhances operational efficiency.

Furthermore, by analyzing user interactions and feedback, organizations can identify opportunities to improve automation, refine response algorithms, and expand the chatbot’s capabilities. Machine learning algorithms can monitor performance and adapt responses based on evolving customer needs.

67% of business leaders believe that machine learning in AI systems will be vital to their company’s ability to keep up with competitors in the future. Combined with an applicable, up-to-date knowledge base, chatbots will only grow more capable with time.

Reach a wider audience 

Storing a diverse range of information about products, services, and policies in knowledge bases enables businesses to cater to the needs of broader audiences. Chatbots can also be integrated into various communication channels, including websites, mobile apps, social media platforms, and messaging applications, allowing companies to engage with customers wherever they are. 

Many chatbot knowledge bases offer multilingual capacity, allowing organizations to communicate with customers in their preferred language. By storing information in multiple dialects and leveraging NLP capabilities, bots can respond to user queries in many different languages, enhancing accessibility for non-native speakers and international customers. This multilingual capacity empowers businesses to connect with a global audience, expand into new markets, and build relationships with consumers from diverse cultural backgrounds.

Types of knowledge base chatbots

The choice between rule-based and AI-based FAQ chatbots depends on your organisation's specific needs. Rule-based bots are typically more suitable for scenarios where inquiries are limited and well-defined. In contrast, AI-based bots may be a better fit for those seeking greater flexibility, scalability, and adaptability.

Rule-based FAQ bot

A rule-based FAQ chatbot typically operates on predefined rules that dictate how it respond to user input. The rules usually involve matching keywords in the user's message to specified responses stored in the knowledge base. For example, if a customer asks about specific product features or pricing, the bot will identify those keywords and provide a corresponding pre-written response.

Rule-based chatbots are commonly used for handling FAQs or providing basic customer support in scenarios where inquiries are unambiguous and don’t vary much. They’re relatively simple to set up and maintain, as they don’t require sophisticated machine learning algorithms or extensive training data. 

AI-based FAQ bot

On the other hand, AI-based chatbots are more sophisticated conversational agents powered by NLP and machine learning. Unlike rule-based chatbots, AI chatbots are capable of interpreting user input in a more human-like manner. They’re able to analyze context, semantics, and intent, enabling them to generate more contextually relevant responses.

These chatbots utilize machine learning algorithms to process large volumes of data and identify patterns in user behavior. Through this iterative process, they can adapt their responses based on feedback and real-world interactions. They may also integrate with external data sources and APIs to access up-to-date information and provide more personalized assistance.

How to build a chatbot knowledge base

Building a knowledge base that caters to the unique needs of your business and customers will require a thorough organizational assessment, extensive research on providers, and routine maintenance to ensure its effectiveness.

1. Define business goals

Without clear benchmarks in mind, companies risk developing a knowledge base that fails to align with the specific needs of their target audience. By defining unambiguous goals, organizations can articulate their overarching objectives, whether improving customer service, increasing sales, or reducing support costs. Goal-setting serves as a guiding principle throughout the development process, informing decisions about content creation, feature implementation, and performance measurement.

Even considering the undeniable importance of setting clear goals, only 51% of businesses attempt to establish them, which could be a major reason that 50% fall short of reaching long-term benchmarks.

Moreover, these objectives help organizations identify key performance indicators (KPIs) to measure the impact of the chatbot knowledge base. By identifying metrics such as customer satisfaction scores, response times, and resolution rates, companies can track the performance of the knowledge base against predetermined benchmarks.

2. Choose the right knowledge base platform/information to include in the knowledge base

Firstly, evaluate a potential knowledge base provider’s features and functionality to determine if it meets your business's specific requirements. Consider factors such as the ease of content management, support for multimedia, NLP capabilities, and advanced analytics tools.

When determining what information to include in your base, it's crucial to identify FAQs and common customer issues across various channels. Analyzing customer feedback and support data can provide further insights into the types of inquiries users have and the information that they seek. 

3. Establish technical scope

You’ll need to consider the technical infrastructure required to support the chatbot knowledge base. Determine the platform that will be used to develop the bot, whether it's a custom-built solution, a third-party chatbot platform, or an open-source framework. Then, assess the scalability and security requirements of the knowledge base to ensure that it can handle the expected volume of user interactions securely. 

Once you’ve done this, establish a roadmap for the implementation of the knowledge base, outlining key milestones, deliverables, and timelines. Make sure to clearly define roles for team members involved in the development, including designers, content creators, and stakeholders. Also, don’t forget to plan for potential challenges that may arise during the implementation process and develop strategies to mitigate them effectively. 

4. Determine the integration method with the chatbot

Ensure that your knowledge base platform supports the required features and functionalities for your chatbot. Many knowledge base software provide APIs or SDKs that allow developers to integrate the knowledge base with third-party systems, including chatbot frameworks.

You can also develop custom connectors to facilitate communication between the two systems, allowing the chatbot to access information from the knowledge base as needed. Test the integration thoroughly to identify any issues in data retrieval, response accuracy, or performance. 

5. Regularly review and update the knowledge base

Lastly, remember to conduct regular audits of your knowledge base content to identify outdated information or gaps in coverage. This involves reviewing user interactions and feedback to identify common issues that may need to be addressed. You’ll also want to regularly communicate with stakeholders to gather insights into areas for improvement and emerging trends.

If you do uncover any weaknesses, develop a plan to update the chatbot knowledge base accordingly. This may involve creating new content, updating existing information, or restructuring the base to improve accessibility. Prioritize updates based on the importance of the content, ensuring that critical information is addressed promptly.

How Freshworks can help you make the best use of chatbots for customer service

Freshworks’ Customer Service Suite includes a conversational AI interface, facilitating the most robust chatbot capacity of any support software available today. Powered by Freddy AI, Freshworks’ bots are fast, versatile, and accurate offering intelligent automation, polyglot capabilities, and integration with the most popular third-party applications. Utilize their omnichannel potential to automate conversations on your customers’ preferred platforms, whether it’s on your website, mobile app, messenger applications, or elsewhere.