How to Build a Knowledge base for Your Chatbot

Whether you are planning on building a simple FAQ chatbot, a virtual assistant, or another sophisticated AI conversational application, it cannot function without data. Building a rich knowledge base is the first step to using automation and natural language processing to help your customers connect with your AI conversational agent.

AI is getting lots of traction among diverse businesses for making customer assistance solutions. Moreover, it is considered a realistic and attainable option for businesses of different types and sizes, instead of the popular belief that AI is only accessible to enterprises with large budgets and development teams.

A competent knowledge base ensures that your bot can handle different kinds of customer requests and offer resolutions to a wide range of issues and queries. So, preplanning your knowledge base will improve chatbot efficiency and services. Many chatbots come with in-built knowledge bases, but data changes frequently in the processes and knowledge bases must be updated to offer accurate responses to the customers.

So, businesses may need to return to the vendor or hire developers to update the KB. But a knowledgebase management software can instantly update and modify chatbot knowledge bases without any developer assistance. It allows users to  update knowledge bases manually with frequently forwarded questions to agents or revise the answers that customers have trouble understanding.

Chatbots can also assist in improving knowledge bases. These knowledge bases grow over time by acquiring new information and are enhanced by a self-learning capability.

Build a Knowledge Management Strategy

Knowledge base management refers to a process of collecting, storing, organizing, and sharing internal information. A knowledge base management strategy ensures better utilization of this information.

Moreover, the knowledgebase management strategy helps align KB users' interests with knowledge base use to help them achieve their objectives. Chatbots are highly self-preserving and continuously collect, analyze, and grow their intelligence from user interactions. Therefore, chatbot knowledge bases also grow and become smarter with increasing volumes of customer conversations.

If you already have a KM strategy and now building a chatbot using the knowledge base, clearly define your strategies and purposes for the bot knowledgebase. If you want to share information for empowering customers and relieving agents, ensure the internal chatbot knowledgebase can serve its purposes.

Therefore, create a strategy and put clear purposes in place before building or incorporating a knowledge base into your chatbot. Chatbots must be correctly integrated with knowledge bases to attain business objectives and reach their targets.

This includes planning what information will be incorporated into the knowledge base and what kind of information must be provided to the chatbot for better user support. Often, organizations start with explicit knowledge, such as manuals, guides, and reports, when building a knowledgebase for the chatbot.

Knowledgebase management software builds the knowledge base extract, arranges the information, and deploys them into the chatbot KB. It makes these intelligent solutions capable of handling most of the customer requests, but remember that knowledge gained through experience, such as tacit and implicit knowledge based queries, is better handled by agents.

So, a chatbot can be integrated with customer messaging services, and both should work together to support the customers.

Select appropriate infrastructure

Prepare the infrastructure and select appropriate framework before implementing your chatbot and chatbot knowledge base. Organizations can choose from existing chatbot infrastructure and tailor it to their business needs. Businesses can also develop chatbot and deploy knowledge base in-house. Multiple types of chatbot platforms are available with capabilities to build chatbots, ranging from basic functionalities to advanced and complex features.

Create rule-based bots with FAQs or self-learning chatbots using APIs. Chatbots can also come with internal knowledge bases and knowledge base management software for updating them. These chatbot providers offer to incorporate process information and answers, images, and links customized to fit the organization.

The knowledge base can power up the responsive FAQ solutions, and your chatbot will be instantly ready to chat. Once you have chosen your chatbot infrastructure, start preparing your data.

Determine and collect data for your chatbot

Suppose you have a knowledge base or a robust FAQ page that you want to implement in your chatbot. In that case, these can be integrated into the bot to power conversational applications instantly. But in most cases, additional data must be incorporated into the chatbot, or knowledgebase content needs to be collected from diverse sources.

Gather the customer or user queries for FAQ bots that are often asked by these people. To list these questions, you can consult sources, like live transcripts and conversational logs from calls and emails. Next, you can arrange them into the following categories:

·        Product or service-related questions:

Any queries related to your product, services, and the company that these users often ask (e.g., customers asking if you have a white shirt)

·        Frequent problems/ issues:

Common issues or troubles that customers or users often face and need resolution (e.g., customers forgetting their password)

·        Pricing and plan-related queries:

Customers or users asking about pricing structures or available plans (e.g., customers asking about different plans available for subscribing to your services)

·        Common customer or user requests:

Customers often put these requests or pose these questions on discounts, sales, free trials, free shipping, and more. (e.g., Can I change the shipping address on my order)

·        User/ customer feedback:

Positive and negative comments and feedback on your products, services, and company (e.g., Thank you for the tutorial video, it was really useful in setting up my device.)

Not all queries are suitable for adding to the chatbot knowledgebase. The chatbot should have options to transfer calls to the agents. They should collect these difficult and complex questions, ask relevant details, and forward them to the agents.

These events will decide which topics should be deployed into the knowledge base and how these topics can be organized to ensure that the customers or users can make the most of the data.

Knowledge base contents should include tables, infographics, and other visual elements for better user comprehension and experience. A knowledgebase management software can help design and present chatbot knowledgebase data better, using images, links, rich texts, and adaptive cards.

Make the data simple and accessible for the chatbots

Unstructured or semi-structured data must be reworked into a structured and conversational format to be added to the chatbot knowledge bases so that your AI conversational solution can access the data to perform its functions.

Different chatbot platforms and developmental frameworks need different kinds of data organization. For example, some popular chatbot-building platforms must arrange data into questions and answers. The chatbot must identify the intents and entities.

Also, often, dialogues are created with multi-turn prompts to train the bot to better cater to the customers' or users' requests. In addition, chatbots are trained with alternate questions for the same answers to increase the chances of offering a resolution. Segmenting and analyzing the knowledge and creating the right flow to feed it to your AI solution will determine how efficient your chatbot will be for its users.

Knowledge base management software for chatbot knowledge bases allows users to create, edit, and manage KB data. It also offers the freedom to create questions and answers with customized features according to their needs.

Customize the language to suit the chatbot's persona

User-friendly chatbots must carefully consider their tone and personality. These will guide how to write the scripts for the chatbots and help offer users with a more enjoyable and meaningful experience.

Chatbot responses should be designed according to the bot's persona and your brand image. The language and content organization in the chatbot knowledgebase should also be in tune with the chatbot's role, persona, and brand.

·        Responses should be brief.

For describing complex subjects, like your terms and conditions, walls of text are not required. Instead, direct visitors to your website's FAQ page or relevant web pages.

·        Don't respond with "yes" or "no."

Even the most sophisticated chatbots still struggle to understand the intricacies of human speech and conversation and modify their responses to fit the context. For example, the chatbot may respond "Yes, it is" to a customer's question about whether delivery is free.

However, if they inquire, "Do I have to pay for delivery?" and the chatbot replies, "Yes, it is," it will sound absurd. Therefore, it is preferable to train the bot to respond, "Deliveries are free." Thus, it can avoid sounding absurd and annoying the user.

·        A chatbot should not ask, "What can I do for you?"

It's an invitation that can leave you feeling unsatisfied. Instead, introduce it by name, clarify that it is a chatbot, and describe its capabilities ("I can assist with shipping, returns, and missing products").

·        Include the user's request in your response. 

It improves the chatbot's intelligence and elicits empathy. For instance, a consumer might inquire, "Do you have shops in Seattle?" A chatbot might respond, "Unfortunately, we don't have shops in Seattle, but we do in Oregon and Montreal."

Wrap Up

Choosing live chat with AI features is an excellent alternative for businesses looking to consolidate their customer service software. The AI chatbot chooses the best response from its knowledge base after understanding and analyzing the customer's intent. When it doesn't understand a question, it forwards it to an agent. It is essential to ensure that your customers' needs are always properly addressed.

According to a survey on consumer views of chatbots, users expect it to be simple to escalate a problem to a human agent if a chatbot cannot assist them. The chatbot is linked to the central knowledge base and improves its accuracy through chats and questions. Customers can receive consistent and quick answers with FAQ chatbots which pull answers from the internal knowledge base full of process information and business data.