How Do Chatbots Tie In With Technical Documentation?

In the 21st century, every effective company employs conversational user assistance to ease the customers’ life. Such aid is helping customers through dialogues with digital AI assistants.

Chatbot assistants:

• have seen 92% growth as a brand communication channel since 2019.
• were used by 67% of global consumers in the past year.
• will handle 75–90% of healthcare and banking queries by 2022.

What Is a Chatbot?

A chatbot is a text-based dialogue system with natural language capabilities. For the bots to answer your question correctly, they must be fed with a lot of information stored in a knowledge database. The user asks a question, and the bot delivers the answer because it understands the intention behind the user’s query and can therefore search for the corresponding entry in the knowledge database.

Why Do We Need Chatbots?

A chatbot is seen as one of the most advanced and promising expressions of interaction between humans and machines.

• A chatbot can enhance and engage customer interactions with less human intervention.
• It removes the barriers to customer support that can occur when demand outpaces resources. Instead of waiting on hold, customers can get answers to their questions in real-time.
• Less service friction can improve the brand experience for customers.
• For companies looking to improve their customer experiences, the addition of chatbots to answer simple questions can enhance satisfaction, streamline the customer journey, and provide customer-centric support.

How Does a Chatbot Work?

Chatbots can be either stateless or stateful. Stateless chatbots approach each conversation as if interacting with a new user. On the other hand, stateful chatbots can review past interactions and frame new responses in context.

Adding a chatbot to a service or sales department requires low or no coding. Many chatbot service providers allow developers to build conversational user interfaces for third-party business applications.

A critical aspect of chatbot implementation is selecting the right natural language processing (NLP) engine. If the user interacts with the bot through voice, for example, then the chatbot requires a speech recognition engine.

Chatbots and Technical Documentation

The company’s technical documentation already contains much of the information that a chatbot communicates. So, for a chatbot to operate correctly, we need to reuse the existing content and improve the consistency of communication. The question is: how do you prepare your technical documentation for conversational user assistance?

A chatbot cannot address all possible use cases, so start with the most likely ones. To find out about such use cases, look at the existing technical documentation, use service protocols, call the support or discuss it on social media.

We could consider the following use cases as the most common ones:

• Interactive investigation
• Instructions for simple tasks
• Explanations: why do a certain step
• Suitable products: for example, spare parts, services

A chatbot must be able to interpret the user’s demand to understand the issue and answer most helpfully. After the first statement, the request for more information follows. Keep in mind that there are many ways to convey a request and try to cover all possibilities.

The further bits of information are called “entities.” The chatbot gathers information from the users during the conversation and gradually applies it to fill pre-defined “slots.” This procedure is called “slot filling.”

Your user can use terminology that is different from the one used at your company. So you should complete entities with commonly used synonyms. When the chatbot recognizes the user’s aim and all entities by analyzing the user’s statements, it selects the most appropriate answer.

Usually, the user’s statements do not provide all the necessary information. In this case, the chatbot asks the user questions to specify the information. Such programs operate through intelligent information. So your existing documentation usually needs to be revised before it can be reused for chatbots:

• Content should solve one problem with a concise and clear answer.
• The topics should be provided with metadata that helps a chatbot to find the right information
• Your content should be structured and independent of media.
• Take into account the particularities of a target audience (a formal or informal form of address, for example).

Conclusion

Chatbots make it easier to resolve customer issues and eliminate a significant amount of manual work for support teams. A deeper contextual understanding of language is required to make information more easily accessible by the chatbot. It is possible to use technical documentation for chatbots, but it requires reworking the applicable existing content where users and their issues are put into focus.

Stay well!

Amrit.

“Follow the river and you will get to the sea.”