For your company’s chatbot to know how to answer your customers’ questions, you need to have a good AI knowledge base.
In this article, you will learn what a knowledge base is, how important it is for a chatbot to operate, and how you can improve it to always get the best results!
What is an AI Chatbot?
A chatbot is an intelligent virtual agent used to optimize communication processes between companies and their customers. However, companies can also use chatbots as internal support for employees.
To learn more about internal chatbots, see the article What Can Internal Chatbots Do for Your Company?
Nonetheless, to be considered intelligent, these agents must possess certain characteristics. In other words, they need certain necessary technologies to have some form of intelligence.
AI for Intelligent Machines
When talking about machines, the term “intelligence” is much debated. We have always been taught that humans are intelligent because of their ability to develop reasoning.
But, nowadays, it’s already possible to program machines to mimic the thinking process of humans.
First, since we are talking about conversational agents, they need to understand and process human language. To this end, they need NLP or Natural Language Processing technology.
For a system to learn the human language, it is fundamental to have linguistic knowledge.
Learn here how important linguistics is in your chatbot.
Second, for the machine to imitate the learning process, it needs Machine Learning technology which, as the name implies, is the one that allows a system to learn by itself.
What is an AI Knowledge Base?
Well, we can divide knowledge bases into two poles. The first concerns the human knowledge base, and the second the “mechanical” knowledge base, let’s call it.
Generally speaking, a knowledge base is all the information acquired and needed to perform a certain task.
The Human Knowledge Base
The human knowledge base is typically known as “knowledge” only. It’s all the information that a person acquires from birth. All the experiences, the learning that is recorded in the brain.
One kind of knowledge is acquired through transmission, like when our parents tell us “don’t touch the oven or you’ll burn yourself” or when they teach us how to speak.
Another kind of knowledge is intrinsic to us, like learning to walk. Just by the experience of seeing other people walking, the baby, on its own, finds a way to start moving more effectively until, eventually, it starts walking.
The Mechanical Knowledge Base
This type of knowledge is similar to the previous one in the aspect of transmission. That is, if the machine is not fed with data, it will never have any intelligence.
Even if we give it the ability to learn by itself, it will never “join the dots” without information.
So, long before a system or, in this case, chatbot starts to learn, it has to have data it can use – a knowledge base.
Put it like this: in chatbots, a knowledge base is a library that gathers structured and unstructured information.
From the structured information, the bot can categorize the unstructured.
Why Do You Need to Create a Good Knowledge Base?
As we have already talked about, the chatbot needs structured information to interpret and categorize the unstructured data subsequently.
But what differentiates a good database from a mediocre one?
A good database has all the information that is indispensable for the system to do its job well.
Just as we need to know a lot about baking to make a great cake, the same is true for chatbots.
If we want them to have a conversation as similar to humans as possible, then we need to give them all the information they need to make that happen.
Of course, your chatbot won’t need to have the same knowledge as a human being (yet). But it should be an expert on the topic. In this case, the product or service your company is offering.
The Easiest Way to Improve Your Chatbot’s Knowledge Base
“Okay. I already have a chatbot implemented in my company’s digital contact channels. The bot responds well to the questions asked, but it could still be better.” – you think.
Well! You don’t have to wait any longer because the answer is Visor.ai’s platform.
The Visor.ai platform is designed and regularly updated to be as intuitive to use as possible and to users to make the changes they want independently.
During the setup period, Visor.ai provides templates that help the implementation be faster because they already include the basic information for each sector.
But beyond that, the Visor.ai platform offers several tools where you can edit and improve your chatbot or email bot’s knowledge base.
To learn more about automating the handling of incoming emails, click here.
5 Features to Enhance your Knowledge Base
1) FAQs
The FAQs tool is where you can build up, so to speak, the overall interactions of your chatbots.
That is, this is where you include the most frequently asked questions by your customers regarding your products or services.
2) FAQ Conflicts
In the FAQ Conflicts, you can see the conflicts that the chatbot is having between different FAQs.
These conflicts come from phrases often having similar information and the chatbot not knowing which one is the most correct when answering the user.
3) Small Talk
Natural conversation between two humans is not only about scientific and interesting topics. Often it is the so-called “small talk,” conversation without much content, but which is also necessary to maintain a certain climate.
The same has to happen with your chatbot if you want to offer an alternative that is as similar as possible to human dialogue.
It is in the Small Talk of the Visor.ai platform that you define these dialogs. From “Good morning! How are you?” to “Who is your creator?” or “What time is it?”.
All these small talk options have to be present in your chatbot’s knowledge base.
4) Text Analysis
In addition to defining interactions, it’s important to give more detailed knowledge, namely words that have the same meaning or words that, appearing together (compound words), have a certain meaning.
This is where the Synonyms and Compound Words sections come in.
In the first, as the name indicates, you can add synonymous words.
For example, if you are part of an insurance company, you can say that “disaster” is the same as “accident,” “incident,” etc.
In Compound Words, you can teach the bot that it can take expressions like “citizen card” as one entity when analyzing user requests. As opposed to parsing word by word.
5) AI Trainer
Finally, in AI Trainer, you can check your chatbot interactions with your customers.
In this tool, you see all the new user sayings that are not yet in the knowledge base and how the chatbot answered them.
Again, the chatbot can answer questions that are not exactly the ones in your database because it has Artificial Intelligence.
In addition to verification, you can correct the interactions that the chatbot had doubts about and teach it the most appropriate answer. Additionally, you can directly add new FAQs.
This process allows you to increase the intelligence of your bot and make it more efficient.
To learn more details about how to train a successful chatbot, click here!
Conclusions
The Visor.ai team developed the NLP and ML technologies in-house to get the best results and meet our customers’ requirements and needs.
That means that all the knowledge about the human language, its rules, and so on are covered when implementing Visor.ai solutions.
The templates we told you about earlier also cover information related to a certain sector, such as Insurance, Banking, or Marketing.
However, there’s no one better than you to talk about your company or product.
You must include this information in your chatbot’s knowledge base yourself.
If you need help or more information, don’t hesitate to contact the Visor.ai team! We’re always available to hear from you!
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