Guest post by Srushti Shah, Digital Marketer.
Most chatbot conversations start a simple “Hi”. However, as they progress, the conversation often takes a semantically difficult and sophisticated tone. Users start shooting complex questions infested with urban slang and jargon that can leave a chatbot dizzy with confusion (if it were a human!). From figuring out how to get started with a mobile app to asking how to navigate a database, all kinds of questions are shot towards a chatbot. With their innate ability to provide canned responses, chatbots are also able to meet user needs with finesse.
However, there is an underlying resource that enables chatbots to do what they do best — offer contextual information. And that is a knowledge base. A knowledge base is a repository where information is kept in a structured manner. The most commonly seen form are FAQs and helpdesk articles where user questions are answered with elaborate responses completed with screenshots and videos. Until chatbots, live chat software, and the likes came, they were the go-to source for every form of customer support.
Now here is the tricky question. Can a knowledge base help a chatbot? Turns out, it can. As a matter of fact, chatbots need a knowledge base to function properly. Think of chatbots as creatures of Artificial Intelligence. Data is their food. A knowledge base hoards data in a structured manner that makes it easy for chatbots to fetch and serve information to users.
Related: What Role Do Knowledge Graphs Play For Conversational AI?
Let’s explore the top 5 reasons why chatbots need a knowledge base.
5 reasons why a strong knowledge base is required for chatbots
1. Chatbots need diverse source data
Chatbots mimic human conversations. To be able to do that, they need diverse source data from which they can create data learning models. When it comes to conversing with website users, chatbots need to have a rough idea of what kind of questions are usually asked and what should be the ideal answer.
Related: Qualitative Data: The Foundation For Any Useful Chatbot!
For the chatbot to be able to do that, it needs to be trained and integrated with a solid knowledge base. The knowledge base integration enables the chatbot to sift through the already existing questions and answers. It matches the same with the user’s query and determines the closest response that can solve the user’s problem.
2. They need continuous learning
Human conversations evolve from time-to-time and person-to-person. In fact, the same query that one person asks will be put forth by another person in a different manner. Artificial Intelligence and Machine Learning, which form the foundation of chatbots, make it possible to unearth patterns and similarities out of this different yet same kind of question.
For example, text analytics, which is a smaller subset of machine learning, makes it possible to turn a huge knowledge base into a smaller cluster of topics. Each of these clusters can be assigned a tag or a label. The chatbot can refer to these labels or tags to pull out the right knowledge base article that will solve the user’s query.
3. They need structured data
One of the abilities of chatbots is to understand unstructured data input, interpret it correctly, and provide structured output. For example, the user input could come in the form of a question with its own sentence structure and grammatical nuances. The chatbot, with its machine learning capabilities, is able to understand the query, match it to the structured data in the knowledge base, and provide the output. To pull out the structured data, a knowledge base is critical. Without it, the chatbot will have to stretch its resources to find an output which may or may not match user preferences.
4. A knowledge base reduces friction in conversations
One of the reasons why support agents dread live chat is this — the conversation goes on forever. Even with step-by-step instructions, there are customers who are unable to get things done on their own. They need an instruction manual of sorts. Perhaps, this is why knowledge base articles are popular. They are always available for reference and can be easily followed. Even bookmarked if that is the case.
Chatbots work by providing canned responses to user queries. The canned responses have maximum impact if they are of a standard nature and can resolve the user query without any doubt. Hence, the need for a strong Knowledge base to assist the chatbot.
5. Chatbots are primarily used for knowledge management
Although their applications are endless, chatbots are primarily used for knowledge management. Here is why:
- Chatbots are better at organizing information
- They can provide contextual responses
- Chatbots make it easy for users to find information
- They learn from user interactions (semi-automatically) and adapt themselves
- They do not require extensive updates
Related: Supervised vs. Unsupervised Learning – Use & Myths!
All of these put together make chatbots effective at knowledge management. A knowledge base which is primarily a collection of help articles is an ideal form of organized information. They help chatbots to find information faster, in the right context and provide them to customers. Since AI-based chatbots are learning from the user interactions, they become adept at understanding customers and providing them what they want.
By the way, if you’d like to learn more about how to structure your data so you can use it for chatbots and voice assistants – check out this article on using Schema.org to prepare data Conversational AI.
When chatbots started becoming mainstream, one of the popular phrases was that they will become a replacement for every customer support medium. The truth is, chatbots facilitate customer support, but they cannot replace all mediums.
For a successful chatbot, a structured knowledge base is needed to augment their ability to serve customers. It is only when backed by a knowledge base that a chatbot can perform at its full potential. It becomes easier for the chatbot to sift through organized information and offer the right response to the user.
Author’s Bio: Srushti Shah is an ambitious, passionate and out of the box thinking woman having vast exposure in Digital Marketing. She is working as a Digital Marketer and Content writer at Acquire. Her key focus is to serve her clients with the latest innovation in her field leading to fast and effective results. Working beyond expectations and delivering the best possible results is her professional motto. Other than work, she loves traveling, exploring new things and spending quality time with family. Reach out to Srushti Shah on Twitter or LinkedIn
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