How does the chatbot know all this?

If the bot efficiently handles user queries, it means that it has a well-configured knowledge base. It is not an easy task, so it is worth preparing it in cooperation with an experienced chatbot provider. Find out what a knowledge base is, how it is created and what you should read to complete the necessary information. The knowledge base is the source from which the bot derives knowledge in order to be able to display it to the user. In the context of the knowledge base, you can often find a division into a general and substantive knowledge base. The general database has some previously prepared bot’s answers to frequently asked questions that may concern many different companies. Examples of facts in the General Knowledge Base include:

greetings and goodbyes,

thanks,

small-talk

From the perspective of each organization, however, a dedicated (substantive) knowledge base for a specific implementation is of key importance, as it is within this framework that answers to the most important questions of future users are created.

Chatbot knowledge base

Determining the processes to be handled by the chatbot is the starting point for further actions. Based on the client’s needs, the so-called facts or answers to potential user questions. However, writing them down is not the end of the work. Each of these articles must be correctly described with keywords. Teams of specialists on the supplier’s side are responsible for the overall configuration. It is thanks to the knowledge base that the users:

find information about the company’s offer and services;

make a complaint about the service;

talk about recruitment conducted in the company;

receive contact to selected people in the company.

The number of facts in the substantive knowledge base depends on the implementation. Nor is it defined once and for all. The chatbot knowledge base is not only expandable, it is also advisable.

The so-called process bots. Intelligent algorithms are expected to handle the full path of the conversation with the user. Such a path has a beginning, an end, and takes into account the various options of answers given by the user. Examples of such paths are:

acceptance and recording of the loss reported by the insured after the interview;

entering new data into the customer’s account after prior authorization;

informing about the best offer for a given consumer based on the parameters provided by the user.

Scenarios must be prepared in such a way that the chatbot can continue the conversation for different variants of answers, as in this sex chat bot.

Ai Chat Bot operation monitoring

Preparing the knowledge base and launching the ai chat bot in production is not the end of the work. Post-implementation monitoring plays a very important role. At this stage, the knowledge base is still being worked on, supplementing it with gaps that were revealed after the first conversations with real users. Post-implementation modifications and improvements allow for high effectiveness of the chatbot’s work, reaching over 90% understanding of the user’s intentions. “Mature bots” is up to 95% effective.