Chatbot Templates: How to Have a Faster Launch
Launching a chatbot with Artificial Intelligence and relevant content can be a complex and time-consuming process. Giving it a good basis and structure is fundamental to get the best results. In this article, we show you some templates of knowledge bases that Visor.ai has.
The implementation and adaptation to your company’s needs are very easy to do. Also, the templates speed up the initial creation process.
To have a good chatbot, you need to follow three key steps: creating the knowledge base, launching, and maintaining it. For everything to work smoothly, it is necessary to have the foundations well laid.
The first and possibly most crucial step to launch your bot is to build the knowledge base. In there, you will have all the information needed for the chatbot to be able to respond to users.
The knowledge base contains the most frequently asked questions that contact centers receive and the answers to them. It is essentially a list of questions and answers that companies have, such as the history of conversations they have obtained from written interactions with clients. On this database are also concepts and expressions intrinsic to their sector.
Specific Templates for Your Business
Most of Visor.ai’s clients are from the insurance and banking sectors, so we created pre-trained models for these same areas. Thus, when new clients arrive, they are already more than halfway done in terms of their knowledge base.
In each template were compiled all questions from all customers in each sector. Of course, we treated the information in such a way that it is as generic as possible, keeping the respective topic. The only task left to the customers is to validate the questions they want the database to have and add the corresponding answers.
The answers are not included in the templates because each customer has his individuality, and we want to show it to their consumers. Another reason we don’t include the answers; it’s because each client has its particular products. However, some products are common to all and others that are particular to a certain brand. Therefore, the client has free access to customize their interactions with customers.
A Chatbot that Distinguishes Concepts and Contexts
To get a little better understanding, we’ll present you with the following cases. In the insurance template, for example, there are questions like “What are the car insurance covers?”. On the other hand, in the banking template, you will find questions such as “How can I open a savings account?”.
In addition to the questions, the Visor.ai templates also contain specific words and expressions used in the different branches. Let’s look at a concept widely used in Insurance Companies, which is that of “acts of God”. At first glance, you can see it as a religious saying, but as it occurs in this specific context, it has the sense of accident or damage caused by natural disasters.
In the insurance context, “acts of God” are the same as an accident caused by an earthquake or a violent storm. So whenever a user says something like “The earthquake damaged my car”, the chatbot will automatically know the type of accident it is and will direct the client to the problem solution.
An example in the banking sector is the concept of “branch”. In everyday life, a branch can have the meaning of a part of a tree, but in a banking context, it means office or agency. Visor.ai’s synonyms lists already have about 100 entries, which consequently helps a lot in the chatbot’s response efficiency.
Grow Your Chatbot’s Intelligence
It must be taken into account that behind these models, there is a whole system powered by Artificial Intelligence, and with knowledge in Natural Language Processing (NLP). These factors allow the bot to distinguish the different question contexts.
Still, it is necessary to keep the concepts and expressions updated on the platform always to obtain the best results.
We talk about expressions, as we recently added a new feature to our Back Office. In this one, you can add all the compound words that often integrate the vocabulary of an industry.
We call “Compound Words” to all expressions that consist of more than one word but have only one meaning. That is, for example, in the insurance industry, the term “car insurance”. When the words are separated, each one has its meaning. However, when followed by each other, they have only one sense. This new update allows Artificial Intelligence to be even more, passing the redundancy, intelligent.
In these two models, the questions are always generic. They can fit in your company because they have no identification whatsoever. Of course, after implementing it, you can change it and adapt it to your brand as you wish (customize the interactions and answers). It is 100% editable, being only a method of accelerating the process of creating the knowledgebase.
To get an idea of the time you can save, the creation of a database on Visor.ai without adopting these models is, on average, three weeks. A process that is already fast when you look at the competition. However, with the incorporation of the templates, this time decreases significantly and can be reduced to half.
Another advantage of these models is that they have a response efficiency of around 40% from the first day of implementation. This percentage may seem low, but it is a performance in which there has been no training or any change. In other words, if you add your insight to these preconceived models, the efficiency rate rises exponentially to well over 70% after a few weeks or months of use.
If you want to speed up the process of creating your knowledgebase and implement an efficient chatbot, Visor.ai has the solution for you. For more information, contact us!