In our previous chatbot explainer posts we discussed the basics of chatbot building including the different kinds of nodes, as well as intent detection and entity extraction. Today we will introduce chatbot templates, which enable the enterprise user to develop a chatbot not from scratch but rather from a pre-built model of the necessary building blocks. Chatbot templates are classified in the Building category of chatbot product features.
Upon creating a chatbot, the chatbot building platform offers the enterprise user the option to create it from a blank canvas or from a chatbot template. The chatbot templates are usually organized by use cases, verticals, features, integration options, and deployment channels. The templates can range from simple use cases such as welcome bots for websites or FAQ bots for restaurants to complex solutions such as airline booking bots or retail banking bots. The chatbot platform may also show the user the number of downloads each template has had in order to gauge its popularity, as well as a brief description of the template and its features.
After deciding which template to use, the user can import the template to create a new chatbot. All the nodes, logic, intents, utterances, and entities in the template would then be made available in the new chatbot. For example, an airline booking template might include pre-built intents such as “book flight,” “change seat,” and “check baggage fees,” as well as pre-built entities such as city names and airport codes around the world. After importing the template, the user can customize these elements and continue building the chatbot from there. Chatbot templates thus save the user time and effort by providing them a blueprint and starter kit for the chatbot development process.
The screenshot above shows a selection of chatbot templates from an example chatbot vendor – Tidio.
Our chatbot explainer series shares our knowledge of chatbot product features. If you have any questions, please reach out to me directly and follow me to get notifications on future posts.
Dong Liu, Founding Analyst
dong@daybreakinsights.com
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