Table of contentsKey takeawaysCollaboration platforms are essential to the new way of workingEmployees prefer engati over emailEmployees play a growing part in software purchasing decisionsThe future of work is collaborativeMethodology
Bots are of various types
In essence, bots are small pieces of code that are programmed to do a particular task again and again. Old style bots were built based on a set of rules. They were replicators. Rule bots that did A when they came across B, C if they came across D. A trigger could generate a specific response or a set of responses. As technology and algorithm science advanced, it gave birth to chat bots. We will explore the base elements that go towards the construction of a chatbot for FAQ s.
A chatbot is built like most other apps-
- User interaction layer
- Processing engine
- Database hooked to the back
The big difference is the interaction layer which is driven more by a chat messenger platform. The chat platform provides for users to interact with the chatbots published on it as if it would with another human being. So a chatbot replicates the identity schematics of a human entity to register on the chat platform. You can invoke a chatbot in the same fashion as you register or start a conversation with another human being.
The core essence of the chatbot is the engine – it receives messages that users type while interacting with it, interprets them and searches its database for the best response for it. This is a base-level Response Bot or FAQ chatbot.
Generation 1 bots: The basic FAQ bot
When the processing engine receives a request from a user, it does a keyword extraction from the question and tries to match it to questions in its database. When it finds a match, it assigns a probability to the match. This is more of a simplistic looking-up with probability matching. The engine then returns the most probable answer it finds on the asked question.
You can set thresholds in the faq chatbot, say a 40% probability match. If it does not come up with an answer that meets or exceeds the 40% probability threshold, it will provide a default answer to the user query.
Say “I am sorry I did not understand your response. Can you change the question and ask it differently”.
This is not scalable and hence, customers will find it difficult to interact with the bot. We need a more sustainable process that is fast and efficient. Then only users will want to interact with the chatbot, the very reason we have designed the bots in the first place.
You can “train” the bot by...
...studying the pattern of questions that users ask. The quality of the faq chatbot keeps improving over time as more answers come into the database. You “train” the bot as it encounters more and more queries. This, however, is the base-level FAQ bot and the story gets even better as we explore more of where platforms like Engati have reached.
Try out the new world of faq chatbots using an open, best-of-breed platform like Engati for free. It does not require any programming experience and lets you craft intelligent paths to handle the interaction interface of the future. Be the bot be a personal bot about you or a bot that provides for the first line of support and information to your business, product, or service. Predictions are by 2021, 60% of all industries will be using different types of bots extensively. Time to start on your journey today and get a head start over the others?
If you'd like to know more, register with Engati!