To understand the value that a conversational AI brings to a Messenger bot, it is important to look at a few common problems.

Fremont, CA: When Dialogflow and Manychat are connected, one can better understand the messages the user sends using powerful conversational AI from Google. Dialogflow uses Natural Language Processing (NLP) technology in order to process messages. 

Here are a few basic examples to help understand the difference between keyword rules in Manychat and NLP.

Dialogflow enables chatbots to extract actionable data from messages and store that data in Manychat User Fields. Without Dialogflow, one would need to add a massive amount of keyword rules to satisfy an infinite number of user input scenarios, and that’s not very practical. With Dialogflow, you need to create a list of everything on your menu, including synonyms.

With Dialogflow connected to Manychat, you don’t need to send the users to a particular Flow or step in a Flow to request the user input. A user can send a message to my bot at any point and utilize Dialogflow to process that input. In order to do that, the Default Message in Manychat becomes a dynamic request, and one can relay every message the bot receives to Dialogflow so one can process all the incoming messages with AI.

When a message hits Dialogflow, one can respond to the user’s message with a simple text response from Dialogflow, or they can add three lines of JSON code to tell Dialogflow to react with a Manychat Flow. Values that they extract from those messages can be used to search their Google Sheet and deliver a dynamic response.

That’s a brief overview of how Dialogflow works and the value it delivers for the conversational experience. They must group similar things users might say together in a Dialogflow Intent. You can highlight words inside phrases to extract the actionable data from messages, respond with Manychat flows, and use that extracted data to create more intelligent responses with the help of Manychat.

Dialogflow is robust, but it lacks the visual design and marketing tools. Manychat is robust but lacks NLP as well as database capabilities for dynamic content such as a restaurant menu. Google Sheets is suitable for managing frequently and changing content, such as a restaurant menu. Still, when these systems are combined, the result is a dynamic conversational food ordering experience, which will delight customers and produce the business results.

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