A Hybrid Chatbot is more than just a chatbot. In addition to bot-to-customer conversations via pre-chat form, post-chat survey, conversational forms, response to repeating customer queries, the Bot also controls a chat conversation based on different internal or external events.
You may use Rasa, Google DialogFlow, or can integrate any bot of your choice using Chatbot API.
Hybrid Chat contains rasa.ai out-of-box but it can be integrated with Google DialogFlow, IBM Watson, Microsoft LUIS, or any bot implementing Chatbot API. The chatbot may serve the customer directly as a primary interface or assists the human agent by giving suggestions on every customer query. To learn how Hybrid Chat integrates with a bot, see:
Control Conversation by Bot
Channel wise Bot Response
The bot may be trained to give a channel-specific response. Hybrid Chat Bot-connector passes the channel name in the
Channel-wise bot response is applicable only to RASA bot
Pre-chat form data collection
A conversation form on any chat channel may be developed using the bot training. Hybrid Chat allows structured/unstructured communication between the customer and the bot. The bot may use this data for any back-office function and hand-off the conversation to a human agent if needed.
Post-chat Feedback Collection
A new environment variable with the name
Messages exchange between the customer and the bot after transferring the chat to the bot are stored and maintained as part of the conversation/chat session history.
|End Conversation||The Bot can send a custom-action via SuggestAction API with action_name |
The integrated bot can request to hand-off a chat to a human agent using SuggestionAction API. The bot may specify the queue to handoff the request to. If not specified, the default queue will be used.
In Queue Messaging
When the Bot has initiated hand-off request via SuggestAction API with action_name "