Build conversational chatbots that solve user queries. Learn how to structure menu navigation, configure NLP keyword triggers, connect webhooks, and setup agent handoffs.
Key foundational blocks to design conversational chatbots that solve user queries cleanly.
Plan chatbot pathways using conversational trees. Keep menus simple, use numbered lists or quick-reply buttons, and ensure users can return to the main menu easily.
Connect your chatbot engine to external APIs. Deliver dynamic order updates, query booking slot availability, and push lead variables directly into databases in real-time.
Ensure complex queries escalate cleanly to live agents. Set up keyword triggers (like 'Help' or 'Agent') and transfer context logs to the shared team inbox panel.
Use structured list menus and quick-reply buttons to prevent user input errors and speed up conversations.
Configure keyword triggers to route users. Detect user intent to guide them through complex queries.
Connect external databases to pull customer data (like account balances or shipment ETAs) dynamically in-chat.
Route conversations to live human support agents, passing along previous logs to prevent repeat questions.
For FAQ deflection and transactional tasks, rule-based chatbots with quick buttons are highly effective. For open-ended customer queries, LLM-trained AI bots are recommended.
Yes. The WhatsApp API allows chatbots to receive and download images, videos, and documents sent by users, saving them directly to your database.
When a user selects an option, the chatbot engine sends an HTTP POST webhook request to your server. Your server queries the database and sends the response back to the user.
A fallback trigger fires when the chatbot doesn't understand the user's input. It typically replies with a friendly message and presents the main menu or offers human support.
