Efficient automated service for inquiries and support via WhatsApp
Tambaqui Na Brasa implemented a digital assistant for automatic atendimento focused on questions via WhatsApp, with forwarding to human support when necessary.
Summary: Efficient automated service that responds to inquiries quickly, improves the customer experience, and keeps human support available for cases that require special attention.
A feature connected to the customer's real routine.
Tambaqui Na Brasa is a Brazilian restaurant specializing in fish dishes, seeking to optimize customer service via WhatsApp, offering quick and accurate responses to frequent inquiries, maintaining a professional and direct tone. Automate the service to respond to common customer questions, reducing the need for human intervention and speeding up support.
The assistant was configured to operate on WhatsApp, interpreting images, audios, and links sent by customers, responding to inquiries professionally and directly. The system routes to human assistance when requested by the customer, shows dissatisfaction, requests special negotiation, or asks questions that require internal analysis.
The project transforms conversation into an operational process.
The case shows the objective, module used, and experience created on WhatsApp, without relying on internal metrics.
Ensure efficient and professional service that responds to common questions and correctly identifies when human assistance is necessary, without losing agility. Configure the assistant with a professional and direct tone, activate the feature to interpret media sent via WhatsApp, and clearly define the rules for passing to human assistance, including triggers for dissatisfaction and specific requests.
How it works for the customer.
The page translates the usage flow into a clear public narrative, without the feel of an internal manual.
Next steps of the setup.
Importance of clear rules for escalation to human support
The value of a professional and direct tone for the restaurant segment
Benefits of media interpretation for better understanding of requests
Need for continuous monitoring for adjustments and improvements
Monitor the assistant's performance for fine-tuning, consider integration with internal systems to expand response scope and explore new functionalities to increase automation.
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