A step-by-step program to solve the smart customer service response and accuracy problem
Background:Traditional intelligent customer service often faces pain points of delayed responses and inaccurate answers, and Botnow provides a systematic solution through modular functionality.
Core Operating Procedure:
- Building a knowledge base system
- Create a structured knowledge base in the console and upload FAQ documents by product/service categories
- Recommended mixed PDF+Excel format to improve semantic recognition accuracy
- Configuring the Workflow Engine
- Setting up a three-tier response mechanism: direct answers to simple questions → transferring complex questions to manual labor → triggering approval for sensitive questions
- Optimize trigger conditions and set keyword matching weight thresholds (0.7-0.8 recommended)
- Plug-in Enhancements
- Integrated multi-round dialog plugin to handle complex inquiries
- Add Sentiment Analysis Plugin to Identify User Urgency
Optimization Recommendations:
Weekly through the platform'sAnalyzing KanbanCheck: ① High Frequency Unresolved Problems TOP10 ② Average Response Time Curve ③ Session Conversion Rate, and continuously iterate on the knowledge base content.
This answer comes from the articleBotnow: AI Intelligent Body Creation and Distribution Platform for Smart Marketing and Smart OfficeThe
May not be reproduced without permission:AI productivity tools " How to utilize the Botnow platform to solve the problem of slow response and low accuracy of enterprise intelligent customer service?
