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E-commerce Ticket Categorization
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Leverage NLP to analyze customer support tickets, automatically identifying issue types and routing them to appropriate departments, enhancing response efficiency and customer satisfaction.
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Analyze the following e-commerce support ticket text to identify its core issue type (e.g., logistics delay, damaged goods, refund request, usage inquiry), determine urgency, and recommend the most suitable handling department or solution. Output only the JSON formatted classification result, including ticket ID, issue category, urgency level (high/medium/low), and suggested action, without additional explanation.
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E-commerce Ticket Class
Please read the following customer service message submitted by the user, analyze its core request, and categorize it into one of the predefined ticket types: Logistics Inquiry, Return/Exchange Request, Product Quality Issue, Account Anomaly, or Other. Output only the classification label without explaining the reasoning process, ensuring accurate classification to assist subsequent manual handling.
E-commerce CS QA
Act as a senior e-commerce customer service quality monitoring expert to analyze the provided customer-service dialogue records. Focus on checking if the customer service accurately understood the customer's needs, used standard polite language, effectively resolved complaints or inquiries, and avoided shirking responsibility or emotional responses. Identify key risk points in the dialogue, such as unfulfilled promises, incorrect information, or poor attitude, and provide specific improvement suggestions. The final output should include a dialogue quality score, a description of main issues, and an optimized reply example to ensure improved customer satisfaction and compliance.
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E-commerce Ticket Classifier
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E-commerce Ticket Classifier
Please analyze the following user inquiry text received by e-commerce customer service, determine its business category based on semantics, such as logistics inquiry, return and exchange application, product consultation, or complaint suggestion, and output the corresponding category label and confidence score for subsequent handling by corresponding specialists.
E-commerce Ticket Classification
Act as an intelligent customer service assistant for an e-commerce platform. You will receive raw text from customer inquiries or complaints. Analyze the semantic intent to determine the core issue. If the text mentions delivery delays, categorize it as a logistics issue. If it involves product quality or description mismatches, categorize it as an after-sales dispute. If it concerns account login or payment anomalies, categorize it as technical support. Output a standardized ticket category label along with brief handling suggestions based on key entities and sentiment, ensuring accuracy and compliance with business protocols.
