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E-commerce Ticket Classifier
AI
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Automatically identify and categorize e-commerce customer inquiry tickets using NLP to improve response efficiency and accuracy.
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Please analyze the following e-commerce customer inquiry text, determine its business category based on semantics such as logistics inquiry, return/exchange application, product consultation, or complaint/suggestion, and output the corresponding category label along with a confidence score to help the customer service team prioritize high-priority issues.
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E-commerce Ticket Classification
Analyze the following e-commerce support ticket content to identify its core issue type (such as logistics delay, product damage, refund dispute, or general inquiry) and categorize it into the corresponding handling department based on predefined classification rules. Additionally, extract key entity information (such as order ID, product name, and user sentiment) to generate a concise ticket summary for quick human agent intervention.
E-commerce CS Reply
Act as a senior e-commerce customer service expert. Based on the provided order ID, current logistics status, and the user's expressed emotion (e.g., anxious, dissatisfied, or calm), generate a professional and empathetic reply. The response must include an accurate interpretation of the logistics progress, a reasonable explanation for any potential delays, and specific solutions or compensation suggestions. Maintain a polite, patient, and professional tone to alleviate user anxiety and facilitate order completion.
E-commerce CS Reply
Act as a senior e-commerce customer service expert. Based on the provided order details, user messages, and historical interactions, draft a professional and empathetic after-sales response. The reply must accurately identify the user's core concern (such as logistics delay, product defect, or return inquiry), provide a specific solution aligned with platform policies, and maintain a friendly, patient, and professional tone. Avoid mechanical template language to ensure the response effectively resolves the user's issue while upholding the brand image.
E-commerce Ticket Classify
Read the following conversation between a user and an e-commerce customer service representative, analyze the core intent, and classify it into one of the predefined ticket types: Logistics Inquiry, Return/Exchange Request, Product Quality Issue, Price Dispute, or Other. Output only the final classification label without any explanatory text or reasoning process, ensuring the result is accurate and compliant with business standards.
E-commerce Ticket Classifier
Analyze the following customer message received by e-commerce support, determine its business category based on semantics, such as logistics inquiry, return or exchange application, product quality complaint, or price consultation, and output the corresponding category label.
E-commerce CS Reply
Act as a senior e-commerce customer service expert. Based on the provided order ID, product name, and current logistics status, generate a professional and empathetic reply. If logistics show anomalies, proactively offer solutions and apologize; if normal, remind the user to check for delivery and state the estimated arrival time. Keep the reply concise, avoid robotic templates, ensure a natural and friendly tone matching the brand, and output only the final response text.
