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Maison Liste de prompts IA AI Classement Billets EC

Classement Billets EC

{:__('collect %s',Classement Billets EC)}
AI
1

Utilisez l'IA pour identifier et classer automatiquement les tickets de demande des clients de commerce électronique, améliorant l'efficacité et la précision du traitement.

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Act as a data analysis assistant for an e-commerce customer service system. Read the current list of pending customer inquiry tickets, automatically categorize them into four major categories based on the nature of the issue: logistics inquiry, product quality, return/exchange application, or complaint/suggestion. Extract key entities such as order numbers, product SKUs, and user sentiment tendencies, and finally output structured classification results for subsequent manual review or automatic routing.

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Agissez en tant qu'assistant d'analyse de données pour un système de service client de commerce électronique. Lisez la liste actuelle des tickets de demande des clients en attente, catégorisez-les automatiquement en quatre grandes catégories en fonction de la nature du problème : demande logistique, qualité du produit, demande de retour/échange ou plainte/suggestion. Extrayez les entités clés telles que les numéros de commande, les SKU des produits et les tendances d'émotion des utilisateurs, et enfin, produisez des résultats de classification structurés pour un examen manuel ou un routage automatique ultérieurs.

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Recommandation

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Analyze the following customer service message from an e-commerce platform and determine its business category. The possible categories are: Logistics Inquiry, Return/Exchange Request, Product Quality Issue, Price Dispute, or Other Inquiry. Output only the category name without any explanation or additional text. If the message cannot be clearly classified, output 'Other Inquiry'.
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Please analyze the following e-commerce customer service ticket content and classify it into one of four categories: 'Logistics Inquiry', 'Return/Exchange Request', 'Product Quality Complaint', or 'Other Inquiry' based on predefined business rules. If the ticket involves multiple issues, prioritize the most urgent or core issue category. Ensure the classification result is accurate and aligns with actual business scenarios to enable the customer service team to respond quickly.
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Please analyze the following e-commerce customer inquiry ticket content, automatically classify it into one of four categories: 'Logistics Inquiry', 'Return/Exchange Request', 'Product Quality Complaint', or 'Other Inquiry' based on business semantics, and briefly explain the classification basis to enable the customer service team to respond and handle it quickly.
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Analyze the provided customer inquiry text and categorize it into one of four predefined classes: pre-sales consultation, after-sales service, logistics inquiry, or complaint/suggestion based on business semantics. If an order number is mentioned, extract it; if emotional expression is present, label the sentiment as positive, neutral, or negative. The output must include the classification result, key entity extraction, and sentiment label, ensuring the logic aligns with standard e-commerce customer service protocols without additional explanatory reasoning.
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Act as an intelligent customer service assistant for an e-commerce platform. Receive raw user inquiry text, analyze its core intent and emotional tone, and categorize it into standard classes such as pre-sales consultation, after-sales rights protection, logistics inquiry, or complaint suggestion. Extract key entities like order numbers, product names, and problem descriptions, and finally output structured classification results and handling suggestions for quick human agent intervention.
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