Routage intelligent des tickets de support e-commerce par IA

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Classification des tickets de support e-commerce

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Utiliser le traitement du langage naturel pour analyser les tickets de support client, catégoriser automatiquement les problèmes par type et les acheminer vers le département approprié, améliorant ainsi l'efficacité de réponse et la satisfaction client.

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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.

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Analysez le contenu du ticket de support e-commerce suivant pour identifier son type de problème principal (tel que le retard logistique, les dommages au produit, le litige de remboursement ou l'enquête générale) et catégorisez-le dans le département de traitement correspondant selon des règles de classification prédéfinies. De plus, extrayez les informations clés sur les entités (telles que l'ID de commande, le nom du produit et le sentiment de l'utilisateur) pour générer un résumé de ticket concis permettant une intervention rapide d'un agent humain.

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Recommandation

Réponse CS E-commerce

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.

Classificateur de tickets E-commerce

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.

Réponse CS E-commerce

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.

Classification Tickets E-com

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.

Classificateur de tickets e-commerce

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.

Service Client E-commerce

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.