option
Maison Liste de prompts IA AI Classification Billets Support

Classification Billets Support

{:__('collect %s',Classification Billets Support)}
AI
3

Utiliser le traitement du langage naturel pour analyser les billets de support e-commerce, identifier automatiquement les types de problèmes et les acheminer vers les départements concernés, améliorant l'efficacité de réponse et la satisfaction client.

Contenu du prompt Copier Copier

Analyze the following e-commerce support ticket content, identify its core issue type, including logistics delay, product damage, refund request, or inquiry, and route it to the logistics, quality inspection, or finance department based on preset rules. Extract key entities such as order number, product name, and user sentiment, and finally output a structured classification result and suggested handling plan to ensure accurate classification and compliance with business standards.

Copier Copier

Analysez le contenu du billet de support e-commerce suivant, identifiez son type de problème central, y compris le retard logistique, les dommages au produit, la demande de remboursement ou la demande de renseignement, et acheminez-le vers le service logistique, le service de contrôle qualité ou le service financier selon des règles prédéfinies. Extrayez les entités clés telles que le numéro de commande, le nom du produit et la tendance émotionnelle de l'utilisateur, et produisez enfin un résultat de classification structuré et un plan de traitement suggéré pour garantir une classification précise et la conformité aux normes commerciales.

Copier Copier
commentaires (0)
0/300

Recommandation

Classificateur de tickets e-commerce
Act as an intelligent customer service system for an e-commerce platform. Receive raw user inquiry or complaint text, analyze its core intent, and classify it into specific business scenarios such as logistics inquiry, product quality issue, return or exchange request, or price dispute. Output a standardized classification label along with a brief handling suggestion to ensure the customer service team can respond quickly and accurately.
Classification Billets EC
Please analyze the following e-commerce customer inquiry ticket content, automatically categorize it into one of the four categories: 'Logistics Inquiry', 'Return/Exchange Application', 'Product Quality Complaint', or 'Other Inquiry' based on business semantics, and briefly explain the basis for classification, ensuring that the classification results conform to actual business scenarios and are logically clear.
Classificateur de Tickets E-commerce
Act as an e-commerce support specialist to analyze the provided customer ticket text, identifying whether the core issue falls under logistics delay, product damage, return/exchange request, or price dispute. Extract key entities such as order ID, product name, and user sentiment, then output a structured classification result with suggested handling priority, ensuring accuracy and compliance with company service standards.
Réponse Client E-com
Act as a senior e-commerce customer service expert. Based on the provided product knowledge base and the customer's inquiry, generate a professional, friendly, and accurate response. The reply should directly address the customer's issue, avoid robotic clichés, ensure a natural and fluent tone consistent with the brand voice, and include necessary after-sales guidance.
Classification Billets E-com
Analyze the following raw customer inquiry text from an e-commerce platform and categorize it into one of four categories: 'Logistics Inquiry', 'Return/Exchange Request', 'Product Quality Complaint', or 'Other Inquiry'. If the text involves multiple intents, prioritize the most urgent or core issue and briefly explain the reasoning. For instance, if a user mentions 'the shirt size is wrong and I want to exchange it', categorize it as 'Return/Exchange Request'. Output only the category and a short rationale without any conversational filler or explanatory prefixes.
Classificateur de Tickets E-commerce
Act as an intelligent customer service system for an e-commerce platform. Receive the raw text of a user's inquiry, analyze its core intent and emotional tone, and automatically classify it into standard categories such as pre-sales consultation, after-sales service, logistics inquiry, or complaints. Extract key entities like order numbers, product names, and issue descriptions, then output a structured ticket summary to facilitate quick intervention by human agents.
OR