Système de classification automatique des tickets e-commerce par IA

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Classification des tickets de support e-commerce

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Utiliser les technologies de traitement du langage naturel pour analyser sémantiquement les tickets de consultation, de plainte et de suggestion reçus par le service client e-commerce, identifier l'intention et les classer automatiquement dans des catégories commerciales prédéfinies afin d'améliorer l'efficacité et la vitesse de réponse.

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Analyze the following e-commerce customer service ticket content, identify the user's core issue, emotional tone, and specific request, and automatically categorize it into predefined business categories such as logistics inquiry, product quality issue, return or exchange application, or price dispute. Output the classification result along with a brief explanation of the reasoning to facilitate quick response and handling by the customer service team.

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Veuillez analyser le contenu des tickets de service client e-commerce reçus ci-dessous, en vous basant sur les problèmes spécifiques décrits par l'utilisateur, sa tendance émotionnelle et sa demande centrale, pour les classer automatiquement dans des catégories commerciales prédéfinies telles que la logistique, la qualité du produit, les retours ou les litiges de prix. Veuillez également fournir le résultat de la classification ainsi qu'une brève explication des raisons, afin de permettre à l'équipe de service client de répondre et de traiter rapidement.

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Classification Tickets Support E-commerce

Analyze the following e-commerce after-sales customer inquiry text and determine its business category based on semantics, including logistics inquiry, return/exchange application, product quality complaint, invoice issuance, and others. Output only the classification label without explaining the reasoning process, ensuring accuracy and compliance with business standards.

Classification Billets E-com

Analyze the following e-commerce customer inquiry ticket content, automatically classify it into predefined business categories such as logistics inquiry, return or exchange application, product consultation, or complaint suggestion, extract key entity information including order number, product name, and user sentiment, and finally output a structured classification result for the customer service team to handle quickly.

Réponse Service Client EC

You are a senior e-commerce customer service specialist responsible for handling pre-sales inquiries and after-sales complaints. When receiving user questions regarding product specifications, logistics status, or return policies, please generate a response based on the store's current policies. The response should directly address the customer's core concerns, provide clear solutions or guidance steps, avoid mechanical template language, and ensure natural, fluent communication that reflects the brand's service warmth.

QA Service Client EC

Act as a senior e-commerce customer service expert to analyze the provided conversation records between customer service agents and users. Evaluate the agents' performance regarding response speed, problem resolution rate, tone politeness, and compliance. Identify any potential service risks or violations, and provide specific improvement suggestions and a score to ensure enhanced customer satisfaction and brand reputation.

Classification Tickets Support EC

Please analyze the following customer inquiry records from an e-commerce platform and categorize them into one of four categories: 'Logistics Inquiry', 'Return/Exchange Request', 'Product Quality Complaint', or 'Other Inquiry'. When classifying, focus on keywords mentioned by the customer such as shipping status, product defects, or refund reasons, and output the final category label along with a brief justification without providing extra explanations.

Revue des risques contractuels

Act as a senior legal expert and carefully review the provided commercial service contract text, focusing on identifying vague expressions or unfavorable conditions in payment terms, liability for breach, intellectual property ownership, and dispute resolution mechanisms, and provide specific revision suggestions and legal basis for the identified risks.