Prompt d'évaluation de la qualité du service client e-commerce

Maison

Liste de prompts IA

QA Service Client EC

${:__('collect %s',QA Service Client EC)}$

Un prompt pour évaluer automatiquement la qualité des dialogues, identifier les violations et optimiser l'expérience de service dans les scénarios de service client e-commerce.

Contenu du prompt

Copier

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.

Copier

Agissez en tant qu'expert senior en service client e-commerce pour analyser les enregistrements de conversation fournis entre les agents du service client et les utilisateurs. Évaluez la performance des agents en matière de vitesse de réponse, de taux de résolution des problèmes, de politesse du ton et de conformité. Identifiez tout risque de service potentiel ou violation, et fournissez des suggestions d'amélioration spécifiques ainsi qu'un score pour garantir une satisfaction client et une réputation de marque améliorées.

Copier

Partager Cliquez pour copier le lien

commentaires (0)

0/300

Soumettre

Recommandation

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.

Classification des tickets de support

Analyze the following e-commerce after-sales ticket text to identify its problem category, including logistics issues, product quality issues, after-sales service attitude, or refund disputes. Extract key entities such as order numbers, product names, user requests, and sentiment tendencies. Finally, output a structured classification result and suggested handling priority to enable the customer service team to respond quickly.

Classification Tickets E-commerce

Act as an intelligent customer service system for an e-commerce platform. Receive raw user inquiry text, analyze its core intent and emotional tone, and accurately classify it into specific business categories such as pre-sales consultation, after-sales complaint, logistics inquiry, or return/exchange application. Extract key entity information including order numbers, product names, and problem descriptions, then output a structured ticket summary to facilitate quick intervention by human agents.

Classification Tickets E-com

Please analyze the following user customer service conversation records from an e-commerce platform, determine the business category based on the content such as logistics inquiry, return or exchange application, product quality complaint, or account anomaly, extract key information like order number, problem description, and user sentiment, and finally output a structured ticket classification result for subsequent manual or automated processing.

Classification Tickets EC

Please analyze the content of the following user customer service tickets from an e-commerce platform, determine which category their core request belongs to based on the conversation context (logistics inquiry, return/exchange application, product quality complaint, or price consultation), and output the corresponding category label along with a brief reason.