Промпт для оценки качества обслуживания в электронной коммерции

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QA Клиентский Сервис

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Промпт для автоматической оценки разговоров службы поддержки электронной коммерции, выявления нарушений и оптимизации процессов.

Содержание промпта

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Act as a senior e-commerce customer service expert to analyze the provided conversation logs between agents and users. Focus on checking if the agent accurately understood the user's intent, adhered to company service standards, and avoided emotional or evasive behavior. Evaluate the effectiveness of the final solution. Identify key risk points (such as complaint escalation or sensitive word usage) and excellent service highlights, then provide specific improvement suggestions and a score to ensure the response is professional, objective, and actionable.

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Выступайте в качестве старшего эксперта по обслуживанию клиентов в электронной коммерции, чтобы проанализировать предоставленные журналы разговоров между агентами и пользователями. Сосредоточьтесь на проверке того, правильно ли агент понял намерение пользователя, соблюдал ли он стандарты обслуживания компании и избегал ли эмоционального или уклончивого поведения. Оцените эффективность окончательного решения, определите ключевые точки риска (такие как эскалация жалоб или использование чувствительных терминов) и сильные стороны обслуживания, а затем предоставьте конкретные предложения по улучшению и оценку, чтобы обеспечить профессиональный, объективный и практичный ответ.

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Рекомендация

Классификатор тикетов 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.

Ответ Клиенту E-com

Act as a senior e-commerce customer service expert. Based on the provided customer inquiry and product knowledge base, generate a professional, friendly, and accurate response. The reply must directly address the customer's specific questions regarding order status, return policies, or product specifications. Avoid mechanical template language, ensure the tone is natural and fluent while matching the brand voice, and strictly adhere to company compliance requirements without making unfulfillable promises.

Классификация тикетов E-commerce

Analyze the provided customer support ticket text from an e-commerce platform and determine its primary intent. Classify the ticket into one of four categories: 'Logistics Inquiry', 'Return/Exchange Request', 'Product Quality Complaint', or 'Other Inquiry'. If multiple issues are present, prioritize the most urgent or the last mentioned issue. Output only the category label without any additional explanation.

Классификация тикетов поддержки

Analyze the following customer message received by e-commerce support, determine its business category based on semantics such as return/exchange inquiry, logistics query, product quality complaint, or account issue, and output the corresponding category label along with a brief handling suggestion, ensuring accurate classification that aligns with customer service standards.

Классификатор тикетов E-commerce

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 Complaint, Price Dispute, Account Issue, and Other. Output only the category name without any explanation. The customer message is: 'The package I received three days ago shows as delivered, but I have not received any physical item. The logistics information is stuck at the transit center. Please verify this and expedite a reshipment or refund.'

Классификатор тикетов E-com