EC 고객 서비스 스마트 응답

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EC 고객 서비스 응답

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주문 데이터를 기반으로 고객 만족도를 향상시키는 지능형 고객 서비스 응답을 생성합니다.

프롬프트 내용

복사

Act as a senior e-commerce customer service expert. Based on the customer inquiry: 'My order #12345 shows shipped but logistics info hasn't updated for three days, I'm anxious,' and considering the order status is 'In Transit,' estimated delivery is '2023-10-15,' and current logistics node is 'East China Distribution Center,' generate a professional, reassuring, and solution-oriented reply. The response must include an apology for the delay, an explanation of the current logistics status, a specific estimated time for the next update, and proactively offer a compensation plan if delivery is not met, maintaining a friendly yet professional tone without using robotic template language.

복사

시니어 EC 고객 서비스 전문가로 행동하십시오. 고객의 문의: '주문 #12345은 발송된 것으로 표시되지만 물류 정보가 3일 동안 업데이트되지 않아 걱정됩니다'를 기반으로, 주문 상태가 '수송 중', 배달 예정일이 '2023-10-15', 현재 물류 노드가 '화동转运中心'임을 고려하여 전문적이고 안심시키며 해결책을 제공하는 응답을 생성하십시오. 응답에는 지연에 대한 사과, 현재 물류 상태의 설명, 다음 업데이트의 구체적인 예상 시간, 및 배달 기한이 지났을 경우의 보상 계획 제안을 포함하며, 기계적인 템플릿 언어를 사용하지 않고 친근하면서도 전문적인 어조를 유지하십시오.

복사

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의견 (0)

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EC 티켓 분류기

Please analyze the following customer message received by an e-commerce support team and determine its business category. The categories include: Logistics Inquiry, Return/Exchange Request, Product Quality Complaint, Price Dispute, and General Consultation. Read the user's input carefully, extract key information such as order numbers, product names, and problem descriptions, and then classify the message into one of the five predefined categories based on established standards. If the message involves multiple issues, select the most urgent or core issue for classification. Finally, output the result in JSON format, including the original message, the predicted category, and a confidence score, ensuring the classification is accurate and meets actual business needs.

이커머스 CS 답변

Act as a senior e-commerce customer service expert. Based on the user-provided order ID, product name, and current logistics status, generate a friendly, professional, and efficient reply text. The reply must include an apology for the logistics delay, a specific estimated delivery time, and a compensation plan (such as coupons or points). Ensure the language is natural and fluent, avoiding mechanical template feelings, with the goal of alleviating user anxiety and promoting repurchase.

이커머스 고객 지원 티켓 분류

Analyze the following e-commerce customer service ticket content and classify it into one of four categories: 'Logistics Inquiry', 'Return/Exchange Request', 'Product Quality Complaint', or 'Other Inquiry' based on user intent, providing a brief explanation for the classification.

이커머스 티켓 분류기

Act as an intelligent customer service system for an e-commerce platform. You will receive raw user inquiry texts and must analyze their core intent to classify them into one of five predefined standard categories: Logistics Inquiry, Return/Exchange Request, Product Consultation, Complaint/Suggestion, or Account Issue. Carefully review the input, extract key entities such as order numbers, product names, or specific pain points, and ignore irrelevant pleasantries. Finally, output only a standardized JSON result containing the original text, the identified intent label, and a confidence score, ensuring accurate classification to support subsequent automated processing workflows.

EC 고객 서비스 자동 응답

Act as a senior ecommerce customer service expert. Generate a professional, friendly, and accurate response based on the provided customer inquiry and product knowledge base. The reply must directly address the customer's issue, avoid mechanical template language, and maintain brand tone consistency to ensure the customer feels valued and understood.

이커머스 CS 답변

Act as a senior e-commerce customer service expert. Based on the provided product details (including name, price, specifications, stock status, and key selling points) and the user's specific inquiry, generate a natural, friendly, and professional reply text. The reply should directly address the user's concerns, accurately cite key product information, avoid mechanical template language or overly complex jargon, and ensure the tone aligns with brand standards to facilitate conversion.