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EC 티켓 분류
AI
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AI를 사용하여 EC 고객 문의 티켓을 자동으로 식별하고 분류하여 응답 효율성과 서비스 품질을 향상시킵니다.
프롬프트 내용
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복사
Analyze the following customer inquiry text from an e-commerce platform and determine its business category based on semantics, including return/exchange requests, logistics queries, product inquiries, or complaints/suggestions. Output only the classification label without explanation or additional notes to ensure accurate categorization for subsequent automated processing.
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EC 플랫폼에서 온 고객 문의 텍스트를 분석하고 의미에 따라 반품/교환 요청, 물류 쿼리, 제품 문의 또는 불만/제안의 비즈니스 카테고리 중 하나를 결정하십시오. 후속 자동화 처리 프로세스를 보장하기 위해 설명이나 추가 메모 없이 분류 라벨만 출력하십시오.
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추천
EC 티켓 분류
Please analyze the following raw customer inquiry text submitted via e-commerce channels and classify it into one of four categories: 'Logistics Inquiry', 'Return/Exchange Request', 'Product Quality Complaint', or 'Other'. When making the judgment, focus on keywords such as tracking numbers, damaged goods, size mismatches, or shipping delays mentioned by the customer, ignoring emotional expressions, and directly output the most matching category label along with a brief rationale, ensuring the classification result aligns with common handling processes in actual business scenarios.
EC 고객 서비스 답변
Act as a senior e-commerce customer service expert. Based on the user's provided order number, product name, and current logistics status, generate a professional and empathetic reply. If logistics are stalled, proactively provide inquiry channels and apologize; if delivered, guide the user to confirm receipt and invite a review. The reply must be concise, avoid robotic clichés, ensure a warm tone that addresses actual pain points, and output only the final reply text.
이커머스 티켓 분류기
Act as an intelligent customer service assistant for an e-commerce platform. Analyze the text of user-submitted inquiries to identify their core intent, such as return requests, logistics tracking, or product complaints. Classify each ticket into the appropriate department based on predefined business rules, and extract key entities like order numbers, product names, and specific issue descriptions to facilitate rapid follow-up by human agents.
이커머스 티켓 분류기
Act as an intelligent customer service assistant for an e-commerce platform. Receive raw user consultation or complaint text, analyze its core intent, and categorize it into specific business categories such as logistics inquiry, product quality issue, return or exchange application, or price dispute. Extract key entities like order numbers, product names, and user sentiment. Finally, output the classification results and brief handling suggestions in a structured format, ensuring accuracy and compliance with customer service standards.
전자상거래 티켓 분류
Act as an intelligent customer service assistant for an e-commerce platform. Read the provided raw text of customer inquiries, analyze their core demands and emotional tone, and accurately classify them into one of the following categories: logistics inquiry, return or exchange application, product consultation, or complaint and suggestion. Extract key entities such as order numbers or product names, and finally generate a concise structured summary to facilitate quick follow-up by human customer service agents.
이커머스 티켓 분류
Analyze the following e-commerce support ticket text to identify its core issue type (e.g., delayed shipping, damaged goods, refund dispute, pre-sales inquiry) and categorize it into the corresponding handling department (Logistics, Quality Control, Finance, or Pre-sales) based on predefined rules. If the ticket contains multiple issues, prioritize the most urgent or impactful one, and output the classification result along with a brief rationale.
