EC 고객 지원 자동 분류기

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EC 고객 지원 티켓 분류

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자연어 처리 기술을 사용하여 EC 고객 지원 문의 및 불만을 자동으로 식별하고 분류합니다.

프롬프트 내용

복사

Analyze the following customer service message received by an e-commerce platform and determine its business category. The categories include: Logistics Inquiry, Return/Exchange Request, Product Quality Complaint, Price Dispute, Account Issue, and Others. Output only the category name without explanation. For instance, if the user says 'My package hasn't moved for three days', classify it as Logistics Inquiry; if the user says 'The clothes faded after washing', classify it as Product Quality Complaint. Accurately categorize the input text.

복사

다음 EC 고객 지원에서 받은 사용자 메시지를 분석하고 비즈니스 카테고리를 결정하십시오. 카테고리에는 물류 문의, 반품/교환 신청, 제품 품질 불만, 가격 분쟁, 계정 문제 및 기타가 포함됩니다. 설명 없이 카테고리 이름만 출력하십시오. 예를 들어, 사용자가 '소포가 3일 동안 움직이지 않았다'고 말하면 물류 문의로 분류하고, 사용자가 '세탁 후 색이 바래졌다'고 말하면 제품 품질 불만으로 분류하십시오. 입력 텍스트를 정확하게 분류하십시오.

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전자상거래 고객 지원 티켓 분류

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이커머스 티켓 분류기

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EC CS 응답

Act as a senior e-commerce customer service expert. Draft a response to a customer complaining about a minor scratch on their received item, who is visibly upset. Your reply must start with a sincere apology acknowledging the issue, then offer two specific solutions (e.g., partial refund or free replacement) for the customer to choose from. Conclude with gratitude and a commitment to improvement. Maintain a professional, gentle, yet firm tone, avoiding robotic phrases, ensuring the customer feels valued and respected to effectively resolve the conflict and protect the brand image.

EC 고객 서비스 응답

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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.