AI 기반 EC 고객 지원 티켓 자동 분류 시스템

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EC 고객 지원 티켓 분류

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자연어 처리 기술을 활용하여 EC 고객 지원 센터가 받는 사용자 문의 및 불만 사항을 자동으로 식별하고 분류하여 응답 효율성과 서비스 품질을 향상시킵니다.

프롬프트 내용

복사

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.

복사

다음 EC 고객 지원 센터에서 받은 사용자 메시지를 분석하고, 반품/교환 문의, 물류 조회, 제품 품질 불만, 계정 문제 등의 비즈니스 카테고리에 따라 해당 카테고리를 판단한 후, 해당 카테고리 라벨과 간단한 처리 제안을 출력하십시오. 분류의 정확성과 고객 서비스 기준 준수를 보장합니다.

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이커머스 티켓 분류기

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.'

이커머스 티켓 분류기

EC 티켓 분류

Act as a data analysis assistant for an e-commerce customer service system. Read the current list of pending customer inquiry tickets, automatically categorize them into four major categories based on the nature of the issue: logistics inquiry, product quality, return/exchange application, or complaint/suggestion. Extract key entities such as order numbers, product SKUs, and user sentiment tendencies, and finally output structured classification results for subsequent manual review or automatic routing.

EC 티켓 분류기

Act as an intelligent customer service assistant for an e-commerce platform. Receive the raw text of a user's inquiry, analyze its core intent and urgency, and categorize it into one of four types: pre-sales consultation, after-sales rights protection, logistics inquiry, or complaint/suggestion. Extract key entities such as order numbers, product names, and problem descriptions. Finally, output a structured classification result and handling suggestions, ensuring the response is accurate and complies with corporate customer service standards.

이커머스 티켓 분류기

Please 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 predefined business rules. If the ticket involves multiple issues, prioritize the most urgent or core issue category. Ensure the classification result is accurate and aligns with actual business scenarios to enable the customer service team to respond quickly.

이커머스 티켓 분류

Please analyze the following e-commerce customer inquiry ticket content, automatically classify it into one of four categories: 'Logistics Inquiry', 'Return/Exchange Request', 'Product Quality Complaint', or 'Other Inquiry' based on business semantics, and briefly explain the classification basis to enable the customer service team to respond and handle it quickly.