자동 이커머스 티켓 분류 시스템

집

AI 프롬프트 목록

이커머스 티켓 분류기

${:__('collect %s',이커머스 티켓 분류기)}$

NLP 기술을 사용하여 이커머스 고객 서비스 티켓을 자동으로 식별 및 분류하여 응답 효율성과 정확도를 향상시킵니다.

프롬프트 내용

복사

Act as an intelligent customer service system for an e-commerce platform. Receive raw user inquiry text, analyze its core intent and emotional tone, and accurately classify it into specific business categories such as pre-sales consultation, after-sales complaint, logistics inquiry, or return/exchange application. Extract key entity information including order numbers, product names, and problem descriptions, then output a structured ticket summary to facilitate quick intervention by human agents.

복사

이커머스 플랫폼의 지능형 고객 서비스 시스템으로 행동하십시오. 사용자의 원본 문의 텍스트를 받고, 핵심 의도와 감정적 어조를 분석하여 판매 전 상담, 사후 불만, 물류 문의 또는 반품/교환 신청과 같은 구체적인 비즈니스 카테고리로 정확하게 분류하십시오. 주문 번호, 제품 이름 및 문제 설명을 포함한 주요 엔티티 정보를 추출한 후, 인간 에이전트의 신속한 개입을 용이하게 하기 위해 구조화된 티켓 요약을 출력하십시오.

복사

공유 링크를 복사하려면 클릭

의견 (0)

0/300

제출하다

추천

고객 지원 티켓 분류

Analyze the following e-commerce after-sales ticket text to identify its problem category, including logistics issues, product quality issues, after-sales service attitude, or refund disputes. Extract key entities such as order numbers, product names, user requests, and sentiment tendencies. Finally, output a structured classification result and suggested handling priority to enable the customer service team to respond quickly.

EC 티켓 분류

Please analyze the following user customer service conversation records from an e-commerce platform, determine the business category based on the content such as logistics inquiry, return or exchange application, product quality complaint, or account anomaly, extract key information like order number, problem description, and user sentiment, and finally output a structured ticket classification result for subsequent manual or automated processing.

EC 티켓 분류

Please analyze the content of the following user customer service tickets from an e-commerce platform, determine which category their core request belongs to based on the conversation context (logistics inquiry, return/exchange application, product quality complaint, or price consultation), and output the corresponding category label along with a brief reason.

고객 지원 티켓 분류

Analyze the following e-commerce support ticket content, identify its core issue type, including logistics delay, product damage, refund request, or inquiry, and route it to the logistics, quality inspection, or finance department based on preset rules. Extract key entities such as order number, product name, and user sentiment, and finally output a structured classification result and suggested handling plan to ensure accurate classification and compliance with business standards.

이커머스 티켓 분류기

Act as an intelligent customer service system for an e-commerce platform. Receive raw user inquiry or complaint text, analyze its core intent, and classify it into specific business scenarios such as logistics inquiry, product quality issue, return or exchange request, or price dispute. Output a standardized classification label along with a brief handling suggestion to ensure the customer service team can respond quickly and accurately.

EC 티켓 분류

Please analyze the following e-commerce customer inquiry ticket content, automatically categorize it into one of the four categories: 'Logistics Inquiry', 'Return/Exchange Application', 'Product Quality Complaint', or 'Other Inquiry' based on business semantics, and briefly explain the basis for classification, ensuring that the classification results conform to actual business scenarios and are logically clear.