AI 기반 이커머스 지원 티켓 자동 라우팅

집

AI 프롬프트 목록

이커머스 고객 지원 티켓 분류

${:__('collect %s',이커머스 고객 지원 티켓 분류)}$

자연어 처리 기술을 사용하여 고객 지원 티켓을 분석하고, 문제를 자동으로 분류하여 해당 부서로 라우팅하여 응답 효율성과 고객 만족도를 향상시킵니다.

프롬프트 내용

복사

Analyze the following e-commerce support ticket text to identify the core issue type (such as logistics delay, product damage, refund dispute, or general inquiry), categorize it into the corresponding handling department based on predefined rules, extract key entities like order ID, product name, and user sentiment, and finally output a structured classification result with suggested handling solutions, ensuring accuracy and compliance with business standards.

복사

다음 이커머스 지원 티켓 텍스트를 분석하여 물류 지연, 제품 손상, 환불 분쟁 또는 일반 문의와 같은 핵심 문제 유형을 식별하고, 미리 정의된 규칙에 따라 해당 처리 부서에 분류하십시오. 또한 주문 ID, 제품 이름 및 사용자 감정 성향과 같은 주요 엔티티를 추출하고, 최종적으로 구조화된 분류 결과와 제안된 처리 솔루션을 출력하십시오. 분류의 정확성과 비즈니스 표준 준수를 보장합니다.

복사

공유 링크를 복사하려면 클릭

의견 (0)

0/300

제출하다

추천

EC 티켓 분류

Act as an intelligent customer service assistant for an e-commerce platform. Receive and analyze the user's raw inquiry text. Your core task is to accurately classify the ticket into one of four categories: 'Logistics Inquiry', 'Return/Exchange Request', 'Product Quality Complaint', or 'Account Anomaly' based on semantic meaning. If the user's intent is ambiguous, infer the most likely business scenario from context; if sensitive words or intense emotions are involved, mark it as 'High Risk' for manual intervention. The final output should contain only the classification label and a brief reason, without additional greetings or explanatory text, ensuring a concise and efficient processing workflow.

이커머스 고객 지원 티켓 분류

Analyze the following e-commerce customer service ticket content, identify the user's core issue, emotional tone, and specific request, and automatically categorize it into predefined business categories such as logistics inquiry, product quality issue, return or exchange application, or price dispute. Output the classification result along with a brief explanation of the reasoning to facilitate quick response and handling by the customer service team.

이커머스 티켓 분류기

Analyze the following e-commerce after-sales customer inquiry text and determine its business category based on semantics, including logistics inquiry, return/exchange application, product quality complaint, invoice issuance, and others. Output only the classification label without explaining the reasoning process, ensuring accuracy and compliance with business standards.

이커머스 티켓 분류

Analyze the following e-commerce customer inquiry ticket content, automatically classify it into predefined business categories such as logistics inquiry, return or exchange application, product consultation, or complaint suggestion, extract key entity information including order number, product name, and user sentiment, and finally output a structured classification result for the customer service team to handle quickly.

EC 고객 서비스 응답

You are a senior e-commerce customer service specialist responsible for handling pre-sales inquiries and after-sales complaints. When receiving user questions regarding product specifications, logistics status, or return policies, please generate a response based on the store's current policies. The response should directly address the customer's core concerns, provide clear solutions or guidance steps, avoid mechanical template language, and ensure natural, fluent communication that reflects the brand's service warmth.

EC 고객 서비스 QA

Act as a senior e-commerce customer service expert to analyze the provided conversation records between customer service agents and users. Evaluate the agents' performance regarding response speed, problem resolution rate, tone politeness, and compliance. Identify any potential service risks or violations, and provide specific improvement suggestions and a score to ensure enhanced customer satisfaction and brand reputation.