AI 기반 이커머스 지원 티켓 라우팅

집

AI 프롬프트 목록

이커머스 티켓 분류

${:__('collect %s',이커머스 티켓 분류)}$

자연어 처리를 활용하여 고객 지원 티켓을 분석하고 의도를 식별하여 물류, 품질, 환불 부서로 라우팅하여 응답 효율성과 정확성을 향상시킵니다.

프롬프트 내용

복사

Analyze the following e-commerce customer support ticket text to identify the core issue and determine its business category. The content involves common scenarios such as damaged goods, delayed shipping, or refund requests. Extract key entities like order numbers, product names, and problem descriptions. Map the ticket to the most appropriate category based on predefined standards including logistics issues, product quality, after-sales service, and others. If the user expresses strong emotions or uses sensitive language, flag it as high priority. The final output should include the classification result, confidence score, and brief handling suggestions, ensuring clear logic that aligns with actual business operations to help the customer service team quickly triage and prioritize urgent cases.

복사

다음 이커머스 고객 지원 티켓 텍스트를 분석하여 핵심 문제를 식별하고 비즈니스 카테고리를 결정하십시오. 내용에는 손상된 상품, 배송 지연, 환불 요청 등의 일반적인 시나리오가 포함됩니다. 주문 번호, 제품 이름 및 문제 설명과 같은 주요 엔티티를 추출하십시오. 물류 문제, 제품 품질, 애프터 서비스, 기타 등의 사전 정의된 기준에 따라 가장 적절한 카테고리로 티켓을 매핑하십시오. 사용자가 강한 감정을 표현하거나 민감한 언어를 사용하는 경우 높은 우선 순위로 플래그를 지정하십시오. 최종 출력에는 분류 결과, 신뢰도 점수 및 간략한 처리 제안이 포함되어 실제 비즈니스 운영과 일치하는 명확한 논리를 보장하여 고객 서비스 팀이 신속하게 분류하고 긴급 사례를 우선 처리할 수 있도록 합니다.

복사

공유 링크를 복사하려면 클릭

의견 (0)

0/300

제출하다

추천

이커머스 티켓 분류기

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 Inquiry'. If the text does not clearly indicate a specific business scenario, assign it to 'Other Inquiry'. Output only the category label name without explaining the reasoning process or providing additional suggestions.

이커머스 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 sentiment, and categorize it into specific business scenarios such as pre-sales consultation, after-sales complaint, logistics inquiry, or return/exchange application. Extract key entities like order numbers, product names, and problem descriptions, then output a structured ticket summary to facilitate quick handling by human agents.

이커머스 고객 지원 티켓 분류

Analyze the following e-commerce support ticket text to identify the user's core request and emotional tone, then automatically categorize it into specific business modules such as logistics delay, product quality issue, return/refund application, or general inquiry, while extracting key entities like order ID, product name, and problem description for subsequent manual agent intervention.

EC 고객 지원 티켓 분류

Please read the following customer service message submitted by the user, analyze its core request, and categorize it into one of the predefined ticket types: Logistics Inquiry, Return/Exchange Request, Product Quality Issue, Account Anomaly, or Other. Output only the classification label without explaining the reasoning process, ensuring accurate classification to assist subsequent manual handling.

EC 고객 서비스 QA

Act as a senior e-commerce customer service quality monitoring expert to analyze the provided customer-service dialogue records. Focus on checking if the customer service accurately understood the customer's needs, used standard polite language, effectively resolved complaints or inquiries, and avoided shirking responsibility or emotional responses. Identify key risk points in the dialogue, such as unfulfilled promises, incorrect information, or poor attitude, and provide specific improvement suggestions. The final output should include a dialogue quality score, a description of main issues, and an optimized reply example to ensure improved customer satisfaction and compliance.

EC 고객 서비스 답변

Act as a senior e-commerce customer service expert. Based on the provided order details and common after-sales issues, generate a professional, friendly, and efficient reply text. The reply must include confirmation of the order status, proactive answers to potential issues, and specific solution suggestions. Maintain a polite and empathetic tone, avoiding mechanical template language, ensuring the content is natural, fluent, and effectively resolves customer concerns.