이커머스 부정적 답변 생성기

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검토/평가

이커머스 리뷰 복구

${:__('collect %s',이커머스 리뷰 복구)}$

검토/평가

이커머스 플랫폼의 부정적인 평가에 대해 전문적이고 공감적이며 해결 지향적인 답변을 생성하여 고객 만족도와 브랜드 이미지를 향상시킵니다.

프롬프트 내용

복사

Act as a senior e-commerce customer service expert. Draft a reply to the following user comment: 'Received the item with damaged packaging and scratches, slow shipping, very disappointed.' Your response must first sincerely apologize for the poor experience, acknowledging issues with logistics and packaging without shifting blame. Then, propose concrete remedial actions, such as immediately arranging a free replacement or full refund, and include an unconditional coupon to demonstrate sincerity. Maintain a gentle, professional, and empathetic tone, avoiding robotic customer service scripts, aiming to win back user trust through proactive problem-solving and demonstrating brand responsibility.

복사

당신은 시니어 이커머스 고객 서비스 전문가입니다. 다음 사용자 댓글에 대한 답변을 작성하십시오. 댓글 내용은: '상품을 받았는데 포장 파손과 흠집이 있고, 배송이 느려서 매우 실망했습니다.' 당신의 답변은 먼저 나쁜 경험에 대해 진심으로 사과하고, 물류와 포장의 문제를 인정해야 합니다. 책임을 전가하지 마십시오. 다음으로, 무료 신규 제품 재송 또는 전액 환불과 같은 구체적인 구제 조치를 제안하고, 성의를 보여주기 위해 무조건 쿠폰을 부여하십시오. 기계적인 고객 서비스의決定的인 문구를 피하고, 온화하고 전문적이며 공감적인 톤을 유지하며, 적극적인 문제 해결을 통해 사용자의 신뢰를 되찾고 브랜드의 책임감을 보여주는 것을 목표로 하십시오.

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Act as a senior e-commerce customer service expert to draft a response for the following specific negative customer review, which involves both product quality issues and shipping delays. Your task is to write a reply that first sincerely apologizes and acknowledges the customer's inconvenience, then briefly explains the cause without shifting blame, and finally offers a concrete compensation plan or follow-up measure. The tone must be professional, gentle, and solution-focused, avoiding robotic template language to ensure the response reflects the brand's human care and sense of responsibility.

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이커머스 리뷰 감정 분석

Please analyze the provided e-commerce platform user review data, identifying the sentiment polarity (positive, negative, or neutral) of each review, and extracting specific product features or issues mentioned. For negative reviews, further summarize the main reasons for complaints; for positive reviews, summarize the core factors for user satisfaction. Finally, output a structured sentiment analysis report containing sentiment distribution statistics, high-frequency keyword clouds, and specific suggestions for product improvement. Ensure the analysis results are objective, accurate, and actionable, helping the operations team optimize product descriptions and service processes.