크로스보더 전자상거래 상품 검색 제목 최적화

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AI 프롬프트 목록

전자상거래 상품 제목 최적화 도구

${:__('collect %s',전자상거래 상품 제목 최적화 도구)}$

크로스보더 전자상거래 플랫폼의 기존 상품 제목을 플랫폼 검색 규칙과 사용자 검색 습관에 맞춰 최적화하여 검색 노출과 클릭률을 높입니다

프롬프트 내용

복사

Combine the search ranking rules of Amazon North America Station and common keywords North American consumers use to search for folding outdoor camping chairs, adjust the word order of the existing product title provided by the seller, add high-traffic long-tail keywords, keep the core product selling points and brand information, and output an optimized title that meets the character requirements.

복사

아마존 북미 스테이션의 검색 순위 규칙과 북미 소비자가 접이식 아웃도어 캠핑 의자를 검색할 때 자주 사용하는 키워드를 결합하여 판매자가 제공한 기존 상품 제목의 어순을 조정하고 높은 트래픽 롱테일 키워드를 추가하며 상품의 핵심 판매 포인트와 브랜드 정보를 유지하고 문자 요구 사항에 맞는 최적화된 제목을 출력해 주세요

복사

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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.

이커머스 티켓 분류기

Act as an e-commerce support specialist to analyze the provided customer ticket text, identifying whether the core issue falls under logistics delay, product damage, return/exchange request, or price dispute. Extract key entities such as order ID, product name, and user sentiment, then output a structured classification result with suggested handling priority, ensuring accuracy and compliance with company service standards.