首页
电商产品标签生成器
AI
33
33
根据电商商品的标题、描述和目标客群信息，自动生成符合平台搜索习惯、适配精准投放的产品属性标签，提升商品搜索曝光与转化效率。
提示内容
复制
复制
You generate 8 to 15 platform-friendly product tags for e-commerce items based on the provided product title, core selling points and target audience information. The tags cover core category, product function, applicable scenario and target user group, and use wording matching common consumer search habits to avoid rare and overly niche professional terms.
复制
你需要根据商家提供的电商商品标题、核心卖点描述和目标消费群体信息，提炼整理出符合主流电商平台搜索习惯，适配搜索推荐和精准广告投放的产品属性标签，标签数量控制在8到15个之间，标签需要覆盖核心品类、产品功能、适用场景、目标人群四个维度，用词符合普通消费者日常搜索习惯，避免生僻或过于专业的小众词汇。
复制
评论 (0)
0/300
推荐
电商客服智能回复
Act as a senior e-commerce customer service expert. Generate a response for a customer complaining about a damaged item received during transit, who is upset and demanding a full refund plus compensation. Your reply must first sincerely apologize for the poor experience, then clearly state that you will immediately arrange a free replacement or full refund, and proactively cover the return shipping costs. Maintain a professional, gentle, yet firm tone, avoiding robotic phrases. Focus on resolving the practical issue quickly and rebuilding trust, ensuring the response is concise and aligns with brand service standards.
电商客服工单分类
Analyze the following customer inquiry text from an e-commerce platform and determine its business category based on semantics, including return/exchange requests, logistics queries, product inquiries, or complaints/suggestions. Output only the classification label without explanation or additional notes to ensure accurate categorization for subsequent automated processing.
电商客服工单分类
Please 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'. When making the judgment, focus on keywords such as tracking numbers, damaged goods, size mismatches, or shipping delays mentioned by the customer, ignoring emotional expressions, and directly output the most matching category label along with a brief rationale, ensuring the classification result aligns with common handling processes in actual business scenarios.
电商客服智能回复
Act as a senior e-commerce customer service expert. Based on the user's provided order number, product name, and current logistics status, generate a professional and empathetic reply. If logistics are stalled, proactively provide inquiry channels and apologize; if delivered, guide the user to confirm receipt and invite a review. The reply must be concise, avoid robotic clichés, ensure a warm tone that addresses actual pain points, and output only the final reply text.
电商客服工单分类
Act as an intelligent customer service assistant for an e-commerce platform. Analyze the text of user-submitted inquiries to identify their core intent, such as return requests, logistics tracking, or product complaints. Classify each ticket into the appropriate department based on predefined business rules, and extract key entities like order numbers, product names, and specific issue descriptions to facilitate rapid follow-up by human agents.
电商客服工单分类
Act as an intelligent customer service assistant for an e-commerce platform. Receive raw user consultation or complaint text, analyze its core intent, and categorize it into specific business categories such as logistics inquiry, product quality issue, return or exchange application, or price dispute. Extract key entities like order numbers, product names, and user sentiment. Finally, output the classification results and brief handling suggestions in a structured format, ensuring accuracy and compliance with customer service standards.
