选项
首页 AI 提示词列表 AI 电商客服工单分类

电商客服工单分类

{:__('collect %s',电商客服工单分类)}
AI
0

利用自然语言处理技术,对电商平台用户提交的售后咨询与投诉工单进行语义分析,自动识别问题类型并分配至对应处理部门,提升响应效率与用户满意度。

提示内容 复制 复制

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.

复制 复制

请分析以下电商售后工单文本,识别其核心问题类型(如物流延误、商品破损、退款争议、咨询解答等),并根据预设的分类规则将其归类到相应的处理部门,同时提取关键实体信息如订单号、商品名称及用户情绪倾向,最终输出结构化的分类结果与建议处理方案,确保分类准确且符合业务规范。

复制 复制
评论 (0)
0/300

推荐

电商客服工单分类
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.
电商客服工单分类
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.
电商客服工单分类
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.
电商客服工单分类
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.
电商客服智能回复
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.
电商客服质检
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.
OR