AI-система автоматической классификации тикетов электронной коммерции

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Классификация Тикетов

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Использование технологий обработки естественного языка для автоматической идентификации и классификации тикетов клиентов электронной коммерции, повышение эффективности и точности.

Содержание промпта

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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.

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Проанализируйте содержание следующих тикетов консультаций, отправленных клиентами электронной коммерции, автоматически классифицируйте их по заранее определенным бизнес-категориям, таким как логистические запросы, заявки на возврат или обмен, консультации по продуктам или жалобы, извлеките ключевую информацию об сущностях, такую как номер заказа, название продукта и эмоциональный тон пользователя, и в конечном итоге выведите структурированный результат классификации для быстрой обработки командой службы поддержки.

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Рекомендация

Ответы службы поддержки EC

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.

QA Клиентская Служба

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.

Классификация тикетов поддержки EC

Please analyze the following customer inquiry records from an e-commerce platform and categorize them into one of four categories: 'Logistics Inquiry', 'Return/Exchange Request', 'Product Quality Complaint', or 'Other Inquiry'. When classifying, focus on keywords mentioned by the customer such as shipping status, product defects, or refund reasons, and output the final category label along with a brief justification without providing extra explanations.

Обзор рисков договора

Act as a senior legal expert and carefully review the provided commercial service contract text, focusing on identifying vague expressions or unfavorable conditions in payment terms, liability for breach, intellectual property ownership, and dispute resolution mechanisms, and provide specific revision suggestions and legal basis for the identified risks.

Классификация тикетов поддержки

Analyze the following e-commerce after-sales ticket text to identify its problem category, including logistics issues, product quality issues, after-sales service attitude, or refund disputes. Extract key entities such as order numbers, product names, user requests, and sentiment tendencies. Finally, output a structured classification result and suggested handling priority to enable the customer service team to respond quickly.

Классификатор тикетов E-commerce

Act as an intelligent customer service system for an e-commerce platform. Receive raw user inquiry text, analyze its core intent and emotional tone, and accurately classify it into specific business categories such as pre-sales consultation, after-sales complaint, logistics inquiry, or return/exchange application. Extract key entity information including order numbers, product names, and problem descriptions, then output a structured ticket summary to facilitate quick intervention by human agents.