вариант
Дом Список AI-промптов AI Классификатор тикетов электронной коммерции

Классификатор тикетов электронной коммерции

{:__('collect %s',Классификатор тикетов электронной коммерции)}
AI
31

Автоматически идентифицируйте и классифицируйте запросы и жалобы пользователей в службе поддержки электронной коммерции с помощью обработки естественного языка.

Содержание промпта Копировать Копировать

Analyze the following user message received by e-commerce customer service and determine its business category. The categories include: Logistics Inquiry, Return/Exchange Request, Product Quality Complaint, Price Dispute, Account Issue, and Others. Output only the classification result without explanation. For example, if the user says 'My package hasn't arrived after three days', classify it as Logistics Inquiry; if the user says 'The clothes shrank after washing', classify it as Product Quality Complaint. Accurately classify the input text.

Копировать Копировать

Проанализируйте следующее сообщение пользователя, полученное службой поддержки электронной коммерции, и определите его категорию бизнеса. Категории включают: Запрос о доставке, Запрос на возврат/обмен, Жалоба на качество продукта, Спор о цене, Проблема с аккаунтом и Другие. Выводите только результат классификации без объяснений. Например, если пользователь говорит 'Мой пакет не прибыл через три дня', классифицируйте его как Запрос о доставке; если пользователь говорит 'Одежда села после стирки', классифицируйте его как Жалоба на качество продукта. Точно классифицируйте входной текст.

Копировать Копировать
Комментарии (0)
0/300

Рекомендация

Классификация Тикетов
Act as an intelligent customer service assistant for an e-commerce platform. Read the provided raw text of customer inquiries, analyze their core demands and emotional tone, and accurately classify them into one of the following categories: logistics inquiry, return or exchange application, product consultation, or complaint and suggestion. Extract key entities such as order numbers or product names, and finally generate a concise structured summary to facilitate quick follow-up by human customer service agents.
Категоризация тикетов электронной коммерции
Analyze the following e-commerce support ticket text to identify its core issue type (e.g., delayed shipping, damaged goods, refund dispute, pre-sales inquiry) and categorize it into the corresponding handling department (Logistics, Quality Control, Finance, or Pre-sales) based on predefined rules. If the ticket contains multiple issues, prioritize the most urgent or impactful one, and output the classification result along with a brief rationale.
Классификатор тикетов E-commerce
Act as an intelligent customer service assistant for an e-commerce platform. Receive raw user inquiry text, analyze its core intent and sentiment, and categorize it into standard classes such as pre-sales consultation, after-sales service, logistics inquiry, or complaints. Extract key entities like order numbers, product names, and issue descriptions, then output a structured classification result with handling suggestions for quick human agent intervention.
Классификация тикетов электронной коммерции
Analyze the provided e-commerce customer ticket text to identify its core intent, such as logistics inquiry, return or exchange request, product quality complaint, or price consultation. Classify the ticket into the corresponding customer service queue based on predefined business rules. Simultaneously, assess the urgency of the ticket; if it involves safety complaints or significant public opinion risks, mark it as high priority and recommend immediate manual intervention. For routine inquiries, extract key entities (e.g., order number, product SKU, problem description) and generate a concise summary to help customer service agents quickly understand the context. The final output should include the classification label, priority level, list of key entities, and a summary of no more than 50 words, ensuring accuracy and facilitating subsequent processing.
Классификация тикетов
Act as part of an e-commerce customer service system. Analyze the incoming customer inquiry text and automatically categorize it into one of four categories: pre-sales consultation, after-sales service, logistics inquiry, or complaint/suggestion. Output the corresponding category label and confidence score to facilitate routing to the appropriate handling team.
Классификатор тикетов E-commerce
Analyze the provided e-commerce customer ticket text to identify its core intent, such as return inquiries, logistics queries, or quality complaints, and categorize it into the corresponding processing queue based on predefined business rules, while assessing urgency to assist human agents in prioritizing high-urgency issues.
OR