Automatischer E-Commerce-Support-Ticket-Klassifizierer

Heim

KI-Prompt-Liste

E-Commerce-Ticket-Klassifizierer

${:__('collect %s',E-Commerce-Ticket-Klassifizierer)}$

Ein KI-Tool, das Kundendiensttickets automatisch in spezifische Geschäftsbereiche kategorisiert.

Prompt-Inhalt

Kopieren

Analyze the following customer service message received by an e-commerce platform and determine its business category. The possible categories are: Logistics Inquiry, Return/Exchange Request, Product Quality Complaint, Price Dispute, Account Issue, and Other. Output only the category name without any explanation. The customer message is: 'The item I received three days ago has damaged packaging and is missing accessories. I request a replacement or a refund.'

Kopieren

Analysieren Sie die folgende vom E-Commerce-Plattform empfangene Kundenbotschaft und bestimmen Sie ihre Geschäftskategorie. Die möglichen Kategorien sind: Logistikanfrage, Rückgabe/Umtausch-Anfrage, Produktqualitätsbeschwerde, Preisstreitigkeit, Konto-Probleme und Sonstiges. Geben Sie nur den Kategoriennamen ohne jegliche Erklärung aus. Die Kundenbotschaft lautet: 'Der Artikel, den ich vor drei Tagen erhalten habe, hat eine beschädigte Verpackung und fehlt Zubehör. Ich fordere einen Ersatz oder eine Rückerstattung.'

Kopieren

Teilen Klicken Sie, um den Link zu kopieren

Kommentare (0)

0/300

Einreichen

Empfehlung

E-Commerce-Ticket-Klassifizierer

Analyze the following e-commerce customer inquiry text, determine its business category based on semantics such as logistics query, return or exchange application, product consultation, or complaint suggestion, and output a standardized classification label along with brief handling suggestions, ensuring accurate classification that complies with corporate customer service standards.

EC-Kundenservice-Antwort

Act as a senior e-commerce customer service expert. Based on the provided order number, current logistics status, and the user's emotional tone, generate a professional yet empathetic response. The reply must include a sincere apology for the logistics delay, an updated estimated delivery time, and a small coupon as compensation. Maintain a gentle but firm tone to defuse dissatisfaction and rebuild trust, avoiding robotic template language to ensure the response is natural, fluent, and consistent with brand values.

E-Commerce-Ticket-Klassifizierer

Act as an intelligent customer service assistant for an e-commerce platform. Receive the raw text of a user's inquiry, analyze its core intent and emotional tone, and categorize it into standard classes such as pre-sales consultation, after-sales complaint, logistics inquiry, or return/exchange application. Extract key entities like order numbers, product names, and problem descriptions, and finally output a structured classification result with handling suggestions to enable manual agents to intervene quickly.

EC-Ticket-Klassifizierung

Please analyze the following e-commerce customer service ticket content, classify it into one of four categories: 'Logistics Inquiry', 'Return/Exchange Request', 'Product Quality Complaint', or 'Other Inquiry' based on business semantics, and briefly explain the reasoning. If the ticket involves multiple intents, prioritize the most urgent or core issue. The output format must include the classification label and a short reason, ensuring the result is accurate and aligns with actual business scenarios.

E-Commerce-Ticket-Klassifizierung

Analyze the provided e-commerce customer consultation text to identify the core request and determine its business category. If the user mentions damaged, missing, or malfunctioning items, categorize it as an after-sales issue. If it involves delayed shipping, logistics updates, or lost packages, categorize it as a logistics issue. If it asks about product specifications, usage tutorials, or compatibility, categorize it as a product inquiry. Ignore emotional expressions and extract key facts for precise classification, outputting the corresponding standard business label.

E-Commerce-Support-Ticket-Klassifizierung

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.