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Heim KI-Prompt-Liste AI E-Commerce-Ticket-Klassifizierung

E-Commerce-Ticket-Klassifizierung

{:__('collect %s',E-Commerce-Ticket-Klassifizierung)}
AI
34

Nutzung der natürlichen Sprachverarbeitung zur Analyse von E-Commerce-Kundentickets, Identifizierung der Absicht und Automatisierung der Kategorisierung und Priorisierung zur Verbesserung der Antworteffizienz und Servicequalität.

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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. Categorize the ticket into the corresponding service department based on predefined business rules. Simultaneously, assess the urgency of the ticket; if it involves safety complaints or potential negative public opinion risks, mark it as high priority and recommend immediate human intervention. For routine inquiries, generate standardized response suggestions for customer service agents. The final output should include the classification label, urgency rating, and key information summary to ensure the customer service team can quickly understand customer needs and respond accurately.

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Analysieren Sie den bereitgestellten Text des E-Commerce-Kundentickets, um seine Hauptabsicht zu identifizieren, wie z. B. eine Logistikabfrage, eine Rückgabe- oder Umtauschanfrage, eine Produktqualitätsbeschwerde oder eine Preiskonsultation. Kategorisieren Sie das Ticket basierend auf vordefinierten Geschäftsregeln in die entsprechende Serviceabteilung. Bewerten Sie gleichzeitig die Dringlichkeit des Tickets; wenn es sich um Sicherheitsbeschwerden oder potenzielle Risiken für negative öffentliche Meinungen handelt, markieren Sie es als hohe Priorität und empfehlen Sie sofortiges menschliches Eingreifen. Generieren Sie für routinemäßige Anfragen standardisierte Antwortvorschläge für Kundenservice-Mitarbeiter. Die endgültige Ausgabe sollte das Klassifizierungsetikett, den Dringlichkeitsgrad und eine Zusammenfassung der Schlüsselinformationen enthalten, um sicherzustellen, dass das Kundenserviceteam die Kundenbedürfnisse schnell verstehen und genau darauf reagieren kann.

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