AI活用ECカスタマーサポートチケット振り分け

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ECサポートチケット分類

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自然言語処理を活用し、顧客サポートチケットを分析して意図を特定し、物流、品質、返金部門へルーティングすることで、対応効率と精度を向上させます。

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コピー

Analyze the following e-commerce customer support ticket text to identify the core issue and determine its business category. The content involves common scenarios such as damaged goods, delayed shipping, or refund requests. Extract key entities like order numbers, product names, and problem descriptions. Map the ticket to the most appropriate category based on predefined standards including logistics issues, product quality, after-sales service, and others. If the user expresses strong emotions or uses sensitive language, flag it as high priority. The final output should include the classification result, confidence score, and brief handling suggestions, ensuring clear logic that aligns with actual business operations to help the customer service team quickly triage and prioritize urgent cases.

コピー

以下のECカスタマーサポートチケットテキストを分析し、核心的な問題を特定してビジネスカテゴリを判断してください。内容には、商品破損、配送遅延、返金リクエストなどの一般的なシナリオが含まれます。注文番号、商品名、問題説明などの主要なエンティティを抽出します。物流問題、製品品質、アフターサービス、その他などの事前定義された基準に基づき、最も適切なカテゴリにチケットをマッピングしてください。ユーザーが強い感情を表したり、機密性の高い言語を使用したりする場合は、高優先度としてフラグを立ててください。最終出力には、分類結果、信頼度スコア、および簡潔な処理提案を含め、実際の業務運用と一致する明確な論理を保証し、カスタマーサービスチームが迅速に仕分けし、緊急案件を優先处理できるようにします。

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