AIによるECサポートチケット自動分類

家

AIプロンプト一覧

ECサポートチケット分類

${:__('collect %s',ECサポートチケット分類)}$

自然言語処理技術を用いて、ECプラットフォームのユーザーが提出したアフターサービス相談と苦情チケットを分析し、問題タイプを自動で識別して対応部署に振り分け、カスタマーサービスの応答効率とユーザー満足度を向上させます。

プロンプト内容

コピー

Analyze the following e-commerce support ticket content, identify its core issue type, including logistics delay, product damage, refund request, or inquiry, and route it to the logistics, quality inspection, or finance department based on preset rules. Extract key entities such as order number, product name, and user sentiment, and finally output a structured classification result and suggested handling plan to ensure accurate classification and compliance with business standards.

コピー

以下のECアフターサービスチケットの内容を分析し、物流遅延、商品破損、返金申請、または問い合わせという核心問題タイプを特定してください。事前に設定されたルールに基づき、物流部、品質検査部、または財務部に振り分けてください。同時に、注文番号、商品名、ユーザーの感情傾向などの主要なエンティティを抽出し、最終的に構造化された分類結果と推奨処理方案を出力してください。分類の正確性と業務規範への準拠を確保します。

コピー

共有リンクをコピーするにはクリック

コメント (0)

0/300

送信

おすすめ

ECサポートチケット分類

Act as an intelligent customer service system for an e-commerce platform. Receive raw user inquiry or complaint text, analyze its core intent, and classify it into specific business scenarios such as logistics inquiry, product quality issue, return or exchange request, or price dispute. Output a standardized classification label along with a brief handling suggestion to ensure the customer service team can respond quickly and accurately.

ECチケット分類

Please analyze the following e-commerce customer inquiry ticket content, automatically categorize it into one of the four categories: 'Logistics Inquiry', 'Return/Exchange Application', 'Product Quality Complaint', or 'Other Inquiry' based on business semantics, and briefly explain the basis for classification, ensuring that the classification results conform to actual business scenarios and are logically clear.

ECサポートチケット分類

Act as an e-commerce support specialist to analyze the provided customer ticket text, identifying whether the core issue falls under logistics delay, product damage, return/exchange request, or price dispute. Extract key entities such as order ID, product name, and user sentiment, then output a structured classification result with suggested handling priority, ensuring accuracy and compliance with company service standards.

ECカスタマー返信

Act as a senior e-commerce customer service expert. Based on the provided product knowledge base and the customer's inquiry, generate a professional, friendly, and accurate response. The reply should directly address the customer's issue, avoid robotic clichés, ensure a natural and fluent tone consistent with the brand voice, and include necessary after-sales guidance.

ECチケット分類

Analyze the following raw customer inquiry text from an e-commerce platform and categorize it into one of four categories: 'Logistics Inquiry', 'Return/Exchange Request', 'Product Quality Complaint', or 'Other Inquiry'. If the text involves multiple intents, prioritize the most urgent or core issue and briefly explain the reasoning. For instance, if a user mentions 'the shirt size is wrong and I want to exchange it', categorize it as 'Return/Exchange Request'. Output only the category and a short rationale without any conversational filler or explanatory prefixes.

ECサポートチケット分類

Act as an intelligent customer service system for an e-commerce platform. Receive the raw text of a user's inquiry, analyze its core intent and emotional tone, and automatically classify it into standard categories 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 ticket summary to facilitate quick intervention by human agents.