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ECレビュー深度解析
レビュー・評価
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自然言語処理技術を用い、ECプラットフォームのユーザーネガティブレビューを多角的に分析し、核心の痛みポイントと感情傾向を特定し、実行可能な改善提案レポートを生成します。
プロンプト内容
コピー
コピー
Act as a senior e-commerce operations expert to deeply deconstruct the provided negative user review text. First, extract specific product attributes (e.g., quality, logistics, customer service) and sentiment polarity mentioned in the comment. Second, judge whether the review constitutes malicious brushing or a genuine experience based on industry常识, and identify potential legal risks or compliance issues. Finally, summarize the core complaint points in concise, professional language and provide three specific operational optimization suggestions, ensuring the response is logically coherent and free of templated phrasing.
コピー
シニアEC運用专家として振る舞い、提供されたユーザーのネガティブレビューテキストを深く分解してください。まず、コメントに含まれる具体的な製品属性（例：品質、物流、カスタマーサービス）と感情の極性を抽出します。次に、業界の常識に基づき、そのレビューが悪意あるブラッシングか実際の体験かを判断し、潜在的な法的リスクやコンプライアンス問題を特定します。最後に、中立的で専門的な言語で核心の苦情ポイントを要約し、3つの具体的な運用最適化提案を提供してください。回答は論理的に整合性があり、定型文の痕跡がないことを確保してください。
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