步驟一：資料收集 (Data Collection)
中文範例：
請幫我分析這份產品評論：「這個app更新後變得超級慢，根本沒法用。」 請提取以下資訊： 1. 產品類型 2. 用戶情緒 3. 問題類別 4. 嚴重程度 用JSON格式回答。
English Example:
Analyze this product review: "This app became super slow after the update, it's basically unusable." Extract: 1. Product type 2. User emotion 3. Issue category 4. Severity level Respond in JSON format.
步驟二：內容生成 (Content Generation)
中文範例：
基於步驟一的分析結果：
{
"product_type": "mobile_app",
"emotion": "frustrated",
"issue": "performance",
"severity": "high"
}
請為客服團隊撰寫回應模板，要求：
- 語氣友善專業
- 承認問題
- 提供解決方案
- 字數100字內English Example:
Based on step 1 analysis:
{
"product_type": "mobile_app",
"emotion": "frustrated",
"issue": "performance",
"severity": "high"
}
Write a customer service response template:
- Friendly and professional tone
- Acknowledge the issue
- Provide solutions
- Under 100 words步驟三：品質檢查 (Quality Check)
中文範例：
請檢查以下客服回應的品質： 「感謝您的反饋。我們已經注意到更新後的性能問題，正在緊急修復中。建議您暫時重啟app或清除快取。預計24小時內推出修復版本。」 評估標準： 1. 語氣是否適當 (1-5分) 2. 是否提供解決方案 (是/否) 3. 改進建議 用結構化格式回答。
English Example:
Review this customer service response quality: "Thank you for your feedback. We've noticed the performance issues after the update and are working on an urgent fix. Please try restarting the app or clearing cache. We expect to release a fix within 24 hours." Evaluate: 1. Tone appropriateness (1-5 scale) 2. Solution provided (Yes/No) 3. Improvement suggestions Respond in structured format.
請點擊上方的一個步驟來查看詳細資訊。