Analyze Feedback

作者 amplitude96fc7d4c58bb无许可证42 个星标收录于 2026年10月8日更新于 2026年10月8日仓库今天更新

Synthesizes customer feedback into actionable themes including feature requests, bugs, pain points, and praise. Use when planning product roadmap, understanding user sentiment, investigating specific issues, or preparing voice-of-customer reports.

AI 生成的概览

借助 Amplitude 反馈工具,将客户反馈归纳为主题、情绪与优先级建议。

功能
引导智能体查看已接入的客户反馈来源,按类型和日期提取主题洞察,并深入查看每个主题背后的具体反馈内容。它还会将主题与用户群组(如使用时长、套餐类型、使用频率)关联。最终产出结构化的客户之声报告,涵盖紧急问题、功能请求、好评、情绪评分和优先级建议。
适用场景
适用于规划产品路线图、调查具体问题或功能请求、了解客户情绪,或准备客户之声汇报时。
运行要求
需要访问 Amplitude 反馈与群组工具(use_amplitude_ai_feedback、use_amplitude_cohorts)以及已接入的反馈渠道。不包含脚本,仅为操作说明。

Analyze Feedback

Perform comprehensive feedback reviews, investigate specific feature requests, understand customer sentiment, then prepare concise but actionable voice-of-customer presentations

Instructions

Step 1: Understand Available Sources

Use Amplitude:use_amplitude_ai_feedback with facet: "sources" to see which feedback channels are connected (surveys, support, app reviews, etc.).

Step 2: Get Themed Insights

Use Amplitude:use_amplitude_ai_feedback with facet: "insights" and appropriate filters:

  • Filter by types: request, complaint, lovedFeature, bug, painPoint
  • Filter by date range for recent feedback
  • Filter by source for channel-specific analysis

Step 3: Drill Into Specific Themes

For top insights, use Amplitude:use_amplitude_ai_feedback with facet: "mentions" to see the actual user feedback driving each theme.

Step 4: Connect to User Segments

Use Amplitude:use_amplitude_cohorts with action: "list" to understand if feedback themes correlate with:

  • User tenure (new vs. established)
  • Plan type (free vs. paid)
  • Usage level (power users vs. casual)

Step 5: Present Findings

Structure as:

  1. Summary: Concise one-liner explaining the number of feedback sources and mentions analyzed along with the key takeaways from the analysis.
  2. Urgent Issues 🚩: Top bugs, issues, or pain-points noted by customers. Share 3-4 themes here unless prompted otherwise.
  3. Top Feature Requests 💡: Top feature requests noted by customers. Share 3-4 themes here unless prompted otherwise.
  4. Praises ❤️: Top praises or loved features noted by customers. Share 1-2 themes here unless prompted otherwise.
  5. Sentiment Analysis: Share a very concise overview of the themes, sentiment on a scale from 1-5 (5 being highest), and snippets of evidence.
  6. Prioritized Recommendations: Very concise section recapping the top 3-7 specific actionable recommendations (unless prompted otherwise) to follow-up on. Inlcude [p0],[p1],[p2],[p3] in front of each title to help size priority with p0 being most urgent and p3 being least.

Best Practices

  • Be comprehensive in your investigation and analysis but concise and actionable in your response.
  • Do not repeat duplicate sections or the same takeaway multiple times.
  • Include 1-2 representative quotes for each theme. Prioritize the best quotes that explains the theme. Include when it was received and what source it came from. If the quote is long, only quote the relevant section tied to the theme.
  • When describing a theme, include the mention volumes, key sources, and recency in a concise manner.
  • Each theme should have consistent formatting like: Concise But Descriptive Theme Name (X mentions) Actionable one-line description or multiple concise bullet-points explaining what the specific issue or request or praise is, what time period the feedback was relevant for, and key sources the theme came from
    • "Customer quote backing the theme" - Source name (Received date)
    • "Customer quote backing the theme" - Source name (Received date)
  • For the Prioritized Recommendations section, each recommendation should just be 1 concise but actionable bullet-point instead of a long theme overview.
  • Do not recap what you did at the very end and just end after the concise prioritized recommendations.
  • Connect feedback to behavioral data when possible.

来源与署名

来源:amplitude/mcp-marketplace位于plugins/amplitude/skills/analyze-feedback提交96fc7d4

许可证: 无许可证

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