/data-metrics-understanding
Use when analyzing Xiaohongshu account data, interpreting performance metrics, making data-driven content decisions, or explaining what each metric means for account growth
$ npx -y skills add vivy-yi/xiaohongshu-skills --skill data-metrics-understanding --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/data-metrics-understanding
Context preview
The summary Claude sees to decide when to auto-load this skill.
Use when analyzing Xiaohongshu account data, interpreting performance metrics, making data-driven content decisions, or explaining what each metric means for account growth
SKILL.md
data-metrics-understanding.SKILL.mdname: data-metrics-understanding
description: Use when analyzing Xiaohongshu account data, interpreting performance metrics, making data-driven content decisions, or explaining what each metric means for account growth
Data Metrics Understanding (数据指标理解)
Overview
Data metrics understanding is knowing what each Xiaohongshu performance metric means, how to calculate it, what benchmarks indicate good vs. bad performance, and how to use metrics to optimize content strategy.
When to Use
**Use when**:
- Analyzing account performance
- Interpreting content data
- Setting performance goals
- Diagnosing growth issues
- Creating performance reports
**Do NOT use when**:
- Needing data export tools (use qiangua-data)
- Analyzing competitor data (use competitor-analysis)
Core Pattern
**Before** (metrics confusion):
❌ "What does engagement rate mean?"
❌ "Is 5% good or bad?"
❌ Don't know which metrics matter
❌ Overwhelmed by data dashboard
**After** (metrics clarity):
✅ Know what each metric measures
✅ Understand good vs. bad benchmarks
✅ Focus on metrics that matter
✅ Use data to drive decisions
**7 Core Metrics**: 1. **Views/Exposure** - Content reach 2. **Engagement Rate** - (Likes+Comments+Shares)/Views 3. **Save Rate** - Saves/Views 4. **Follower Growth** - New followers per post 5. **Completion Rate** - Video/audio watched to end 6. **Click-Through Rate** - Profile visits from content 7. **Share Rate** - Shares/Views
Quick Reference
| Metric | Formula | Good Benchmark | What It Indicates | |--------|---------|----------------|------------------| | **Views** | Total impressions | 500+ for new accounts | Reach and discovery | | **Engagement Rate** | (L+C+S)/Views | 8-12% | Content resonance | | **Save Rate** | Saves/Views | 3-5% | Content value | | **Follower Growth** | New followers/post | 5-10+ per 1K views | Conversion effectiveness | | **Completion Rate** | Watched to end | 70%+ for videos | Content engagement | | **Share Rate** | Shares/Views | 1-3% | Shareability |
Implementation
Step 1: Track Essential Metrics
**Weekly tracking minimum**:
- Total views per post
- Likes, comments, shares per post
- New followers gained
- Follower loss (unfollows)
**Tools**:
- Xiaohongshu Creator Center (free)
- Export to Excel for analysis
Step 2: Calculate Engagement Rate
**Formula**:
Engagement Rate = (Likes + Comments + Shares) / Views
Example:
Views: 1,000
Likes: 100
Comments: 20
Shares: 10
Engagement Rate = (100+20+10)/1000 = 13%
**Benchmark**:
- Below 5%: Needs improvement
- 5-10%: Average/good
- Above 10%: Excellent
Step 3: Analyze Save Rate
**Saves = content value indicator**
**Formula**: Save Rate = Saves / Views
**Benchmark**:
- 1-3%: Average
- 3-5%: Good (content worth saving)
- 5%+: Excellent (highly valuable content)
**Use for**: Tutorial, guide, educational content optimization.
Step 4: Monitor Follower Growth
**Per-post growth**:
**Benchmark** (per 1K views):
- 0-2 followers: Poor conversion
- 3-7 followers: Average
- 8-15 followers: Good
- 15+ followers: Excellent
**Goal**: Increase growth rate over time.
Step 5: Compare to Benchmarks
**Industry averages** (varies by niche):
- Fashion/beauty: 10-15% engagement
- Food/lifestyle: 8-12% engagement
- Education/tips: 12-18% engagement
**Adjust for**: Account size, niche, content type.
Step 6: Identify Problem Metrics
**Red flags**:
- Engagement rate dropping over time
- Views high but saves low (not valuable)
- Follower loss > gain (churning audience)
- Completion rate <50% (content not engaging)
**Take action**: Use specific skills to address issues.
Common Mistakes
| Mistake | Fix | |---------|-----| | **Focusing only on views** | Engagement rate matters more | | **Ignoring save rate** | Saves = content value | | **Comparing to mega-accounts** | Use similar-sized accounts | | **Not tracking over time** | Trends matter more than snapshots | | **Analysis paralysis** | Focus on 3-5 key metrics |
Real-World Impact
**Data-driven accounts**: 3-5x faster growth **Ignoring metrics**: Stagnation, don't know what works
---
**Related Skills**:
- **REQUIRED**: data-analytics (complete analysis methodology)
- **REQUIRED**: qiangua-data (advanced metrics tools)
- content-performance-analysis (individual post analysis)
- traffic-analysis (where views come from)
Read more
name: data-metrics-understanding description: Use when analyzing Xiaohongshu account data, interpreting performance metrics, making data-driven content decisions, or explaining what each metric means for account growth
Data Metrics Understanding (数据指标理解)
Overview
Data metrics understanding is knowing what each Xiaohongshu performance metric means, how to calculate it, what benchmarks indicate good vs. bad performance, and how to use metrics to optimize content strategy.
When to Use
**Use when**:
- Analyzing account performance
- Interpreting content data
- Setting performance goals
- Diagnosing growth issues
- Creating performance reports
**Do NOT use when**:
- Needing data export tools (use qiangua-data)
- Analyzing competitor data (use competitor-analysis)
Core Pattern
**Before** (metrics confusion):
❌ "What does engagement rate mean?" ❌ "Is 5% good or bad?" ❌ Don't know which metrics matter ❌ Overwhelmed by data dashboard
**After** (metrics clarity):
✅ Know what each metric measures ✅ Understand good vs. bad benchmarks ✅ Focus on metrics that matter ✅ Use data to drive decisions
**7 Core Metrics**: 1. **Views/Exposure** - Content reach 2. **Engagement Rate** - (Likes+Comments+Shares)/Views 3. **Save Rate** - Saves/Views 4. **Follower Growth** - New followers per post 5. **Completion Rate** - Video/audio watched to end 6. **Click-Through Rate** - Profile visits from content 7. **Share Rate** - Shares/Views
Quick Reference
| Metric | Formula | Good Benchmark | What It Indicates | |--------|---------|----------------|------------------| | **Views** | Total impressions | 500+ for new accounts | Reach and discovery | | **Engagement Rate** | (L+C+S)/Views | 8-12% | Content resonance | | **Save Rate** | Saves/Views | 3-5% | Content value | | **Follower Growth** | New followers/post | 5-10+ per 1K views | Conversion effectiveness | | **Completion Rate** | Watched to end | 70%+ for videos | Content engagement | | **Share Rate** | Shares/Views | 1-3% | Shareability |
Implementation
Step 1: Track Essential Metrics
**Weekly tracking minimum**:
- Total views per post
- Likes, comments, shares per post
- New followers gained
- Follower loss (unfollows)
**Tools**:
- Xiaohongshu Creator Center (free)
- Export to Excel for analysis
Step 2: Calculate Engagement Rate
**Formula**:
Engagement Rate = (Likes + Comments + Shares) / Views Example: Views: 1,000 Likes: 100 Comments: 20 Shares: 10 Engagement Rate = (100+20+10)/1000 = 13%
**Benchmark**:
- Below 5%: Needs improvement
- 5-10%: Average/good
- Above 10%: Excellent
Step 3: Analyze Save Rate
**Saves = content value indicator**
**Formula**: Save Rate = Saves / Views
**Benchmark**:
- 1-3%: Average
- 3-5%: Good (content worth saving)
- 5%+: Excellent (highly valuable content)
**Use for**: Tutorial, guide, educational content optimization.
Step 4: Monitor Follower Growth
**Per-post growth**:
**Benchmark** (per 1K views):
- 0-2 followers: Poor conversion
- 3-7 followers: Average
- 8-15 followers: Good
- 15+ followers: Excellent
**Goal**: Increase growth rate over time.
Step 5: Compare to Benchmarks
**Industry averages** (varies by niche):
- Fashion/beauty: 10-15% engagement
- Food/lifestyle: 8-12% engagement
- Education/tips: 12-18% engagement
**Adjust for**: Account size, niche, content type.
Step 6: Identify Problem Metrics
**Red flags**:
- Engagement rate dropping over time
- Views high but saves low (not valuable)
- Follower loss > gain (churning audience)
- Completion rate <50% (content not engaging)
**Take action**: Use specific skills to address issues.
Common Mistakes
| Mistake | Fix | |---------|-----| | **Focusing only on views** | Engagement rate matters more | | **Ignoring save rate** | Saves = content value | | **Comparing to mega-accounts** | Use similar-sized accounts | | **Not tracking over time** | Trends matter more than snapshots | | **Analysis paralysis** | Focus on 3-5 key metrics |
Real-World Impact
**Data-driven accounts**: 3-5x faster growth **Ignoring metrics**: Stagnation, don't know what works
---
**Related Skills**:
- **REQUIRED**: data-analytics (complete analysis methodology)
- **REQUIRED**: qiangua-data (advanced metrics tools)
- content-performance-analysis (individual post analysis)
- traffic-analysis (where views come from)
版本: v3.0 Complete Edition 更新: 2025-01-22 状态: ✅ 完整 (139个技能)
Other skills on xiaohongshu-skills.
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Open skill - /content-planning
Use when planning Xiaohongshu content calendar, running out of content ideas, needing systematic approach to content creation, or wanting to align content with account goals
Open skill - /content-portfolio
内容作品集管理 - 系统化整理、展示和优化你的内容资产
Open skill - /content-repurposing
Use when repurposing Xiaohongshu content, recycling existing posts, adapting content for different formats, maximizing content value, or creating content variations from core material
Open skill - /content-scaling
内容规模化生产 - 从单打独斗到系统化内容工厂的高效方法论
Open skill

