vivy-yi/xiaohongshu-skills/xinhong-data

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Use when conducting deep analytics on Xiaohongshu accounts, tracking content performance trends, researching influencer data, monitoring category growth, or making strategic decisions with comprehensive social media analytics

Install

npx vskill@latest install vivy-yi/xiaohongshu-skills/xinhong-data

SKILL.md

Xinhong Data (新红数据)

Overview

Xinhong Data is a professional analytics platform specifically designed for Xiaohongshu, providing deep insights into account growth, content performance, influencer partnerships, industry trends, and competitive intelligence with granular data visualization and reporting capabilities for brands, agencies, and serious creators.

When to Use

Use when:

  • Conducting comprehensive account audits
  • Analyzing long-term growth trends
  • Researching influencer partnerships deeply
  • Monitoring industry and category trends
  • Evaluating content strategy effectiveness
  • Preparing detailed performance reports
  • Making data-driven strategic decisions

Do NOT use when:

  • Just starting with minimal data
  • Need quick daily checks (use basic analytics)
  • Want simple metrics (use built-in tools)
  • Cannot interpret complex data

Core Pattern

Before (surface-level analytics):

❌ "Basic metrics only (likes, followers)"
❌ "No trend analysis over time"
❌ "Shallow competitor insights"
❌ "Guessing content strategy"
❌ "Blind to industry shifts"

After (deep data intelligence):

✅ "Complete account health dashboard"
✅ "Trend analysis with actionable insights"
✅ "Deep competitor benchmarking"
✅ "Data-driven content optimization"
✅ "Industry trend forecasting"

5 Analytics Dimensions:

  1. Account Growth Analysis - Comprehensive growth tracking
  2. Content Performance Deep Dive - Detailed content metrics
  3. Audience Insights - Demographics and behavior
  4. Competitor Benchmarking - Strategic comparison
  5. Industry Trend Analysis - Market intelligence

Quick Reference

Analysis TypeData DepthUpdate FrequencyBest For
Account AuditComprehensiveMonthlyStrategy reviews
Content AnalysisPost-levelReal-timeContent optimization
Audience StudyDemographicWeeklyTargeting refinement
Competitor IntelComparativeBi-weeklyStrategic planning
Trend ForecastIndustry-wideMonthlyOpportunity spotting

Implementation

Step 1: Conduct Account Audits

Comprehensive Performance Review:

Account Audit Framework:
1. Growth Trajectory Analysis
Long-Term Performance Tracking:
Growth Metrics (90-Day View):
Follower Growth:
- Starting count (Day 1)
- Ending count (Day 90)
- Net growth
- Growth rate percentage
- Daily average growth
- Growth velocity (accelerating/decelerating)
Growth Velocity:
- Week 1-4: Growth rate
- Week 5-8: Growth rate
- Week 9-12: Growth rate
- Trend identification (acceleration/stagnation)
Benchmarking:
- vs. Previous period (MoM, YoY)
- vs. Category average
- vs. Competitors (similar size)
- Percentile ranking
Audit Example:
"Account Growth Audit (Q1 2026):
90-Day Period: Jan 1 - Mar 31
Follower Metrics:
- Starting: 8,500
- Ending: 12,750
- Net growth: +4,250
- Growth rate: +50% (excellent)
- Daily average: +47.2 followers/day
Velocity Analysis:
January: +1,200 (14% growth)
February: +1,550 (18% growth from Jan)
March: +1,500 (13% growth from Feb)
Trend: Accelerating through Feb, stabilizing in Mar
Benchmarking:
- Category average: 8% quarterly growth
- Your performance: 50% (6.25x category!)
- Competitor avg (similar size): 12%
- Your percentile: Top 5% in category
Growth Drivers Identified:
- Educational carousels (40% of growth)
- Live stream appearances (30% of growth)
- Influencer shoutouts (20% of growth)
- Viral content (10% of growth)
Recommendations:
- Double down on educational content (primary driver)
- Increase live stream frequency (high ROI)
- Nurture influencer relationships (sustainable growth)
- Test more viral content formats"
2. Engagement Quality Assessment
Beyond Surface Metrics:
Engagement Breakdown:
Component Analysis:
- Likes: Passive engagement baseline
- Comments: Active engagement indicator
- Saves: Value indicator (future reference)
- Shares: Viral potential measure
- Follows from post: Conversion metric
Quality Metrics:
Comment Quality:
- Avg comment length (characters)
- Question vs. statement ratio
- @mentions (conversation depth)
- Emoji usage (sentiment expression)
- Thread depth (reply chains)
Sentiment Analysis:
- Positive sentiment (%)
- Negative sentiment (%)
- Neutral sentiment (%)
- Brand mentions sentiment
- Product feedback sentiment
Engagement Health Report:
"Engagement Quality Audit (March 2026):
Overall Engagement Rate: 8.2% (above 5% category avg)
Component Breakdown:
- Likes: 68% of total engagement
- Comments: 15% (high! good conversation)
- Saves: 14% (excellent! content valued)
- Shares: 3% (opportunity to improve)
Comment Quality Analysis:
Sample: 500 comments analyzed
Avg length: 18 characters (substantial)
Questions: 35% (high engagement!)
@mentions: 12% (community interaction)
Emoji usage: 45% (expressive)
Thread depth: 2.3 avg replies (good discussion)
Sentiment Breakdown:
- Positive: 78% (excellent)
- Neutral: 19%
- Negative: 3% (low, manageable)
Top Engagement Drivers:
1. Educational carousels: 12% engagement, 25% saves
2. Before/after posts: 10% engagement, 18% shares
3. Personal stories: 9% engagement, 22% comments
4. Tutorials: 8.5% engagement, 15% saves
5. Product demos: 7% engagement, 10% comments
Underperforming:
1. Generic quotes: 4% engagement, 3% saves
2. Pure promotion: 4.5% engagement, 2% shares
3. Reposted content: 5% engagement, 4% saves
Insights:
- Audience values education (high saves, comments)
- Authenticity resonates (personal stories perform)
- Visual proof matters (before/after)
- Promotion needs value first (pure promo fails)
- Community is interactive (questions, threads)
Action Plan:
1. Increase educational content to 50% of calendar
2. Add more personal storytelling elements
3. Create visual transformation content regularly
4. Reduce generic quote posts by 80%
5. Always add value to promotional content"
3. Content Portfolio Analysis
Categorize and Evaluate All Content:
Content Classification:
By Type:
- Educational (how-to, guides, tips)
- Inspirational (quotes, motivation)
- Promotional (product, sales)
- Entertainment (humor, trends)
- Personal (stories, behind-the-scenes)
- User-generated (testimonials, reposts)
By Format:
- Single image
- Carousel (multiple slides)
- Video (short-form, long-form)
- Live stream recording
- Stories/short clips
By Topic:
- Product-specific
- Ingredient education
- Routine building
- Problem-solving
- Industry news
- Trend response
Performance Matrix:
"Content Portfolio Analysis (Last 100 Posts):
By Type Performance:
┌─────────────────────┬──────┬─────────┬────────┬──────────┐
│ Type │ Count│ Avg Eng │ Saves │ Shares │
├─────────────────────┼──────┼─────────┼────────┼──────────┤
│ Educational │ 40 │ 10.2% │ 22% │ 8% │
│ Promotional │ 25 │ 5.1% │ 9% │ 3% │
│ Personal │ 15 │ 9.5% │ 18% │ 10% │
│ Inspirational │ 12 │ 4.8% │ 6% │ 5% │
│ Entertainment │ 5 │ 6.2% │ 12% │ 15% │
│ UGC/Testimonials │ 3 │ 11.5% │ 28% │ 12% │
└─────────────────────┴──────┴─────────┴────────┴──────────┘
By Format Performance:
┌─────────────┬──────┬─────────┬────────┬──────────┐
│ Format │ Count│ Avg Eng │ Saves │ Shares │
├─────────────┼──────┼─────────┼────────┼──────────┤
│ Carousel │ 45 │ 10.8% │ 25% │ 7% │
│ Video │ 20 │ 8.5% │ 15% │ 12% │
│ Single Image│ 30 │ 5.2% │ 8% │ 4% │
│ Live Stream │ 5 │ 9.8% │ 18% │ 6% │
└─────────────┴──────┴─────────┴────────┴──────────┘
Optimal Mix Identified:
- 50% Educational carousels (10.2% eng, 25% saves)
- 20% Personal videos (9.5% eng, 10% shares)
- 15% UGC/testimonials (11.5% eng, 28% saves!)
- 10% Live stream highlights (9.8% eng)
- 5% Entertainment/viral (6.2% eng, 15% shares)
Eliminate (underperforming):
- Inspirational quotes (4.8% eng, low value)
- Pure promotional (5.1% eng, low saves)
- Single image posts (5.2% eng, low engagement)
Portfolio Optimization:
Current mix misaligned with performance
Shift to high-performing formats
Expected engagement increase: +35%"
4. Posting Pattern Analysis
Optimize Schedule and Frequency:
Timing Analysis:
Day of Week:
- Monday engagement rate
- Tuesday engagement rate
- Wednesday engagement rate
- Thursday engagement rate
- Friday engagement rate
- Saturday engagement rate
- Sunday engagement rate
Time of Day:
- Morning (7-9 AM)
- Lunch (12-1 PM)
- Afternoon (2-4 PM)
- Evening (7-10 PM)
- Late night (10 PM-12 AM)
Frequency Analysis:
Current: 5 posts/week
Test: 7 posts/week
Impact: Diminishing returns after 6/week
Schedule Audit:
"Posting Schedule Analysis (Q1 2026):
Day-of-Week Performance:
┌───────────┬──────────┬─────────┬────────┐
│ Day │ Posts │ Avg Eng │ Rank │
├───────────┼──────────┼─────────┼────────┤
│ Monday │ 15 │ 6.8% │ 5 │
│ Tuesday │ 18 │ 9.2% │ 1 ✓ │
│ Wednesday │ 17 │ 8.5% │ 2 │
│ Thursday │ 16 │ 8.1% │ 3 │
│ Friday │ 15 │ 7.5% │ 4 │
│ Saturday │ 10 │ 5.8% │ 6 │
│ Sunday │ 9 │ 6.2% │ 7 │
└───────────┴──────────┴─────────┴────────┘
Time-of-Day Performance:
┌─────────────┬──────────┬─────────┬────────┐
│ Time │ Posts │ Avg Eng │ Rank │
├─────────────┼──────────┼─────────┼────────┤
│ 7-9 AM │ 20 │ 5.2% │ 5 │
│ 12-1 PM │ 15 │ 7.8% │ 3 │
│ 2-4 PM │ 18 │ 6.5% │ 4 │
│ 7-9 PM │ 45 │ 9.5% │ 1 ✓ │
│ 9-11 PM │ 17 │ 8.8% │ 2 │
└─────────────┴──────────┴─────────┴────────┘
Frequency Analysis:
Current: 5 posts/week (100 posts in Q1)
Avg engagement: 7.5%
Test: 6 posts/week (24 posts in test month)
Avg engagement: 7.4% (slight decrease)
Reach: +12% (more content discovery)
Follower growth: +18% (vs +15% baseline)
Test: 7 posts/week (28 posts in test month)
Avg engagement: 6.8% (notable decrease)
Reach: +15% (but lower quality)
Follower growth: +16% (vs +15% baseline)
Optimal Schedule:
- Frequency: 6 posts/week (Mon-Sat)
- Best days: Tuesday, Wednesday, Thursday
- Best time: 8-9 PM (peak engagement)
- Rest day: Sunday (audience lower)
Expected improvement:
- Engagement: +15% (better timing)
- Reach: +12% (more posts)
- Growth: +20% (optimal frequency)"
5. Hashtag Strategy Review
Optimize Discoverability:
Hashtag Performance:
For each hashtag used:
- Total posts with tag (volume)
- Avg engagement rate
- Reach achieved
- Follower growth attributed
- Trend trajectory (rising/falling)
Mix Analysis:
Broad (1M+ posts):
- #skincare (10M+ posts)
- Engagement: 5.2%
- Reach: High, but competitive
Niche (10k-100k posts):
- #dryskincare (85k posts)
- Engagement: 9.8%
- Reach: Targeted, less competitive
Long-tail (<10k posts):
- #winterdryskincare (3.5k posts)
- Engagement: 12.5%
- Reach: Highly targeted
Hashtag Audit:
"Hashtag Performance Audit (Q1 2026):

This is the start of the file. Read the full SKILL.md on GitHub.

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Source

Popularity

Repository stars
164
Repository forks
43
7-day trend score
26

Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 21 Mar 2026, 7 months ago.

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