Loading...
Loading...
Use when analyzing Xiaohongshu account performance, tracking content metrics, researching competitors, or making data-driven decisions to optimize content strategy
npx skill4agent add vivy-yi/xiaohongshu-skills huitun-data❌ "Guessing what content works"
❌ "No competitor insights"
❌ "Posting at random times"
❌ "Unsure why posts succeed/fail"
❌ "Wasting resources on poor performers"✅ "Know exactly what content resonates"
✅ "Competitor strategy revealed"
✅ "Optimal posting times identified"
✅ "Clear reasons for performance"
✅ "Resources focused on winners"| Analysis Type | Key Metrics | Frequency | Use For |
|---|---|---|---|
| Account Overview | Followers, engagement rate, growth | Weekly | Health check |
| Content Performance | Likes, saves, shares, comments | Per post | Content optimization |
| Competitor Analysis | Growth, top content, strategy | Monthly | Benchmarking |
| Trend Research | Hot topics, rising hashtags | Weekly | Content ideation |
| Influencer Search | Engagement, audience, cost | Per campaign | Partner selection |
Account Health Dashboard:
1. Follower Growth Analysis
Understand Audience Expansion:
Key Metrics:
- Total followers (current count)
- Growth rate (% change over time)
- Daily new followers (average)
- Unfollow rate (churn)
- Net growth (gains - losses)
Growth Benchmarks:
- New accounts (0-1k): 5-10% monthly growth
- Growing accounts (1k-10k): 3-7% monthly growth
- Established accounts (10k-100k): 2-5% monthly growth
- Large accounts (100k+): 1-3% monthly growth
Analysis Framework:
"Week 1 Analysis:
- Starting followers: 5,200
- Ending followers: 5,450
- Net growth: +250 (4.8%)
- Daily average: +36 followers/day
- Unfollow rate: 1.2% (healthy)
- Conclusion: Above average growth, keep doing what's working"
Growth Drivers:
Identify which content caused growth spikes:
- Top performing posts (viral content)
- Influencer shoutouts (partnerships)
- Trending topics (timely content)
- Hashtag optimization (discoverability)
2. Engagement Rate Deep Dive
Measure Audience Connection:
Engagement Formula:
(Likes + Comments + Saves + Shares) / Followers × 100
Rate Benchmarks:
- Excellent: 10%+ (highly engaged audience)
- Good: 5-10% (healthy engagement)
- Average: 3-5% (room for improvement)
- Below Average: Under 3% (needs attention)
Component Analysis:
- Likes: Passive approval
- Comments: Active engagement
- Saves: Value indicator (future reference)
- Shares: Viral potential
Example Analysis:
"March 2026 Engagement:
Total Followers: 8,500
Post Performance:
- Avg likes: 420 (4.9%)
- Avg comments: 45 (0.5%)
- Avg saves: 85 (1.0%)
- Avg shares: 12 (0.1%)
Total engagement: 6.5% ✓ (Good)
Breakdown:
- Likes: 75% of engagement
- Comments: 8% of engagement
- Saves: 15% of engagement
- Shares: 2% of engagement
Insights:
- Strong save rate (content valuable)
- Low share rate (not very viral)
- Good comment rate (community active)
- Action: Test more shareable content"
3. Audience Demographics
Know Your Followers:
Demographic Data:
- Age distribution (key age groups)
- Gender split (male vs female)
- Geographic location (cities, provinces)
- Active times (when they're online)
- Interests (topics they engage with)
Age Analysis:
"18-24: 25% (students, young professionals)
25-34: 45% (prime target ✓)
35-44: 25% (secondary target)
45+: 5%
Target: Women 25-40
Match: 70% of audience ✓"
Location Insights:
"Top cities:
- Shanghai: 22%
- Beijing: 18%
- Guangzhou: 12%
- Shenzhen: 10%
- Hangzhou: 8%
Tier 1 cities: 70% (urban, affluent ✓)"
Active Times:
"Peak engagement:
- Tuesday: 8-9 PM (highest)
- Thursday: 7-9 PM (high)
- Sunday: 7-8 PM (moderate)
Low engagement:
- Monday morning (busy)
- Friday afternoon (weekend starts)
Action: Prioritize posting Tue/Thu evenings"
4. Content Performance Ranking
Identify Winners and Losers:
Top Performing Content:
- Sort by engagement rate
- Analyze common themes
- Identify format preferences
- Note hashtag effectiveness
Bottom Performing Content:
- Lowest engagement posts
- Understand why they failed
- Learn what to avoid
- Test improvements
Performance Categories:
"Top 10% (Superstars):
- Educational carousels
- Before/after transformations
- Personal stories
- Engagement rate: 12%+
Middle 60% (Consistent):
- Product showcases
- Tips and how-tos
- Lifestyle content
- Engagement rate: 5-8%
Bottom 30% (Underperformers):
- Purely promotional
- Generic quotes
- Off-topic content
- Engagement rate: Under 4%
Action: Double down on top 10%, improve middle 30%"
5. Growth Trend Analysis
Spot Patterns and Anomalies:
Trend Visualization:
- 30-day follower growth chart
- 90-day engagement trend
- Spikes and dips identification
- Seasonal patterns
Spike Analysis:
"March 15: +180 followers (3x average)
Cause: Viral post '5 Skincare Mistakes'
- 15k+ views
- 1,200 saves
- 200 shares
Learning: Educational content with mistake themes goes viral
April 3: -45 followers (unusual)
Cause: Controversial opinion post
- Negative comments
- Backlash from community
Learning: Avoid controversial topics, stay positive"
Seasonal Patterns:
"Q1 (Jan-Mar): Slow growth (post-holiday)
Q2 (Apr-Jun): Accelerating (spring content)
Q3 (Jul-Sep): Peak season (summer skincare)
Q4 (Oct-Dec): Strong (holiday gifting)
Strategy: Increase content volume in Q2-Q3"Competitor Analysis Framework:
1. Identify Competitors
Find Relevant Accounts:
Direct Competitors:
- Same niche (skincare, fashion, etc.)
- Similar target audience
- Comparable size (within 10x followers)
- Active presence (regular posting)
Indirect Competitors:
- Adjacent niches (skincare → wellness)
- Larger accounts (aspirational)
- Emerging accounts (rising fast)
Discovery Methods:
- Search industry keywords
- Check hashtag leaders
- View "similar accounts"
- Note who competitors engage with
Example:
"Skincare brand competitors:
Direct:
- @glowbeauty (12k followers, similar size)
- @radiantskin (8k followers, slightly smaller)
- @purebeauty (15k followers, slightly larger)
Indirect:
- @wellnessguru (50k followers, adjacent niche)
- @dermatologist (100k followers, authority)"
2. Performance Benchmarking
Compare Key Metrics:
Metrics to Compare:
- Follower growth rate (% monthly)
- Average engagement rate
- Posting frequency (posts/week)
- Top content types
- Hashtag strategy
Benchmark Table:
| Metric | You | Competitor A | Competitor B | Industry Avg |
|--------|-----|-------------|-------------|--------------|
| Followers | 8,500 | 12,000 | 15,000 | N/A |
| Growth Rate | 4.8% | 3.2% | 5.5% | 4% |
| Engagement | 6.5% | 5.8% | 7.2% | 5% |
| Posts/Week | 5 | 4 | 6 | 5 |
| Avg Likes | 420 | 550 | 680 | 500 |
Insights:
- Growth: Above average ✓
- Engagement: Competitive ✓
- Posting frequency: On par ✓
- Opportunity: Increase avg likes (need more viral content)"
3. Content Strategy Analysis
Reverse-Engineer Success:
Content Mix:
"Competitor A (@glowbeauty):
Content breakdown (last 30 posts):
- Educational: 40% (12 posts)
- Product showcase: 30% (9 posts)
- User testimonials: 20% (6 posts)
- Behind-the-scenes: 10% (3 posts)
Top performing:
- Educational carousels (12% engagement)
- Before/after photos (10% engagement)
- Product demos (8% engagement)
Posting schedule:
- Tuesday, Thursday, Sunday evenings
- Consistent times (8-9 PM)
- 4 posts/week
Hashtag strategy:
- 5-8 hashtags per post
- Mix of broad (#skincare) and niche (#dryskincare)
- Creates own branded hashtag (#GlowTips)"
4. Hashtag and Keyword Research
Discover Winning Terms:
Competitor Hashtags:
Track which hashtags competitors use:
- Most frequently used
- Highest engagement associated
- Branded vs. trending hashtags
Hashtag Performance:
"Analyze competitor's top 10 posts:
Note all hashtags used
Group by category:
- Broad: #skincare, #beauty
- Niche: #dryskin, #naturalskincare
- Trending: #skincareroutine
- Branded: #YourBrandTips
Calculate average engagement per hashtag type:
- Broad: 5% engagement
- Niche: 8% engagement ✓
- Trending: 7% engagement
- Branded: 4% engagement
Learning: Niche hashtags perform best
Action: Increase niche hashtag usage"
5. Campaign and Partnership Tracking
Monitor Competitor Moves:
Partnership Activity:
- Influencer collaborations (who they work with)
- Brand partnerships (co-marketing)
- Affiliate relationships
- Campaign frequency
Campaign Examples:
"Competitor B (@radiantskin):
Recent campaign: 'Summer Glow Challenge'
Duration: 2 weeks
Partners: 10 micro-influencers
Hashtag: #SummerGlowChallenge
Results:
- 2,500 UGC posts
- +3,000 followers gained
- ¥50k revenue attributed
- Engagement spike: 12%
Success factors:
- Clear, fun challenge theme
- Micro-influencers (high engagement)
- Prize incentive (motivated participation)
- Simple participation requirements
Learning: Challenges drive massive engagement
Action: Plan similar challenge campaign"Trend Research Framework:
1. Hot Topic Discovery
Find Rising Content Themes:
Trend Metrics:
- Search volume (how many searching)
- Growth rate (how fast rising)
- Engagement level (interest intensity)
- Duration (sustained vs. flash)
Trend Categories:
Rising Fast (past 24 hours):
- Breaking news, viral content
- Short lifespan (1-3 days)
- High competition
Rising Steady (past week):
- Seasonal topics, emerging trends
- Medium lifespan (1-2 weeks)
- Moderate competition
Evergreen (always relevant):
- Foundational topics
- Consistent search volume
- Steady competition
Example:
"Hot topics in skincare niche:
Rising Fast:
- 'Summer sunscreen mistakes' (+300% today)
- Action: Create content within 24 hours
Rising Steady:
- 'Glass skin routine' (+50% this week)
- Action: Plan content for this week
Evergreen:
- 'Dry skincare tips' (consistent)
- Action: Always have this content available"
2. Hashtag Performance Tracking
Optimize Tag Strategy:
Hashtag Analysis:
For each hashtag you use:
- Total posts with tag (saturation)
- Avg engagement rate
- Growth trend (rising/falling)
- Competitor usage
Performance Scoring:
Score each hashtag (1-10):
- Relevance to content (1-3)
- Engagement rate (1-3)
- Competition level (1-2)
- Growth trend (1-2)
High-performing hashtags (score 8+):
"Top performers:
#skincaretips: Score 9/10
- Relevance: 3/3 (perfect match)
- Engagement: 3/3 (12% avg)
- Competition: 2/2 (moderate)
- Growth: 1/2 (steady)
#dryskincare: Score 8/10
- Relevance: 3/3 (perfect match)
- Engagement: 2/3 (10% avg)
- Competition: 2/2 (low)
- Growth: 1/2 (rising)
Action: Use these in every relevant post"
3. Seasonal Trend Calendar
Plan Content Around Events:
Monthly Themes:
January: New Year, fresh starts, resolutions
February: Self-love, Valentine's Day
March: Spring skincare, seasonal transition
April: Earth Day, sustainability
May: Mother's Day, gifting
June: Summer prep, sun protection
July: Summer survival, hydration
August: Back-to-school, quick routines
September: Fall transition, skincare updates
October: Breast cancer awareness, health
November: Gratitude, community
December: Holidays, gifting, year-end
Planning Example:
"June content plan (summer prep):
Week 1: Sunscreen education
Week 2: Lightweight routines
Week 3: Summer skincare mistakes
Week 4: Hydration focus
Hashtags to ride:
#SummerSkincare
#SunscreenTips
#SummerGlow
Lead time: Create content 2 weeks early"
4. Content Gap Analysis
Find Underserved Areas:
Market Research:
- What topics are competitors NOT covering?
- What questions do followers ask?
- What searches have high volume/low competition?
- What are trending in adjacent niches?
Gap Identification:
"Content gaps in skincare niche:
High search, low competition:
- 'Skincare for eczema' (5k searches, 200 posts)
- 'Men's skincare routine' (3k searches, 150 posts)
- 'Skincare during pregnancy' (2k searches, 100 posts)
Questions from followers:
- 'What ingredients to avoid while pregnant?'
- 'How to build routine on budget?'
- 'Skincare order of application?'
Action: Create content for these gaps"
5. Viral Content Prediction
Anticipate Next Big Thing:
Leading Indicators:
- Early adopter accounts (trendsetters)
- International trends (what worked on Instagram)
- Seasonal patterns (predictable)
- Platform algorithm shifts
Prediction Framework:
"Signals for upcoming trends:
1. Micro-influencers talking about topic (early adoption)
2. Instagram trend gaining traction (likely to spread)
3. Seasonal shift approaching (predictable)
4. Xiaohongshu testing new feature (algorithm boost)
Example prediction:
'Skin cycling' trend emerging:
- 10 micro-influencers mentioned this week (up from 2)
- Trending on Instagram (likely to spread)
- Educational content (always popular)
Prediction: Will go mainstream in 2-3 weeks
Action: Create educational content now, be ready when trend hits"Influencer Analytics Framework:
1. Influencer Discovery
Find Right Partners:
Search Filters:
- Niche/industry (skincare, beauty, fashion)
- Follower count (1k-500k+)
- Engagement rate (minimum 5%)
- Location (target cities)
- Growth rate (positive trend)
Discovery Methods:
- Search by keyword (niche terms)
- Competitor partnerships (who they work with)
- Hashtag leaders (who dominates hashtags)
- Similar audiences (lookalike)
Example:
"Search for micro-influencers:
Filters:
- Followers: 5k-50k
- Engagement: 8%+
- Niche: Skincare
- Location: Tier 1 cities
- Growth: +5% monthly (growing)
Results: 25 potential partners
Shortlist: Top 10 based on engagement and audience match"
2. Engagement Quality Assessment
Look Beyond Metrics:
Quality Indicators:
- Comment authenticity (real conversations vs. spam)
- Follower activity (active vs. ghost followers)
- Content consistency (regular posting)
- Audience interaction (influencer responds)
Red Flags:
- Generic/bot comments ("great post!", "nice!")
- Sudden follower spikes (bought followers)
- Inconsistent posting (lack of commitment)
- Low comment-to-like ratio (<1%)
Quality Scorecard:
"Influencer: @skincarequeen (25k followers)
Engagement Metrics:
- Avg likes: 1,200 (4.8%)
- Avg comments: 85 (0.34%)
- Comment quality: High (genuine questions)
- Response rate: 80% (engages with audience)
Content Quality:
- Post frequency: 4-5x/week (consistent)
- Production value: High (professional)
- Brand alignment: Perfect (niche match)
Growth:
- Monthly growth: +8% (healthy)
- Follower quality: High (active, real)
Overall Score: 9/10
Decision: Strong partnership candidate"
3. Audience Analysis
Ensure Target Match:
Demographic Match:
- Age alignment (target 25-40)
- Gender split (90% women matches)
- Location (target cities present)
- Interests (skincare enthusiasts)
Audience Authenticity:
- Follower-to-following ratio (near 1:1 or higher)
- Comment sentiment (positive, engaged)
- Engagement patterns (organic vs. suspicious)
Example Analysis:
"@skincarequeen audience:
- Age: 25-34 (50%), 35-44 (30%) ✓ matches target
- Gender: 95% women ✓ matches target
- Location: Shanghai (25%), Beijing (20%) ✓ tier 1
- Interests: Skincare (80%), beauty (60%), wellness (40%)
Audience authenticity:
- Follower ratio: 1.2:1 (healthy)
- Comments: Genuine, specific (not spam)
- Engagement: Consistent (not spike-heavy)
Conclusion: Perfect audience match"
4. Partnership ROI Prediction
Estimate Campaign Success:
Historical Performance:
- Past campaign results
- Typical engagement rate
- Conversion rate (if trackable)
- Brand partnership frequency
ROI Estimation:
"Influencer: @skincarequeen
Followers: 25k
Engagement: 5.1%
Cost: ¥2,000 per post
Expected reach:
- Immediate: 25k × 30% = 7,500 views
- Shares: 7,500 × 5% = 375 additional views
- Total reach: ~7,900
Expected engagement:
- Likes: 7,900 × 5% = 395
- Comments: 7,900 × 0.5% = 40
- Saves: 7,900 × 2% = 158
Expected conversions (if product link):
- Clicks: 7,900 × 3% = 237
- Purchases: 237 × 5% = 12
- Revenue: 12 × ¥150 = ¥1,800
ROI: ¥1,800 / ¥2,000 = 0.9 (break even on direct sales)
Value: Brand awareness + content reuse = additional value
Decision: Worth it for brand exposure + content"
5. Campaign Tracking
Measure Partnership Success:
Tracking Metrics:
- Reach (impressions, unique viewers)
- Engagement (rate, quality)
- Clicks (link clicks, promo code uses)
- Conversions (sales, signups)
- ROI (revenue / cost)
Attribution:
- Trackable links (UTM parameters)
- Unique promo codes (INFLUENCER20)
- Conversion tracking (website analytics)
- Customer surveys (how did you hear about us?)
Example Report:
"Campaign: @skincarequeen partnership
Duration: 1 month
Posts: 4
Investment: ¥8,000
Results:
- Total reach: 35,000
- Avg engagement: 6.2% (above target)
- Link clicks: 850
- Promo code uses: 95
- Sales: 95 units × ¥150 = ¥14,250
- ROI: 1.78 (revenue / cost)
Content value:
- Reusable content: 4 posts
- Content rights: Perpetual
- Additional value: ¥2,000
Total value: ¥16,250
Total ROI: 2.03
Conclusion: Successful partnership, renew"Data-Driven Optimization:
1. Content Performance Review
Weekly Analysis:
Top Performers Analysis:
- Identify top 5 posts (by engagement)
- Common themes: Educational carousels
- Formats: Multi-slide, visual-heavy
- Topics: Skincare mistakes, tips
- Hashtags: Mix of broad + niche
- Posting times: Tuesday/Thursday 8 PM
Bottom Performers Analysis:
- Identify bottom 5 posts
- Common issues: Purely promotional
- Formats: Single image, text-heavy
- Topics: Product-focused only
- Engagement: Under 4%
Action Items:
"Based on analysis:
Do more of:
- Educational carousels (12% avg engagement)
- Before/after content (10% avg)
- Skincare tips and mistakes (high saves)
- Post Tue/Thu 8 PM (peak engagement)
Do less of:
- Pure product promotion (3% engagement)
- Generic quotes (4% engagement)
- Text-heavy posts (low saves)
- Monday posts (low engagement)
New mix:
- Educational: 50% (from 40%)
- Product: 20% (from 30%)
- UGC/testimonials: 20% (from 15%)
- Entertainment: 10% (from 15%)"
2. A/B Testing Framework
Continuous Experimentation:
Test Variables:
Format Test:
Version A: Carousel (7 slides, educational)
Version B: Single image + long caption
Version C: Video (60 seconds)
Measure: Engagement rate, saves, shares
Winner: Carousel (12% vs 6% vs 8%)
Action: Prioritize carousel format
Hashtag Test:
Version A: 5 hashtags (3 broad, 2 niche)
Version B: 10 hashtags (5 broad, 5 niche)
Version C: 15 hashtags (mix)
Measure: Reach, engagement
Winner: 10 hashtags (optimal balance)
Action: Standardize on 8-12 hashtags
Posting Time Test:
Version A: Morning post (7-9 AM)
Version B: Evening post (7-9 PM)
Version C: Lunch post (12-1 PM)
Measure: Reach, engagement
Winner: Evening post (highest engagement)
Action: Prioritize evening posts
Testing Cadence:
- Weekly: 1 small test (hashtag or time)
- Monthly: 1 major test (format or content type)
- Quarterly: Review all learnings
3. Posting Schedule Optimization
Data-Driven Timing:
Optimal Time Analysis:
"Heatmap analysis (engagement by day/time):
Monday:
- 7-8 AM: Low (3% engagement)
- 12-1 PM: Medium (5%)
- 8-9 PM: Medium (6%)
Tuesday:
- 8-9 PM: High (8%) ✓
Wednesday:
- 7-8 PM: High (7.5%)
Thursday:
- 8-9 PM: High (8.2%) ✓
Friday:
- 7-8 PM: Medium (6%)
Saturday:
- 2-3 PM: Medium (6%)
Sunday:
- 7-8 PM: Medium (6.5%)
Optimal windows:
- Tuesday 8-9 PM
- Thursday 8-9 PM
- Wednesday 7-8 PM
Action: Schedule important content for these times"
4. Seasonal Strategy Adjustment
Adapt to Patterns:
Seasonal Performance:
"Q1 Performance (Jan-Mar):
- Avg engagement: 5.8%
- Top content: Winter skincare tips
- Slowest growth month: January
Q2 Performance (Apr-Jun):
- Avg engagement: 6.5% (improving)
- Top content: Spring routines, sun protection
- Growth accelerating
Q3 Planning (Jul-Sep):
- Expected: Peak engagement
- Focus: Summer skincare, hydration
- Increase post frequency (6-7x/week)
- Campaign: Summer challenge
Q4 Planning (Oct-Dec):
- Expected: Strong (holiday season)
- Focus: Gifting, year-end reviews
- Campaign: Holiday gift guide"
5. Goal Setting and Tracking
Measure Against Targets:
SMART Goals:
- Specific: Clear metrics
- Measurable: Quantifiable
- Achievable: Realistic
- Relevant: Aligns with business
- Time-bound: Deadline
Example Goals:
"Q2 2026 Goals:
Followers:
- Start: 8,500
- Target: 12,000 (+41%)
- Stretch: 15,000 (+76%)
- Monthly growth: 12%
Engagement:
- Current: 6.5%
- Target: 8% (improvement)
- Strategy: More educational content
Content:
- Post frequency: 5x/week → 6x/week
- Carousel rate: 40% → 60%
- Video content: 10% → 20%
Conversion:
- Link clicks: 500/month → 800/month
- Email signups: 200/month → 350/month
- Sales: ¥25k/month → ¥40k/month
Monthly check-ins:
- Review progress
- Adjust strategy if off-track
- Celebrate wins"| Mistake | Why Happens | Fix |
|---|---|---|
| Data overload | Track too many metrics | Focus on 5-7 key metrics |
| Analysis paralysis | Overthinking insights | Take action on clear patterns |
| Ignoring context | Metrics without meaning | Consider seasonality, events |
| Copying competitors blindly | Seems safe | Adapt to your unique brand |
| Vanity metrics | Focus on follower count | Prioritize engagement and conversion |
| Not acting on insights | Comfortable with status quo | Implement changes based on data |
| Checking too frequently | Impatience | Review weekly, not daily |