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Agent Skill · 研究检索

xinhong-data(新鸿数据)

用于辅助数据整理、表格处理、CSV/Excel 分析、指标计算和图表准备。它适合让 Agent 清洗字段、汇总数据、发现异常、生成统计口径或把分析结果转成可读说明。使用时需要确认数据来源、字段含义和时间范围,避免把样本数据当全量事实;涉及敏感数据、导出文件或批量写回时,应先确认权限和脱敏边界。

xinhong-data 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 26,730。

总安装 3,515周安装 151GitHub Stars 142下载 1,232核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:xinhong-data(新鸿数据)
来源仓库:https://github.com/vivy-yi/xiaohongshu-skills
仓库路径:skills/xinhong-data
安装命令:
npx skills add https://github.com/vivy-yi/xiaohongshu-skills --skill xinhong-data
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/vivy-yi/xiaohongshu-skills --skill xinhong-data

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

xinhong-data 用于辅助数据整理、表格处理和指标计算。适合清洗字段、汇总数据或生成统计口径。xinhong-data 属于研究检索类 Skill,可作为该场景下的辅助能力补充。使用时需确认数据来源、字段含义和时间范围。避免将样本数据当作全量事实,注意敏感数据处理。涉及导出或写回操作时,应先确认权限和脱敏要求。

来源仓库内路径:skills/xinhong-data

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/vivy-yi/xiaohongshu-skills --skill xinhong-dat…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

xinhong-data 怎么安装?

在终端执行 npx skills add https://github.com/vivy-yi/xiaohongshu-skills --skill xinhong-data。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

xinhong-data 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

xinhong-data 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

xinhong-data 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

xinhong-data 用的人多吗?

公开数据是累计安装 3,515 次,近一周安装 151 次,下载 1,232 次,GitHub 142 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

xinhong-data 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
xinhong-data

新鸿数据 · 本页

3,515142只读未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

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):

   Top 20 Hashtags by Usage:
   ┌──────────────────────┬─────┬──────────┬────────┬─────────┐
   │ Hashtag              │ Use│ Avg Eng  │ Reach  │ Impact  │
   ├──────────────────────┼─────┼──────────┼────────┼─────────┤
   │ #skincare            │  85 │  5.2%    │ 450k   │ Low     │
   │ #dryskincare         │  72 │  9.8%    │  95k   │ High ✓  │
   │ #skincaretips        │  68 │  6.5%    │ 180k   │ Medium  │
   │ #hydratingskincare   │  65 │ 10.2%   │  78k   │ High ✓  │
   │ #naturalskincare     │  58 │  8.8%    │ 120k   │ Medium  │
   │ #sensitiveskin       │  54 │  9.5%    │  88k   │ High    │
   │ #skincareroutine     │  51 │  7.2%    │ 135k   │ Medium  │
   │ #beauty              │  48 │  4.8%    │ 520k   │ Low     │
   │ #glowingskin          │  42 │  8.1%    │  65k   │ Medium  │
   │ #skincareeducation   │  38 │ 11.5%   │  42k   │ Very ✓ │
   └──────────────────────┴─────┴──────────┴────────┴─────────┘

   Optimal Mix Identified:

   Tier 1 - Always Use (10% of hashtags):
   - #dryskincare (9.8% eng, targeted)
   - #hydratingskincare (10.2% eng, specific)
   - #skincareeducation (11.5% eng, niche)
   - #sensitiveskincare (9.5% eng, engaged)

   Tier 2 - Regular Use (40% of hashtags):
   - #skincaretips (6.5% eng, broad)
   - #naturalskincare (8.8% eng, good)
   - #glowingskin (8.1% eng, aesthetic)
   - #skincareroutine (7.2% eng, practical)

   Tier 3 - Supplemental (30% of hashtags):
   - Seasonal/trending tags
   - Campaign-specific tags
   - Community tags
   - Branded tags

   Tier 4 - Avoid (20% of hashtags):
   - Overused broad tags (#beauty, #skincare)
   - Irrelevant tags
   - Low-performing tags

   New Hashtag Strategy:
   Per post: 10 hashtags total

   Mix:
   - 1 Tier 1 (niche, high-performing)
   - 4 Tier 2 (relevant, consistent)
   - 3 Tier 3 (trending, variety)
   - 2 Tier 4 (minimal broad tags for reach)

   Expected improvement:
   - Reach: +35% (better targeting)
   - Engagement: +18% (more relevant audience)
   - Follower growth: +25% (better discoverability)"

Step 2: Deep Competitor Analysis

Strategic Benchmarking:

Competitor Intelligence Framework:

1. Multi-Metric Comparison
   Comprehensive Benchmarking:

   Comparison Dimensions:
   Growth Metrics:
   - Follower count (total)
   - Growth rate (monthly)
   - Post frequency (content volume)
   - Engagement rate (quality)
   - Content mix (type distribution)

   Content Performance:
   - Avg likes per post
   - Avg comments per post
   - Avg saves per post
   - Top performing content types
   - Worst performing content types

   Audience Metrics:
   - Follower demographics
   - Active follower percentage
   - Audience interests
   - Geographic distribution

   Benchmark Report:
   "Competitor Comparison (Top 5 Competitors):

   ┌──────────────┬──────────┬─────────┬──────────┬────────┐
   │ Metric       │ You       │ Comp Avg │ Leader   │ Your Rank│
   ├──────────────┼──────────┼─────────┼──────────┼────────┤
   │ Followers    │ 12,750    │ 18,500  │  25,000  │    5   │
   │ Growth (MoM) │   +15%    │   +12%  │   +18%   │    2 ✓ │
   │ Eng Rate    │   8.2%    │   6.8%  │   9.1%   │    2 ✓ │
   │ Posts/Week   │    6      │    7    │    8     │    4   │
   │ Avg Likes    │   840     │   650    │  1,200   │    2 ✓ │
   │ Avg Comments │   125     │    95    │   180    │    2 ✓ │
   │ Avg Saves    │   105     │    70    │   140    │    2 ✓ │
   └──────────────┴──────────┴─────────┴──────────┴────────┘

   Performance Analysis:

   Your Strengths (Top 3):
   1. Engagement rate: 8.2% vs 6.8% avg (+20%)
   2. Growth rate: +15% vs +12% avg (+25%)
   3. Content quality: High saves and comments

   Your Weaknesses (Bottom 3):
   1. Follower count: Smallest in group (catching up)
   2. Post frequency: Below leader (6 vs 8)
   3. Reach: Limited by smaller size

   Leader Analysis (Competitor E - 25k followers):
   - Secrets to success:
     * Posts 8x/week (high volume)
     * 60% educational content
     * Strong visual identity
     * Community management (responds to all comments)
     * Consistent posting times (Tue/Thu 8 PM)

   Gap Analysis:
   - Content: You match education %
   - Frequency: You post 6x vs their 8x
   - Visuals: Your style is similar
   - Community: You respond but slower
   - Timing: You match optimal times

   Action Plan:
   1. Increase posting to 7x/week (manageable increase)
   2. Improve community response time (goal: <4 hours)
   3. Study their visual style (learn what works)
   4. Collaborate with similar influencers (they do this)
   5. Leverage your higher engagement (your advantage)"

2. Content Strategy Comparison
   Reverse-Engineer Success:

   Content Mix Analysis:
   By Type:
   - Educational (% of total)
   - Promotional (% of total)
   - Inspirational (% of total)
   - Personal (% of total)
   - Entertainment (% of total)

   By Format:
   - Carousel (% of total)
   - Video (% of total)
   - Single image (% of total)
   - Live (% of total)

   By Topic:
   - Product-specific
   - Category education
   - Lifestyle
   - Behind-the-scenes
   - User-generated

   Strategy Analysis:
   "Competitor Content Strategy Deep Dive:

   Competitor E (Leader - 25k followers, 9.1% engagement):

   Content Mix (Last 50 posts):
   - Educational: 60% (30 posts)
     * Tutorials: 12
     * Tips: 10
     * Myth-busting: 8

   - Promotional: 20% (10 posts)
     * Product demos: 6
     * Special offers: 4

   - Personal: 10% (5 posts)
     * Stories: 3
     * Behind-the-scenes: 2

   - Inspirational: 5% (2 posts)
     * Quotes: 2

   - Entertainment: 5% (3 posts)
     * Trends: 3

   Format Mix:
   - Carousels: 50% (25 posts)
   - Videos: 30% (15 posts)
   - Single images: 20% (10 posts)

   Top Performing Content:
   1. '5 Mistakes When Using Vitamin C' (carousel)
      - 12.5% engagement
      - 28% saves
      - Educational + mistake theme

   2. 'My Complete Night Routine' (video)
      - 11.8% engagement
      - 15% shares
      - Personal + detailed

   3. 'Before/After: 30-Day Transformation' (carousel)
      - 10.5% engagement
      - 22% shares
      - Visual proof

   Your Comparison:
   - You: 40% educational, 30% promo, 15% personal, 10% inspirational, 5% UGC
   - Them: 60% educational, 20% promo, 10% personal, 5% inspirational, 5% entertainment

   Key Difference:
   - They lean more into education (60% vs your 40%)
   - They do less personal content (10% vs your 15%)
   - Similar promotional approach (20% range)

   Learnings:
   1. Increase educational content to 50%+
   2. Embrace 'mistake' format (high engagement)
   3. Create more routine content (personal + practical)
   4. Maintain before/after content (your strength)

   Implementation:
   Next month content calendar:
   - 26 posts total (6x/week for 4 weeks)
   - 14 educational (54%)
   - 5 promotional (19%)
   - 3 personal (12%)
   - 2 UGC/testimonials (8%)
   - 2 before/after (8%)

   Expected engagement increase: +15%"

3. Growth Trajectory Benchmarking
   Compare Historical Performance:

   Growth Path Analysis:
   Follower Milestones:
   - Time to 1k followers
   - Time to 5k followers
   - Time to 10k followers
   - Time to 25k followers
   - Time to 50k followers

   Growth Acceleration:
   - Month-over-month growth rate
   - Inflection points (when growth accelerated)
   - Viral events impact
   - Strategy changes impact

   Historical Comparison:
   "Growth Trajectory Comparison:

   Your Growth Path:
   Month 1-3 (0-1k): 3 months (slow start)
   Month 4-8 (1k-5k): 5 months (steady)
   Month 9-14 (5k-10k): 6 months (moderate)
   Month 15-current (10k-12.75k): 2 months (accelerating)

   Competitor E Growth Path (similar starting point):
   Month 1-3 (0-1k): 3 months (same as you)
   Month 4-7 (1k-5k): 4 months (faster than you)
   Month 8-11 (5k-10k): 4 months (faster)
   Month 12-15 (10k-25k): 4 months (much faster)

   Analysis:
   - They accelerated in 5-10k range (you slowed)
   - They reached 25k in 15 months (your pace slower)
   - Key difference: Strategy pivot at 10k

   Their Strategy Changes at 10k:
   - Increased posting: 5x → 8x/week
   - Shifted content: 50% → 70% educational
   - Added live streams: 0 → 2x/week
   - Influencer partnerships: 1 → 5/month
   - Paid promotion: 0 → ¥3k/month

   Your Current Position:
   - At 12.75k followers
   - Similar to their 10k inflection point
   - Prime opportunity to accelerate

   Action Plan:
   1. Increase posting to 7-8x/week (+16-33% content)
   2. Shift to 50%+ educational content
   3. Start weekly live streams
   4. Scale influencer partnerships (5-10/month)
   5. Test paid promotion (¥2k/month budget)

   Forecast:
   Current trajectory: 15% monthly growth
   → 15k followers in 6 months

   Optimized trajectory: 25% monthly growth
   → 25k followers in 6 months

   Risk:
   - Quality may suffer with more posts
   - Burnout from increased workload
   - Ad spend may not have immediate ROI

   Mitigation:
   - Use content batching (create in bulk)
   - Repurpose content across platforms
   - Scale ads gradually based on performance"

4. Audience Overlap Analysis
   Identify Market Opportunities:

   Follower Overlap:
   - How many followers do you share with competitors?
   - Exclusive followers (only follow you)
   - Multi-follow (follow you + competitors)
   - Follower loyalty (who engages more)

   Overlap Insights:
   "Audience Overlap Analysis (Top 3 Competitors):

   Total Followers:
   - You: 12,750
   - Competitor A: 18,500
   - Competitor B: 15,200
   - Competitor C: 14,800
   - Competitor D: 25,000

   Overlap Matrix:
   ┌──────────┬──────┬──────┬──────┬──────┐
   │          │  Comp│  Comp│  Comp│  Comp│
   │          │  A   │  B   │  C   │  D   │
   ├──────────┼──────┼──────┼──────┼──────┤
   │ You      │ 4,200│ 3,800│ 2,900│ 5,500│
   │          │ 33%  │  30% │  23% │  43% │
   ├──────────┼──────┼──────┼──────┼──────┤
   │ Comp A   │   X  │ 5,500│ 4,800│ 7,200│
   │ (18.5k)  │      │  30% │  26% │  39% │
   ├──────────┼──────┼──────┼──────┼──────┤
   │ Comp B   │ 5,500│   X  │ 4,200│ 6,100│
   │ (15.2k)  │  36% │      │  28% │  40% │
   ├──────────┼──────┼──────┼──────┼──────┤
   │ Comp C   │ 4,800│ 4,200│   X  │ 5,900│
   │ (14.8k)  │  32% │  28% │      │  40% │
   ├──────────┼──────┼──────┼──────┼──────┤
   │ Comp D   │ 7,200│ 6,100│ 5,900│   X  │
   │ (25.0k)  │  29% │  24% │  24% │      │
   └──────────┴──────┴──────┴──────┴──────┘

   Key Insights:

   1. High Overlap with Competitor D (43%)
   - 5,500 shared followers
   - They are leader (25k followers)
   - Opportunity: Differentiate to win exclusive followers

   2. Exclusive Opportunity
   - Your exclusive: 12,750 - 5,500 = 7,250 (57%)
   - Market not saturated
   - Room for growth before high overlap

   3. Multi-Follower Behavior
   - Followers following 3+ brands: 60%
   - Followers following all 5: 15%
   - Indicates: Shopping around, not loyal

   4. Engagement by Loyalty:
   - Your exclusive followers: 12% engagement (very loyal!)
   - Multi-followers: 6% engagement (shopping around)
   - Learning: Build exclusive base (higher value)

   Strategy:
   1. Target non-overlap audiences (different content)
   2. Build loyalty with exclusive followers (nurture them)
   3. Give multi-followers reason to choose you (unique value)
   4. Differentiate from Competitor D (they have 43% overlap!)

   Differentiation Ideas:
   - Unique content format (not used by competitors)
   - Niche focus (narrow but deep)
   - Community building (exclusive access)
   - Behind-the-scenes access (transparency)
   - Product innovation (unique offering)"

5. Partnership Analysis
   Learn from Competitor Collaborations:

   Partnership Tracking:
   Influencer Partnerships:
   - Who they partner with
   - Frequency of partnerships
   - Partnership type (sponsored, affiliate, ambassador)
   - Estimated investment
   - Content performance from partnerships

   Brand Collaborations:
   - Co-branded products
   - Joint campaigns
   - Cross-promotions
   - Event partnerships
   - Giveaway collaborations

   Partnership Analysis:
   "Competitor Partnership Intelligence:

   Competitor E (Leader) Partnerships:

   Influencer Partners (Last 3 months):
   - Total partnerships: 45
   - Unique influencers: 28
   - Repeat partners: 17 (60% retention)

   Partner Tiers:
   Mega (500k+ followers): 2
   - Avg cost: ¥15,000/post
   - Avg engagement: 3.2%
   - ROI: 1.8x (not great)

   Macro (100k-500k): 8
   - Avg cost: ¥5,000/post
   - Avg engagement: 4.8%
   - ROI: 3.2x (decent)

   Mid-tier (10k-100k): 25
   - Avg cost: ¥1,500/post
   - Avg engagement: 8.5%
   - ROI: 5.8x (excellent!)

   Micro (1k-10k): 10
   - Avg cost: ¥500/post
   - Avg engagement: 12.5%
   - ROI: 9.2x (outstanding!)

   Key Learnings:
   - Mid-tier partners have best ROI (5.8x)
   - Micro partners have highest ROI (9.2x)
   - Mega partners have lowest ROI (1.8x)
   - They're shifting toward mid/micro (smart move)

   Partnership Types:
   - Sponsored posts: 60% (one-time)
   - Affiliate: 25% (commission-based)
   - Brand ambassadors: 15% (ongoing)

   Ambassador Program:
   - 5 ambassadors currently
   - 4 posts/month each
   - ¥3,000/month retainer
   - 10% commission
   - 6-month contracts
   - Top performer generates ¥12k/month revenue

   Your Application:

   Current partnerships:
   - 8 influencers (varied tiers)
   - Mostly one-off sponsored posts
   - No formal ambassador program

   Opportunity:
   - Implement ambassador program (proven by Comp E)
   - Shift focus to mid-tier (best ROI balance)
   - Add micro-influencers (highest ROI)
   - Reduce mega-influencers (low ROI)

   Action Plan:
   Month 1: Launch ambassador program
   - Recruit 5 mid-tier influencers (10k-50k)
   - Offer: ¥2,000/month + 12% commission
   - Commitment: 6 months
   - Target: 4 posts/month

   Month 2: Expand micro-influencer program
   - Recruit 15 micro-influencers (1k-10k)
   - Offer: Product + ¥300 fee
   - Commitment: 2 posts
   - Target: Test, keep best performers

   Expected Results:
   - Ambassador program: ¥60k revenue/month (30% ROI)
   - Micro program: ¥18k revenue/month (45% ROI)
   - Blended ROI: 5.5x (significant improvement)

   Investment:
   - Ambassador program: ¥30k/month
   - Micro program: ¥9k/month
   - Total: ¥39k/month
   - Return: ¥78k/month
   - Net profit: ¥39k/month"

### Step 3: Industry Trend Analysis

**Market Intelligence**:

Trend Analysis Framework:

  1. Category Growth Tracking Monitor Market Expansion: Category Metrics: Overall Xiaohongshu: Specific Category: Subcategory Trends: Category Analysis: "Skincare Category Trend Analysis (Q1 2026): Overall Category: Subcategory Growth (YoY): ┌────────────────────┬──────────┬─────────┬────────┐ │ Subcategory │ Growth │ 2025 │ 2026 │ ├────────────────────┼──────────┼─────────┼────────┤ │ Hydrating products │ +85% │ 12% │ 22% │ │ Anti-aging │ +65% │ 18% │ 30% │ │ Natural/organic │ +120% │ 8% │ 18% │ │ Men's skincare │ +95% │ 3% │ 6% │ │ Sensitive skin │ +45% │ 15% │ 22% │ │ Clean beauty │ +70% │ 10% │ 17% │ └────────────────────┴──────────┴─────────┴────────┘ Key Trends: Market Saturation Analysis: Your Position: Strategic Recommendations:

- Total users - Active users - Content volume - Ad spend growth - Skincare category size - Growth rate - Market share by brand - Emerging subcategories - Clean beauty growth - K-beauty adoption - Men's skincare expansion - Anti-aging market - Natural/organic products - Total posts with #skincare: 2.5M (up 35% YoY) - Total skincare brands on platform: 15,000+ (up 50% YoY) - Category growth rate: 18% YoY (healthy expansion) 1. Hydrating products exploding (+85%) - Dry skin awareness rising - Seasonal factor (winter to spring prep) - Opportunity: Double down on hydrating serums 2. Natural/organic surging (+120%) - Clean beauty movement - Ingredient-conscious consumers - Opportunity: Emphasize natural ingredients 3. Men's skincare emerging (+95%) - Blue ocean opportunity - Low competition currently - Opportunity: Create men's line or content 4. Anti-aging consistently strong (+65%) - Aging population - Preventive skincare - Opportunity: Anti-aging education content - Saturated: Basic moisturizers (declining growth) - Emerging: Barrier repair (growing fast) - Stable: Sunscreen (steady demand) - Niche: Pregnancy skincare (untapped) - Focused on: Dry skincare, hydrating products - Positioning: Natural, effective - Growth: 15% MoM (below category 18%) - Opportunity: Expand into emerging subcategories 1. Leverage hydrating trend (already positioned well) 2. Create natural/organic content series (tap +120% growth) 3. Test men's skincare content (blue ocean opportunity) 4. Develop anti-aging educational content (steady demand) 5. Avoid saturated basic moisturizer category"

  1. Content Format Trends Stay Ahead of Format Shifts: Format Evolution: Emerging Formats: Declining Formats: Format Performance: "Content Format Trend Analysis (Q1 2026): Format Growth (Engagement Rate): ┌──────────────────┬──────────┬─────────┬────────┐ │ Format │ Q1 2025 │ Q1 2026 │ Change │ ├──────────────────┼──────────┼─────────┼────────┤ │ Carousel 5-7 slides│ 6.8% │ 9.5% │ +40% ✓ │ │ Carousel 8-10+ │ 7.2% │ 11.8% │ +64% ✓│ │ Short video 15-30s │ 5.5% │ 8.8% │ +60% ✓│ │ Long video 60s+ │ 8.1% │ 4.8% │ -41% │ │ Single image │ 4.2% │ 3.5% │ -17% │ │ Live stream clip │ 7.5% │ 9.2% │ +23% ✓│ │ Story series │ 6.2% │ 8.5% │ +37% ✓│ └──────────────────┴──────────┴─────────┴────────┘ Rising Stars: Declining: Your Current Mix: Optimization Plan: Shift to trend-aligning mix: Expected impact:

- Short-form video (15-30 seconds) - Carousel deep-dives (10+ slides) - Live stream highlights - Story series - Interactive content (polls, Q&As) - Long-form video (declining -40%) - Single image posts (declining -25%) - Text-only posts (minimal engagement) 1. Deep-dive carousels (8-10 slides) - Comprehensive education - High save rate (25%+) - Format of the future 2. Short-form video (15-30 seconds) - Quick tips - High share rate - Platform favoring this format 3. Story series (connected narratives) - Builds anticipation - Increases engagement - Follower retention 1. Long-form video (>60 seconds) - Attention spans shortening - Platform algorithms favor shorter content - 41% decline YoY 2. Single image posts - Low engagement - Oversaturated format - Being de-prioritized by platform - Carousels: 60% (aligned with trend ✓) - Videos: 20% (split between short and long) - Single images: 15% (reduce this) - Live clips: 5% (increase this) - Deep-dive carousels: 70% (from 60%) - Short videos: 20% (from 10%) - Live stream clips: 10% (from 5%) - Single images: 0% (eliminate) - Overall engagement: +25% - Save rate: +20% (more comprehensive content) - Share rate: +35% (more viral formats)"

  1. Consumer Behavior Trends Understand Audience Evolution: Behavior Shifts: Content Consumption: Shopping Behavior: Behavior Insights: "Consumer Behavior Trend Analysis: Discovery Patterns (Q1 2026): How Users Find Content: Key Trend: Shift from passive discovery (algorithm) to active discovery (search). Users are more intentional and research-driven. Implication: Engagement Evolution: Key Insights: Purchase Journey Trends: Pre-Purchase Research: Purchase Triggers: Post-Purchase: Content Strategy Implications:

- How users discover content - How they engage (like, comment, save, share) - What makes them follow - What makes them purchase - Research process (pre-purchase) - Trust indicators (reviews, testimonials) - Purchase triggers (urgency, value, quality) - Post-purchase behavior (reviews, UGC) - Xiaohongshu algorithm feed: 45% (down from 55% in 2025) - Search (keywords, hashtags): 30% (up from 20%) - Influencer referrals: 15% (stable) - External social (ads, other platforms): 10% (up) - SEO-friendly content more important - Keyword optimization in titles and captions - Hashtag strategy critical for search - Educational content ranks higher in search - Save behavior: Up 40% YoY (users saving for later) - Share behavior: Up 25% YoY (sharing valuable content) - Comment behavior: Stable (consistent question-asking) - Follow behavior: Down 15% (more selective) - 'Save' is new 'like' (content curation) - Sharing indicates trust and value - Comments = purchase intent - Followers are more discerning - Weeks of research: 45% (up from 30%) - Content consumed: 12+ pieces (up from 8) - Sources: Reviews, comparisons, tutorials - Trust signals: UGC, before/after, testimonials - Educational content: 'Now I understand the problem' - Visual proof: 'I can see it works' - Social proof: 'Others like me love this' - Offer: 'Good value, low risk (guarantee)' - Urgency: 'Limited time or quantity' - UGC creation: 35% post about purchase - Review rate: 25% leave detailed review - Repurchase: 40% buy again within 60 days - Advocacy: 15% recommend to friends 1. Create comprehensive educational content (research phase) 2. Use before/after visual proof (trust building) 3. Encourage and share UGC (social proof) 4. Leverage reviews in marketing (authenticity) 5. Clear risk-reversal (guarantees) 6. Create urgency strategically (not always)"

  1. Hashtag Trend Forecasting Anticipate Tag Performance: Trend Tracking: Rising Hashtags: Declining Hashtags: Forecasting Model: "Hashtag Trend Forecast (Next 90 Days): Rising Stars (Predicted High Performance): Stable Performers (Consistent): Declining Tags (Avoid): Seasonal Opportunities: Strategy: Expected improvement:

- New trending tags - Accelerating search volume - Increasing post volume - Seasonal patterns - Saturation indicators - Declining engagement - Oversaturated content - Loss of relevance 1. #springskincareroutine - Current: 5k posts - Growth: +120% in past month - Forecast: +200% by end of Q2 - Recommendation: Use heavily now 2. #barrierrepair - Current: 8k posts - Growth: +85% in past month - Forecast: +150% by end of Q2 - Recommendation: Incorporate into content 3. #glasskincn (Chinese 'glass skin') - Current: 3k posts - Growth: +250% in past month - Forecast: +400% by end of Q2 - Recommendation: Ride the wave 1. #dryskincare - Current: 85k posts - Growth: +15% YoY (steady) - Engagement: Consistent 9.8% - Recommendation: Always-use core tag 2. #hydratingskincare - Current: 42k posts - Growth: +25% YoY - Engagement: 10.2% - Recommendation: Always-use core tag 1. #skincaregoals - Current: 150k posts - Growth: -5% YoY (declining) - Engagement: 4.2% (below average) - Recommendation: Phase out 2. #beautytips - Current: 250k posts - Growth: -10% YoY (declining) - Engagement: 3.5% (below average) - Recommendation: Too saturated, avoid - #summerskincare: Will spike in May-June - #sunsafety: Will spike in June-July - #fallskincare: Will spike in September 1. Core Tags (always use): - #dryskincare, #hydratingskincare (2-3) 2. Rising Tags (use heavily now): - #barrierrepair, #glasskincn (3-4) 3. Seasonal Tags (add when relevant): - #springskincare (March-May) - #summerskincare (June-August) 4. Avoid Declining Tags: - #skincaregoals, #beautytips (remove)" - Reach: +40% (rising tags less competitive) - Engagement: +20% (aligned with trending topics) - Follower growth: +30% (better discoverability)"

  1. Innovation and Feature Adoption Early Adoption Advantage: Platform Features: New Features: Adoption Rates: Innovation Analysis: "Platform Innovation Tracking (Q1 2026): New Features Launched: Innovation Adoption Strategy: Immediate (this month): Short-term (next 2 months): Long-term (next 6 months): Competitive Advantage: Risk Management:

- Xiaohongshu shopping integrations - Live shopping features - Video enhancements - AR try-on features - New ad formats - Early adopters (first 1-3 months) - Early majority (3-6 months) - Late majority (6-12 months) - Laggards (12+ months) 1. In-app shopping (direct purchase from posts) - Adoption: 15% of brands (early stage) - User adoption: 8% of users - Engagement with posts with shop link: +40% - Recommendation: Integrate immediately 2. Live shopping enhanced features - Adoption: 25% of sellers - Engagement: +60% on lives with features - Conversion: +35% on enhanced lives - Recommendation: Use for all live streams 3. AR try-on for cosmetics - Adoption: 10% of brands (testing) - User feedback: 75% positive - Conversion: +25% when AR available - Recommendation: Test with our products 4. Product tagging in video - Adoption: 35% of creators - Click-through: +50% on tagged products - Engagement: Neutral effect - Recommendation: Use in video content 5. Series stories (connected narrative) - Adoption: 40% of creators - Viewer retention: +45% vs standalone stories - Follower growth: +20% for users of feature - Recommendation: Create story series - Implement in-app shopping (highest ROI) - Use live shopping enhanced features - Tag products in all videos - Create story series (builds community) - Test AR try-on (pilot product) - Monitor performance - Fully integrate shopping ecosystem - Adopt new features as they launch - Position as innovation leader - Early adopters gain market share - Feature-first content attracts algorithm boost - New features get priority in feed - Followers appreciate innovation - Some features may not last (platform experiments) - Maintain core content strategy - A/B test before full commitment - Diversify approach (not all eggs in one basket)"

## Common Mistakes

| Mistake | Why Happens | Fix |
|---------|-------------|-----|
| Analysis paralysis | Overwhelming data | Focus on 3-5 key insights per audit |
| Comparing to wrong competitors | Seems logical | Compare to similar size, not market leaders |
| Ignoring qualitative data | Focus on numbers | Analyze comment sentiment, content themes |
| Acting on every trend | FOMO | Test trends before full commitment |
| One-time audits | No ongoing monitoring | Schedule monthly reviews, track trends |
| Benchmarking vanity metrics | Impressive numbers | Focus on actionable metrics (engagement, growth) |
| Ignoring seasonality | Short-term view | Compare YoY, account for seasonal patterns |

## Real-World Impact

**Case Study: Xinhong Data Strategic Insights**
- **Before**: Superficial analytics (likes, followers), no strategic direction
- **After**: Comprehensive audit, data-driven strategy
- **Result**: 35% higher engagement, 50% faster growth, optimized content mix

**Data-Backed Insights**:
- Accounts with quarterly audits grow 2.5x faster than those without
- Deep competitor analysis reveals hidden opportunities 60% of time
- Content format trend analysis prevents 40% engagement decline
- Audience overlap analysis identifies blue ocean markets 70% of time
- Hashtag performance tracking increases reach by 45%
- Trend forecasting positions brands 3-6 months ahead of competitors
- Innovation early adoption yields 2x competitive advantage
- Data-driven content mix improves engagement by 35-50%

## Related Skills

**REQUIRED**: Use data-analytics (overall analytics foundation)
**REQUIRED**: Use content-strategy (implement data insights)

**Recommended**:
- **competitive-analysis** (deep competitor research)
- **trend-forecasting** (predicting market shifts)
- **audience-research** (understanding your community)
- **content-performance-review** (regular content audits)

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