social-analytics

v2026.09.24

Analyze social media profiles and engagement. Use when: auditing competitor social presence; calculating engagement rates; identifying top-performing content; tracking profile growth; benchmarking social metrics

GitHub
安装命令
npx skhub add guia-matthieu/social-analytics
Markdown
SKILL.md

Social Analytics

Analyze social media profiles and calculate engagement metrics - understand what content works for competitors and your own accounts.

When to Use This Skill

  • Competitor analysis - Audit competitor social presence
  • Engagement benchmarking - Calculate and compare engagement rates
  • Content analysis - Identify top-performing post types
  • Profile audit - Assess social media health
  • Reporting - Generate social performance reports

What Claude Does vs What You Decide

Claude DoesYou Decide
Structures analysis frameworksMetric definitions
Identifies patterns in dataBusiness interpretation
Creates visualization templatesDashboard design
Suggests optimization areasAction priorities
Calculates statistical measuresDecision thresholds

Dependencies

pip install click pandas requests beautifulsoup4
# For authenticated API access:
pip install tweepy instaloader

Commands

Analyze Profile

python scripts/main.py analyze @competitor --platform twitter
python scripts/main.py analyze @brand --platform instagram

Calculate Engagement

python scripts/main.py engagement @profile --platform twitter --days 30
python scripts/main.py engagement @profile --platform linkedin --posts 50

Find Top Posts

python scripts/main.py top-posts @profile --platform twitter --count 10
python scripts/main.py top-posts @profile --metric likes

Export Data

python scripts/main.py export @profile --platform twitter --format csv
python scripts/main.py export @profile --platform instagram --output report.json

Compare Profiles

python scripts/main.py compare @brand1 @brand2 @brand3 --platform twitter

Examples

Example 1: Competitor Social Audit

# Analyze competitor profile
python scripts/main.py analyze @competitor_brand --platform twitter

# Output:
# Profile Analysis: @competitor_brand
# ─────────────────────────────────────
# Followers:      45,230
# Following:      1,234
# Total Posts:    2,456
# Avg Likes:      234
# Avg Retweets:   45
# Engagement:     2.3%
# Post Frequency: 3.2/day
# Top Hashtags:   #marketing, #growth, #startup

Example 2: Benchmark Engagement Rates

# Compare engagement across competitors
python scripts/main.py compare @brand1 @brand2 @brand3 --platform twitter

# Output:
# Engagement Comparison
# ─────────────────────
# Profile         Followers   Eng.Rate   Posts/Day
# @brand1         45,230      2.3%       3.2
# @brand2         32,100      3.1%       2.1
# @brand3         89,500      1.8%       4.5

# Winner: @brand2 (highest engagement despite fewer followers)

Example 3: Find Winning Content

# Identify top performing posts
python scripts/main.py top-posts @marketing_pro --platform twitter --count 10

# Output:
# Top 10 Posts by Engagement
# ──────────────────────────
# 1. "Here's what nobody tells you about..."
#    Likes: 2,345  RTs: 456  Eng: 6.2%
#    Type: Thread  Time: Tuesday 9am

# 2. "The biggest mistake I see founders make..."
#    Likes: 1,890  RTs: 312  Eng: 4.8%
#    Type: Single  Time: Wednesday 8am

Engagement Rate Benchmarks

Twitter/X

Account SizeGoodGreatExcellent
<10K1-3%3-6%>6%
10K-100K0.5-1%1-3%>3%
100K+0.2-0.5%0.5-1%>1%

Instagram

Account SizeGoodGreatExcellent
<10K3-6%6-10%>10%
10K-100K1-3%3-6%>6%
100K+0.5-1%1-3%>3%

LinkedIn

Account SizeGoodGreatExcellent
Personal2-4%4-8%>8%
Company0.5-1%1-2%>2%

Metrics Explained

MetricFormulaWhat It Measures
Engagement Rate(likes + comments + shares) / followersOverall content resonance
Amplificationshares / followersContent virality
Conversationcomments / followersCommunity engagement
Applauselikes / followersContent appreciation

Output Formats

FormatBest For
textQuick terminal review
csvSpreadsheet analysis
jsonProgrammatic use
mdReports and docs

Skill Boundaries

What This Skill Does Well

  • Structuring data analysis
  • Identifying patterns and trends
  • Creating visualization frameworks
  • Calculating statistical measures

What This Skill Cannot Do

  • Access your actual data
  • Replace statistical expertise
  • Make business decisions
  • Guarantee prediction accuracy

Related Skills

Skill Metadata

  • Mode: centaur
category: social
subcategory: analytics
dependencies: [pandas, requests, beautifulsoup4]
difficulty: intermediate
time_saved: 4+ hours/week
发现
标签

此技能尚未发布标签。

版本
最新版本元数据

版本

v2026.09.24

发布时间

2026年9月24日

分类

未分类

许可证

MIT

源路径

skills/social/social-analytics

默认分支

main

最新提交

a69bf67

Tree SHA

55b3324