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 Does You Decide

Structures analysis frameworks Metric definitions

Identifies patterns in data Business interpretation

Creates visualization templates Dashboard design

Suggests optimization areas Action priorities

Calculates statistical measures Decision 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 Size Good Great Excellent

<10K 1-3% 3-6%

6%

10K-100K 0.5-1% 1-3%

3%

100K+ 0.2-0.5% 0.5-1%

1%

Instagram

Account Size Good Great Excellent

<10K 3-6% 6-10%

10%

10K-100K 1-3% 3-6%

6%

100K+ 0.5-1% 1-3%

3%

LinkedIn

Account Size Good Great Excellent

Personal 2-4% 4-8%

8%

Company 0.5-1% 1-2%

2%

Metrics Explained

Metric Formula What It Measures

Engagement Rate (likes + comments + shares) / followers Overall content resonance

Amplification shares / followers Content virality

Conversation comments / followers Community engagement

Applause likes / followers Content appreciation

Output Formats

Format Best For

text

Quick terminal review

csv

Spreadsheet analysis

json

Programmatic use

md

Reports 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

• content-repurposer - Repurpose top-performing content

• hashtag-analyzer - Deep dive into hashtag performance

Skill Metadata

• Mode: centaur

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