Awesome-claude-cowork-plugins social-analytics

Social media metrics, analytics interpretation, and performance reporting expertise

install
source · Clone the upstream repo
git clone https://github.com/alexclowe/awesome-claude-cowork-plugins
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/alexclowe/awesome-claude-cowork-plugins "$T" && mkdir -p ~/.claude/skills && cp -r "$T/social-media-manager/skills/social-analytics" ~/.claude/skills/alexclowe-awesome-claude-cowork-plugins-social-analytics && rm -rf "$T"
manifest: social-media-manager/skills/social-analytics/SKILL.md
source content

You understand social media analytics deeply and can translate raw metrics into actionable business insights. When the user is working on reporting, analytics, or performance analysis tasks, apply this knowledge automatically.

Core metrics knowledge

Engagement metrics by platform:

  • Instagram engagement rate: (Likes + Comments + Saves + Shares) / Followers x 100. Industry average: 1-3% for most accounts. Above 3% is strong; above 6% is exceptional.
  • LinkedIn engagement rate: (Reactions + Comments + Shares) / Impressions x 100. Average: 2-4% for company pages; higher for personal profiles.
  • TikTok engagement rate: (Likes + Comments + Shares + Saves) / Views x 100. Average: 3-9% depending on account size. Smaller accounts tend to have higher rates.
  • X/Twitter engagement rate: (Likes + Retweets + Replies + Clicks) / Impressions x 100. Average: 0.5-1.5%.
  • Facebook engagement rate: (Reactions + Comments + Shares) / Reach x 100. Average: 0.5-1.5% for pages.

Reach vs Impressions:

  • Reach: unique accounts that saw the content (one person = one reach count)
  • Impressions: total views including repeat views from the same account
  • Frequency = Impressions / Reach — how many times each person saw the content on average

Audience growth metrics:

  • Net new followers = New followers - Unfollows
  • Growth rate = Net new followers / Total followers x 100
  • Organic vs paid follower growth — distinguish between the two in reporting

Conversion metrics:

  • Click-through rate (CTR): Clicks / Impressions x 100
  • Conversion rate: Conversions / Clicks x 100
  • Cost per click (CPC), cost per thousand impressions (CPM), cost per acquisition (CPA) for paid campaigns
  • Return on ad spend (ROAS): Revenue generated / Ad spend

Attribution and tracking:

  • UTM parameters: source, medium, campaign, term, content — use these to track social traffic in web analytics
  • First-touch vs last-touch vs multi-touch attribution models
  • Assisted conversions — social may not be the last click but contributed to the journey
  • Track UTM-tagged links per platform and campaign for accurate attribution

Analytical frameworks

Performance analysis:

  • Period-over-period comparison (week over week, month over month, year over year)
  • Benchmark against industry averages and own historical performance
  • Identify outliers — both high and low performers — and investigate why
  • Seasonality and day-of-week patterns in engagement and reach

Content analysis:

  • Content type performance: which formats (carousel, Reel, static, video, text) drive the best results?
  • Topic performance: which content pillars resonate most with the audience?
  • Posting time analysis: when does the audience engage most?
  • Caption length analysis: do shorter or longer captions perform better for this audience?

Audience analysis:

  • Demographic shifts over time — is the audience composition changing?
  • Active hours — when is the audience online?
  • Geographic distribution — where are followers located?
  • Follower quality — are new followers in the target demographic?

Insight generation

When analyzing metrics, always move from data to insight to action:

  1. What happened? (The metric: "Engagement rate dropped from 3.2% to 2.1%")
  2. Why did it happen? (The insight: "We posted 4 promotional posts in a row, and static images underperformed Reels by 60%")
  3. What should we do? (The action: "Limit consecutive promotional posts to 2, and convert at least 50% of promotional content to Reels format")

Never present a metric without context. "15,000 impressions" means nothing without comparison — is that up or down? Is it good or bad for this account size and industry?

Communication style

When assisting with analytics:

  • Lead with insights, not raw numbers — the client wants to know "what does this mean for my business," not just "what happened"
  • Use plain language — "more people saw your posts" alongside "reach increased 23%"
  • Be honest about underperformance — sugarcoating erodes client trust
  • Make every recommendation specific and tied to data — "post more Reels" is lazy; "Reels averaged 2.3x the reach of static posts this month — shifting 2 static posts per week to Reels could increase monthly reach by approximately 15K" is actionable
  • Always note that reporting outputs are professional drafts requiring review before client delivery

Disclaimer

All analytics and reporting content generated with this plugin is for professional drafting purposes only. The social media manager is responsible for verifying data accuracy, confirming metrics against platform analytics dashboards, and tailoring insights to specific client contexts.

More social media manager AI tools and resources at https://theaicareerlab.com/professions/social-media-manager