acrid-auto/skills/analytics

Analytics Skill

name: analytics
description: Reads the consolidated analytics dashboard, generates insights, makes recommendations, and feeds metrics into operational decisions. Acrid's data brain.

Purpose

Turn raw numbers into decisions. The Analytics Collector fills the JSON. This skill reads it and tells Acrid what matters, what's broken, and what to do next.

Not a dashboard. Not a report generator. This skill exists to make Acrid's content, product, and distribution decisions data-driven instead of vibes-driven.

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When It Runs

| Trigger | Mode | What It Does | |---------|------|-------------| | Session start | Lightweight | Read dashboard, flag anomalies (revenue event, traffic spike, broken API) | | /heartbeat | Summary | Key metrics in 3 lines — traffic, revenue, content output | | /ops | Feed | Push metrics into cockpit scoreboard update | | On-demand | Full | Complete analysis with insights and recommendations |

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Pre-Execution Checklist

1. Read memory/analytics-dashboard.json completely
2. Check last_updated — if older than 24h, run Analytics Collector agent first
3. Read memory/content-log.md for recent post context
4. Read site-config.json for current product/revenue state

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What It Produces

1. Metrics Summary (every run)

ANALYTICS | 7d: {visitors}v / {pageviews}pv / {bounce_rate}% bounce
REVENUE | All-time: ${total} | 30d: ${last_30d} | Sales: {count}
CONTENT | 7d: {posts} posts | Blog: {blog_count} | Learn: {learn_count}
EMAIL | {subscribers} subscribers ({real_count} real, {test_count} test)
SPEND | ${monthly_total}/mo | RPD: ${revenue_per_dollar_spent}

2. Anomaly Flags (when detected)

• Traffic spike or drop (>30% change week-over-week)
• New revenue event (any sale)
• API failure in collection_log
• Spend anomaly (new charge, unexpected increase)
• Content gap (0 posts in 48+ hours)
• Funnel break (high traffic page with zero conversion flow)

3. Insights + Recommendations (full mode)

• What's working (top traffic sources, top pages, converting paths)
• What's not working (low-traffic channels, dead pages, attribution gaps)
• Specific next actions with expected impact
• Unit economics analysis (cost per output, revenue per dollar)

4. Cockpit Feed (during /ops)

Update these fields in infrastructure/launch-cockpit.md:

• Scoreboard: visitors, revenue, posts, products, subscribers
• Any new wins or blockers from analytics data

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Rubric

Score each analytics run 0-100:

| Criteria | Weight | What "Good" Looks Like | |----------|--------|----------------------| | Data freshness | 20 | Dashboard updated within 24h, all APIs succeeded | | Accuracy | 25 | Numbers match API responses, no stale/fabricated data | | Insight quality | 25 | Findings are specific and actionable, not generic ("post more") | | Recommendations | 20 | Each recommendation has a clear next action and expected outcome | | Brevity | 10 | Full analysis in under 500 words. No fluff. |

Minimum passing score: 70. Below 70, re-run with better data or sharper analysis.

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Analysis Framework

When generating insights, work through these lenses:

1. Traffic → Source → Action: Which sources drive visitors? What content feeds those sources? Do more of what works.
2. Funnel → Leak → Fix: Homepage → Product page → Purchase. Where do people drop off? Fix the biggest leak.
3. Content → Traffic → Revenue: Which content types drive traffic that converts? Kill content types that don't connect to revenue.
4. Spend → Output → ROI: What does each unit of content cost? Is the return positive or negative? Where's the best margin?
5. Trend → Direction → Bet: Week-over-week, what's growing? What's shrinking? Double down or cut.

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History & Trends

The dashboard JSON has a history array with weekly snapshots. When analyzing:

• Compare current week to previous weeks
• Flag trends (3+ weeks of growth or decline in any metric)
• Calculate week-over-week change percentages
• Note inflection points (when did a metric start moving?)

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Rules

• Never fabricate data. If the dashboard is stale, say so. Run the collector, don't guess.
• Be specific. "Reddit drove X visitors" not "social media is performing well."
• Recommend actions, not observations. "Post 2 more Reddit replies in r/ClaudeCode this week" not "Reddit seems to be working."
• Include the number. Every insight must reference a specific metric.
• Don't over-analyze small samples. 1 week of data is a snapshot, not a trend. Say so.
• Update site-config.json if revenue or product stats changed.
• Append to LEARNINGS.md after every full analysis run.

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Failure Conditions

This skill has failed if:

• It reports metrics that don't match the dashboard JSON
• Recommendations are generic ("post more content", "improve SEO")
• It takes more than 500 words for a full analysis
• It doesn't flag a broken API or stale data
• It runs without checking data freshness first
• Insights don't connect to revenue or distribution

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Integration Points

• Thread Writer: Check which pillars drive the most traffic via source breakdown
• Reddit Engine: Validate Reddit as top referral source, prioritize subreddits by traffic
• DITL Writer: Include analytics highlights in daily blog when notable
• Marketing Engine: Feed top-performing content types into marketing decisions
• Ops Manager: Provide scoreboard numbers for cockpit update

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The skill that turns "I think Reddit works" into "Reddit drove X% of traffic, Y% of revenue, and here's what the attribution gap means."

LEARNINGS.md