/digital-marketing-pro:performance-report

Purpose

Generate a structured marketing performance report that transforms raw data into insights. Covers KPI tracking, trend analysis, anomaly detection, and prioritized recommendations for optimization.

Scope (vs /digital-marketing-pro:performance-check): this skill is the narrative formatting layer — it turns metrics into a stakeholder-ready deliverable (executive summary, channel commentary, trend narrative, prioritized recommendations, audience-appropriate formatting). It consumes the live pulls and persisted snapshots that /digital-marketing-pro:performance-check produces rather than re-pulling from the platforms itself. Use performance-check to see the numbers now; use performance-report to tell the story. For deeper anomaly diagnosis, hand off to /digital-marketing-pro:anomaly-scan.

Input Required

The user must provide (or will be prompted for):

• Reporting period: Date range for the report
• Channels to cover: Which marketing channels to include (all, or specific ones)
• Data source: Raw data (paste, CSV, or connected platform)
• KPIs of interest: Specific metrics to focus on (or use defaults for the channel)
• Comparison period: Previous period, YoY, or custom benchmark
• Audience: Who will read the report (executive summary vs. tactical detail)

Process

1. Load brand context: Read ~/.claude-marketing/brands/_active-brand.json for the active slug, then load ~/.claude-marketing/brands/{slug}/profile.json. Apply brand voice, compliance rules for target markets (skills/context-engine/compliance-rules.md), and industry context. Also check for guidelines at ~/.claude-marketing/brands/{slug}/guidelines/_manifest.json — if present, load restrictions and relevant category files. Check for custom templates at ~/.claude-marketing/brands/{slug}/templates/. Check for agency SOPs at ~/.claude-marketing/sops/. If no brand exists, ask: "Set up a brand first (/digital-marketing-pro:brand-setup)?" — or proceed with defaults.
2. Ingest and validate the provided performance data
3. Calculate core KPIs per channel: traffic, conversions, revenue, ROAS, CPA, engagement, growth. Break out GA4's "AI Assistant" default channel (referrals from ChatGPT, Gemini, Copilot, Perplexity, etc.) as its own line so AI-sourced traffic and conversions are visible rather than folded into Referral/Direct
4. Run trend analysis: period-over-period changes, trajectory, seasonality adjustments
5. Detect anomalies: significant spikes or drops with likely root causes
6. Benchmark against industry averages and brand targets
7. Generate insights: what worked, what underperformed, and why
8. Produce prioritized recommendations for the next period
9. Format report for the specified audience (executive vs. tactical)

Output

A structured performance report containing:

• Executive summary with headline metrics and overall assessment
• Channel-by-channel KPI dashboard with period-over-period comparison
• Trend analysis with visualizable data points
• Anomaly alerts with root cause hypotheses
• Top wins and underperformers with context
• Actionable recommendations ranked by expected impact
• Next period goals and focus areas

Agents Used

• analytics-analyst — Data analysis, KPI calculation, trend detection, anomaly identification, recommendations