/performance-report

name: performance-report
description: "Turn marketing data into a stakeholder-ready performance report: executive summary, channel-by-channel KPI dashboard, trend analysis, anomaly alerts with root-cause hypotheses, and recommendations ranked by expected impact — formatted for an executive or tactical audience. Triggers on \"/digital-marketing-pro:performance-report\", \"write the monthly performance report\", \"summarize campaign results for stakeholders\", \"why did performance change last quarter\", \"turn these metrics into a report\". Consumes snapshots persisted by /digital-marketing-pro:performance-check rather than re-pulling platforms itself; reads the brand profile, custom templates, and agency SOPs. Hands deeper anomaly diagnosis to /digital-marketing-pro:anomaly-scan."
argument-hint: "[time-period]"

/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