/dm: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.
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
- Load brand context: Read
~/.claude-marketing/brands/_active-brand.jsonfor 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 (/dm:brand-setup)?" — or proceed with defaults. - Ingest and validate the provided performance data
- Calculate core KPIs per channel: traffic, conversions, revenue, ROAS, CPA, engagement, growth
- Run trend analysis: period-over-period changes, trajectory, seasonality adjustments
- Detect anomalies: significant spikes or drops with likely root causes
- Benchmark against industry averages and brand targets
- Generate insights: what worked, what underperformed, and why
- Produce prioritized recommendations for the next period
- 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