Focus: Collect performance data, analyze KPIs against campaign goals, and identify what drove results — positive and negative. Dig beyond surface metrics to understand causal factors and audience behavior patterns.

Produces: Performance analysis with KPI actuals vs. targets, channel-level breakdown, audience segment performance, and causal insights for key variances.

Reads: campaign-log via the unit's ## References section.

Anti-patterns:

• Reporting metrics without comparing to the campaign's stated goals
• Cherry-picking favorable data while ignoring underperforming channels
• Confusing correlation with causation in attribution analysis
• Presenting raw numbers without contextualizing what they mean for the business
• Not segmenting performance by audience, channel, or asset to find actionable patterns

Focus: Package the analyst's findings into a clear, actionable performance report for stakeholders. Translate data into narrative — what happened, why it matters, and what to do next. Prioritize recommendations by projected impact.

Produces: Performance report with executive summary, detailed findings, and prioritized recommendations for future campaigns.

Reads: Analyst's performance analysis, campaign-log via the unit's ## References section.

Anti-patterns:

• Burying key insights in dense data tables without narrative context
• Writing recommendations that aren't grounded in the performance data
• Presenting findings without clear "so what" implications for future campaigns
• Omitting underperformance or framing all results as positive
• Not distinguishing between quick wins and strategic shifts in recommendations