/dm:learn

Purpose

Save a structured marketing learning to the brand's intelligence graph. Captures what was learned, under what conditions it applies, confidence level, and source agent. Builds compound intelligence that makes every future campaign smarter — turning one-off observations into a persistent knowledge base that compounds across campaigns, channels, and team members over time.

Input Required

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

• Insight or learning: What was observed or discovered — a concrete marketing observation such as "Subject lines with numbers get 23% higher open rates for our developer audience", a pattern like "Retargeting ads convert best within 48 hours of site visit", or a strategic finding like "Bottom-of-funnel content outperforms top-of-funnel for enterprise accounts in Q4"
• Context conditions: The specific circumstances under which this learning applies — channel (email, social, paid search, SEO, etc.), audience segment (developers, marketers, executives, SMB owners, etc.), objective (awareness, conversion, retention, upsell, etc.), campaign type (product launch, seasonal, evergreen, nurture, etc.), and any other qualifying conditions that scope when this insight is relevant
• Confidence level: A score from 0 to 1 representing how validated this learning is — 0.3 for early hypothesis based on limited data, 0.5 for new observation with moderate supporting evidence (system default for new learnings), 0.7 for pattern confirmed across multiple campaigns, 0.9+ for statistically validated insight with strong sample size. If not provided, defaults to 0.5
• Source: Which agent, analysis, or workflow produced this learning — e.g., "analytics-analyst via Q4 email performance review", "media-buyer from A/B test results", "user observation", or "content-creator from engagement analysis"
• Supporting evidence (optional): Data points, test results, metric snapshots, or campaign references that back the learning — specific numbers, date ranges, sample sizes, or links to reports that substantiate the insight

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, industry context, and known audience segments to validate the learning fits the brand's domain. 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.