/dm:geo-monitor

Purpose

Monitor and track brand visibility across generative AI engines. Systematically test how AI platforms respond to queries relevant to the brand, score visibility using a structured rubric, track changes over time, and identify opportunities to improve AI presence. This command provides a repeatable, quantitative framework for understanding where and how the brand appears (or fails to appear) in AI-generated responses — giving marketers the data they need to optimize for the emerging generative engine optimization (GEO) channel. Supports baselining, trend tracking, competitive benchmarking, and narrative alignment checks across all major AI platforms.

Input Required

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

• Target queries to test: Organized by intent type — brand queries ("What is [brand]?"), product queries ("[brand] [product] features"), comparison queries ("[brand] vs [competitor]"), and category queries ("best [category] tools"). Minimum 5 queries recommended for meaningful scoring. If not provided, the command will generate a default query portfolio based on the brand profile
• AI platforms to monitor: ChatGPT, Perplexity, Gemini, AI Overviews, and Copilot — default is all five. The user can narrow to specific platforms if they only care about certain engines or have limited testing capacity
• Monitoring frequency: weekly or monthly — determines how often the brand should be re-tested and how trend data is bucketed. Weekly is recommended for active optimization campaigns, monthly for steady-state monitoring
• Competitor brands to benchmark against (optional): One or more competitor brand names to test with the same query portfolio — enables side-by-side visibility scoring to understand relative AI presence. If omitted, the report focuses solely on the user's brand without competitive context

Process

1. Load brand context: Read ~/.claude-marketing/brands/_active-brand.json for the active slug, then load ~/.claude-marketing/brands/{slug}/profile.json. Extract brand name, product names, category, key differentiators, and desired positioning to inform query portfolio and narrative alignment scoring. Also check for guidelines at ~/.claude-marketing/brands/{slug}/guidelines/_manifest.json — if present, load brand voice and messaging constraints. If no brand exists, ask: "Set up a brand first (/dm:brand-setup)?" — or proceed with defaults.
2. Define query portfolio: Organize target queries by intent type — informational (what is, how does), navigational (brand-specific), transactional (buy, pricing, sign up), and comparison (vs, alternatives, best). If the user provided queries, classify them into these buckets. If not, generate a balanced portfolio of 10-20 queries from the brand profile covering all four intent types. Each query is tagged with its type for segmented scoring.