AEO/GEO Strategy Setup

3-phase roadmap. Each phase delivers value standalone — stop after any phase. See REFERENCE.md for theory (4-stage funnel, 7-step framework, channel guide, schema injection per stack).

Phase 1 — Measure (Week 1)

Goal: know where the brand stands in AI answers today.

1. Interview user for 5 candidate questions a customer would ask AI without naming the brand. Examples:
   • "Best <category> for <use case>?"
   • "<competitor A> vs <competitor B> — which is better?"
   • "Is <category> safe / legal / reliable?"
2. Warn user about workload: "5 questions × 3 AIs × 3 runs = 45 incognito queries. Roughly 1–2 hours. Three runs are required for statistical significance — AI answers are probabilistic."
3. Generate templates/share-tracker.csv with the 5 questions filled in.
4. After user fills CSV, run scripts/calculate-share.py — outputs share %, ranking, stage (risk / growth / compete / dominate), sentiment breakdown, and writes a dated markdown report to reports/YYYY-MM-DD.md.

Stage thresholds: 0–10% risk · 10–30% growth · 30–50% compete · 50%+ dominate.

Phase 2 — Define (Weeks 2–4)

Goal: a single canonical sentence used everywhere.

1. Interview 5 slots one at a time:
   • Company name: legal + alternate name
   • Target customer: who specifically
   • Concrete metric/outcome: numbers, not adjectives ("3만 명 작가" not "many artists")
   • Core value: what they get
   • Category: noun phrase that names the market
2. Assemble: [Company] is a [category] for [target customer], delivering [core value] backed by [metric/outcome].
3. Save to entity-definition.md at project root. Tell user: "Use this verbatim on website, press releases, LinkedIn. Inconsistency = AI sees multiple companies."
4. Distribution checklist (short term — open web, low entry barrier):
   • Namu Wiki entry (Korean brands)
   • Medium / Brunch posts (10+)
   • LinkedIn company page + founder profile
   • Crunchbase company entry
   • Press releases via wire services
   • YouTube videos with subtitles + descriptions
5. Long-term goals (12+ months, see REFERENCE.md):
   • Wikipedia entry (only after meeting notability — 5+ independent reliable sources)

Phase 3 — Systematize (Weeks 5–8)

Goal: schema markup + ongoing monitoring loop.

1. JSON-LD Organization schema: scaffold templates/organization-schema.json.
   • Required: name, url, description (reuse Phase 2 sentence verbatim), sameAs (social/wiki URLs)
   • Optional: logo, foundingDate, founder, numberOfEmployees, areaServed, knowsAbout
   • Detect site stack from package.json / composer.json / wp-config.php. Show injection guide from REFERENCE.md for that stack (Next.js, WordPress, static HTML).
2. Monthly monitor: append rows to single accumulating templates/monitoring.csv — same 5 questions plus brand-name probes. Each month adds 24 rows with month=YYYY-MM.
3. After 2+ months, run scripts/track-trend.py — share % delta per AI, sentiment shift, action triggers, dated markdown report.

Operating Rules

• No brand-name in Phase 1 questions: customers don't search by your brand. Strip any candidate that includes it.
• Numbers beat adjectives: refuse vague metric slots in Phase 2. "fast delivery" → "within 1 hour citywide".
• Open web only: never recommend login-walled platforms (private Slack, app-only content). AI cannot read them.
• Reuse Phase 2 sentence: description field in schema and bios must match it character-for-character.
• Single accumulating CSV: monitoring.csv grows over time. Never split per month.

Quick Start

User says "set up GEO for our brand":

1. Phase 1 → measure first. Confirm CSV results before moving on.
2. Ask: "Continue to Phase 2 (entity definition)?"
3. Continue phase by phase until user stops.

Reference

• Theory + channel guide + schema injection per stack: REFERENCE.md
• Share tracker: templates/share-tracker.csv
• Schema scaffold: templates/organization-schema.json
• Accumulating monitor: templates/monitoring.csv
• Share calculator (writes reports/): scripts/calculate-share.py
• Trend tracker (writes reports/): scripts/track-trend.py