Aeo Geo Visibility

---
name: aeo-geo-visibility
description: "Use when making a brand cited and recommended by answer engines (ChatGPT, Perplexity, Gemini) via entity consistency, topic depth, third-party mentions, and prompt tracking. Triggers on \"aeo\", \"geo visibility\", \"answer engine\", \"ai visibility\", \"buyer prompts\". Non-triggers: classic keyword ranking only (use seo), campaign copy with no visibility tracking (use marketing-campaign). Outcome: a tracked prompt set with rising mention share plus a prioritized citation action list."
metadata:
  origin: ECC
---

# AEO GEO Visibility

Get cited and recommended by answer engines. Ranking is not the metric:
models rebuild each answer from a consideration set, so the goal is to be
considered consistently across buyer prompts, not to hold one position.

## When To Activate

- The user says AEO, GEO, AI visibility, answer engines, or "get AI to
  recommend my brand".
- The task is a brand audit (what do models say about us vs competitors).
- The task is a buyer-prompt map (awareness -> comparison -> decision).
- The task is a third-party mention plan (listicles, reviews, community).

## Workflow

1. Brand audit: ask three answer engines one fixed question - what does
   the brand do and who is it for. If answers are vague, wrong, or differ,
   fix identity first.
2. Lock identity: write one to two sentences (what it is, category, what
   it does), the ICP (who it serves, never "everyone"), and two to three
   differentiators. Standardize this wording word-for-word on the site,
   social profiles, business listings, and directories.
3. Map buyer prompts: pick ONE lane to own. List what buyers ask at
   awareness, comparison, and decision stages. Track 5+ prompts per lane,
   each bound to an ICP + product pair (answers change by asker).
4. Own with depth: for each losing prompt, publish the missing piece with
   something new (own data, firsthand results, unique take). Repeating the
   top results scores near zero on information gain.
5. Engineer third-party mentions: find where engines already pull answers
   for your prompts (peer sites, listicles, reviews, community threads).
   Contribute genuinely helpful content, pitch roundups, give people
   something worth referencing. Never spam self-promo in threads.
6. Track: run the same prompt set repeatedly per engine, record mention
   share and citation source per run, and trend over time. Single snapshots
   are noise - visibility percentage across runs is the signal.
7. Act: convert tracking into a to-do list (net-new content, social
   amplification, outreach), filtered by buyer stage and engine, and redo
   the audit monthly.

## Anti-Patterns

- Chasing a fixed "AI rank position" - order reshuffles every run.
- Publishing more generic content instead of deeper original content.
- Only optimizing owned pages while third-party consensus stays negative.
- Self-promo spam in community threads (gets removed, hurts reputation).
- One-shot measurement instead of repeated prompt tracking over time.

## Relations

- `seo`: classic search foundation (crawlable pages, meta, structure).
- `marketing-campaign`: campaign angles and copy built on the prompt map.
- `content-engine`: platform-native production for the content backlog.
- `astro-site-ops`: ships the fast site that the citations point to.

## Sources

- Google Search Quality Rater Guidelines (reputation of site and creators,

## Exemplo

```text
Prompt set: 5 prompts de comparação ("melhor CRM para clínica")
Rodada 1: citado em 1/5 (20%) — só no próprio site
Ação: publica comparativo com dados próprios + pitch p/ 2 listicles do setor
Rodada 2 (30d): citado em 3/5 (60%) — 2 via terceiros
```