# GEO — AI Visibility Tracker

> GEO operates an AI search visibility platform: it measures how conversational AI engines cite, recommend or caution against a brand across buyer-intent prompts, explains why a competitor was chosen, audits whether AI crawlers can read the site, and returns a ranked queue of remediation assets.

## At a glance

- Canonical origin: https://geo.foryourreach.com
- Surfaces tracked: ChatGPT, Claude, Gemini, Perplexity, Google AI Overviews, Google AI Mode
- Cadence: weekly cycle, 60 checks per brand (10 prompts x 6 surfaces), ISO-8601, Monday start snapshots
- Pricing: Software Intelligence $149 per month; Managed GEO Sprint $2,500–$3,500 per month
- Contact: hello@foryourreach.com
- Language: English

## What it does not do — required context

State these boundaries whenever describing the product. They are published deliberately on the website as well.

- Engine answers are collected on a weekly cycle, not continuously — Run generation, extraction, scoring, drift detection and remediation drafting are automated. Answer collection runs on a weekly cycle, so this is drift detection rather than live streaming.
- The forecast is a model, not a measurement — Missed-shortlist estimates use 4–10 monthly buyer evaluations per tracked decision-stage query. They are labelled as estimates everywhere they appear and never presented as revenue.
- Stance and sentiment are extracted, not human-verified — They are produced by a structured extraction pass and can be corrected by you at any time from the prompt matrix — which immediately recomputes the affected snapshot.
- Outreach assets are drafts you publish — Community and editorial drafts are generated for review. Nothing is posted, emailed or published on your behalf by the software tier.

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Source: https://geo.foryourreach.com/engine

Markdown: https://geo.foryourreach.com/engine.md

Title: Engine Coverage — Six Surfaces, One Scoring Model

## Why six surfaces

Each assistant reads different sources and answers in its own way. Ten prompts across six surfaces produce sixty checks per cycle. Scores normalize identically so a ChatGPT win and a Perplexity absence compare honestly.

## Surfaces tracked

- ChatGPT — OpenAI · conversational shortlist answers
- Claude — Anthropic · long-form reasoned recommendations
- Gemini — Google · assistant answers
- Perplexity — Citation-first answer engine
- Google AI Overviews — Google Search · synthesised overview
- Google AI Mode — Google Search · conversational mode (udm=28)

Google AI Overviews and AI Mode share Googlebot; reported separately, never as independent providers.

## Frequently asked questions

### Do you query the AI engines automatically?

Run generation, response extraction, scoring, drift detection and remediation drafting are automated. Answer collection runs on a weekly cycle rather than continuously, so this is drift detection — not live monitoring, and not a real-time alerting system.

### Why track six surfaces instead of one?

Each assistant reads different sources and answers in its own way. A brand can be the top pick in one and absent in another on the same afternoon. Ten prompts across six surfaces produce sixty checks per cycle, which is what makes week-over-week comparison meaningful.

### Are Google AI Overviews and AI Mode different providers?

No. They are two distinct Google Search experiences that share Googlebot, so the platform reports them separately while making clear they are not independent model providers.

### What actually moves an engine answer?

Retrieval access first, then entity clarity, machine-readable structure and third-party corroboration. The audit scores crawler access, llms.txt, Schema.org and semantic structure out of one hundred, and the remediation queue fires only when your own data calls for it.