# 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. --- Source: https://geo.foryourreach.com Markdown: https://geo.foryourreach.com/index.md Title: AI Visibility Tracker — Overview ## What this is, in plain English It is a weekly report on how AI assistants describe a business. We ask the same questions its buyers ask, record which tools ChatGPT, Claude, Gemini, Perplexity and Google’s AI answers recommend, and explain exactly why the brand was left out when it was. Then we hand over the fixes, ranked so the fastest and highest-impact ones come first. ## What the customer gets - See what every major AI assistant says about the brand, in one place. - Know the exact reason a competitor was recommended instead. - Get each fix drafted, ranked by how quickly it pays off. - Hear about a wrong or damaging claim while it is still fixable. - Prove to a board what changed, with a before and after. - Feed the same numbers to their own tools through an API. ## The problem this solves Conversational AI engines answer buying questions with a two-to-three option shortlist and a rationale instead of a page of links. A brand outside that shortlist is excluded from the evaluation before it is ever visited, and no impression, click or analytics event records the loss. ## What the platform measures - Recommendation stance per answer: First choice, Recommended, Alternative, Mentioned only, Cautioned against. - Position weight: 1 / log₂(position + 1), so a first mention counts a full unit and a third mention about half. - Stance multipliers: First choice x1.25, Recommended x1.00, Alternative x0.75, Mentioned only x0.50, Cautioned against x0.00. - Weighted visibility score: min(100, Σ (position weight × stance multiplier × sentiment modifier × category stage weight) ÷ (engines × 1.375) × 100). - Citation share: min(100, citing answers ÷ (tracked prompts × 6) × 100). ## The five remediation tiers, ranked by time to value - Tier 1 — Objection-Buster FAQ (5 minutes): A ≤45-word direct answer to the exact objection the engine raised, plus FAQPage JSON-LD. - Tier 2 — llms.txt production asset (5 minutes): A complete /llms.txt file: proposition, capability matrix, pricing, key pages, contact. - Tier 3 — Entity disambiguation (10 minutes): Organization JSON-LD with sameAs slots and step-by-step placement instructions. - Tier 4 — Versus blueprint (2 hours): An honest comparison page with a capability matrix, when-to-choose-each, and migration friction. - Tier 5 — Citation authority outreach (Ongoing): A non-promotional, affiliation-disclosing contribution draft for the source that decided the answer. ## What changes when you act Marking an action complete locks the current visibility score as its baseline. The next complete weekly cycle writes a measured after-value onto that action. Actions without a second cycle report as awaiting measurement rather than as a win. ## Frequently asked questions ### What is AI search visibility, and why does it matter now? AI search visibility is whether conversational engines name your brand when a buyer asks for a recommendation. Instead of ten blue links, ChatGPT, Claude, Gemini, Perplexity and Google AI surfaces return a two-to-three option shortlist. If you are not in it, no click, no impression and no analytics event records the loss — the buyer simply never learns you exist. ### How does GEO measure it? Each brand tracks ten grounded buyer-intent prompts across six AI surfaces, producing sixty checks per weekly cycle. Every check yields a recommendation stance, a sentiment, a position and a citation list. Visibility is position-weighted and stance-weighted, then normalised to a 0–100 score so it is directly comparable week over week. ### What is the difference between SEO, AEO and GEO? SEO optimises for a ranked list of links. AEO optimises to be the extracted answer. GEO optimises to be the source a generative engine reasons over and cites. The same foundations serve all three, but AEO and GEO weight structure, crawler access, entity clarity and third-party corroboration far more heavily than keyword density. ### Does the platform 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. ### What do you actually do about a bad result? Every gap becomes a ranked asset with an effort badge, ranked by time to value: a five-minute objection-buster answer, an llms.txt file, entity disambiguation schema, a versus blueprint, then citation authority outreach. Each one ships with draft copy you can paste or hand to our engineers. ### Can our own agents and tools read the data? Yes. The platform exposes a Model Context Protocol server at /api/mcp with six brand-scoped tools covering citation reports, prompts, sources and the action queue, authenticated with per-brand bearer tokens so an engineering agent can pull visibility data into your own workflows.