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GEO Competitive Monitoring

See how ChatGPT, Claude, Gemini and Perplexity describe your brand and your competitors — and what it takes to be cited over them.

GEO Competitive Monitoring measures how AI models and agents actually see your brand. It runs brand×model exposure matrices, position/ladder tests, and competitive audits across ChatGPT, Claude, Gemini and Perplexity — then turns the findings into concrete GEO actions: structured data, citable summary blocks and answer-content that models can quote. If AI answers are becoming a traffic channel, this is the instrument panel for it.

What it does

Brand × model exposure matrix

A matrix of how prominently each AI model mentions your brand when asked about your category — your share of AI voice.

Position & ladder tests

Run the same prompt against models and track where your brand lands — first answer, deep in the list, or not at all.

Competitor AI visibility tracking

Monitor competitors in the same queries so you know exactly whose brand is being cited instead of yours.

Trend & alerting

AI visibility tracked over time with alerts when your brand's share of AI answers rises or collapses.

MCP readiness audit

Assess how well AI agents can understand your site through Model Context Protocol — the storefront for agent traffic.

UCP agent-commerce score

Score whether an agent can actually complete a purchase on your store — the agent-commerce conversion audit.

Citable-content diagnostics

Find which of your pages are structured and worded so models can quote them — and what's missing from the answer-ready content.

Structured data actions

FAQPage, Service, SoftwareApplication and more — concrete schema fixes that make your content machine-citeable.

Action ledger

Every finding maps to a tracked action with evidence — GEO becomes a workflow, not a curiosity.

Why it's different

vs. traditional rank tracking

Track position in AI answers across models — the channel where discovery is moving — not just the blue links.

vs. manually asking chatbots

A repeatable matrix across four models with trend and alerting — you get data, not anecdotes.

vs. generic brand monitoring

Beyond mentions: share of AI voice, ladder position, MCP readiness and agent-commerce scores.

vs. single-model checks

ChatGPT, Claude, Gemini and Perplexity behave differently — monitoring one hides most of the picture.

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