AI search is changing how decisions get made. Users are no longer scanning results. They're accepting answers. Which means: If you're not cited, you're not considered.
This glossary breaks down the terms that actually matter. Not just definitions, but what they mean in practice.
When an AI system selects your content as a source in its answer.
This is the closest equivalent to "ranking" in AI search. But it's more selective. AI doesn't show 10 options. It shows a handful. If you're not one of them, you don't exist in that moment.
Search experiences powered by large language models that return direct answers instead of links.
Examples: ChatGPT, Gemini, Perplexity, Claude.
The key shift: users are skipping the results page entirely.
The practice of making your brand more likely to be selected and cited by AI systems.
Unlike SEO, which focuses on ranking, GEO focuses on:
A measurement of how likely your brand is to be cited by AI systems.
Typically scored 0–100 based on:
Most sites score below 40. Which means: they are rarely or never cited.
This is what tools like SearchScore are designed to measure.
Your presence within AI-generated answers.
Not: rankings, impressions, traffic.
But: whether you are actually mentioned. This is the metric most teams are currently blind to.
Any factor that influences whether AI selects your content.
This includes:
Most teams optimise these in isolation. AI evaluates them together.
The process where AI retrieves information from external sources before generating a response.
This is how citations happen. AI doesn't rely purely on training data. It:
If your content is not retrieved, it cannot be cited.
Structured data that helps AI understand what your content is and how to interpret it.
Examples: Article, FAQ, Organisation, Review.
Schema does not "rank" your site. It reduces ambiguity. Which increases the chance of being selected.
The perceived credibility of the person behind the content.
AI systems increasingly look for:
Anonymous or generic content is less likely to be trusted.
How widely your brand is recognised and referenced across the web.
This includes: mentions, backlinks, press coverage, consistent positioning.
AI uses this to answer: "Is this a credible source?"
How useful your content actually is.
AI prefers:
Not: generic summaries, surface-level content.
The systems powering AI search.
Examples: GPT-4, Claude, Gemini, Llama.
They are trained on vast datasets and refined through retrieval and feedback.
These are the platforms where citations matter most.
A proposed standard for controlling how AI systems interact with your content.
Similar to robots.txt. Not widely adopted yet, but gaining traction.
The practice of surrounding your content with signals that reinforce credibility.
This includes:
It helps AI understand not just what you're saying, but why it should trust it.
SEO answers: "Can you rank?"
GEO answers: "Will AI choose you?"
Those are not the same problem.
Most teams don't know if they're visible in AI. Because there's no standard tooling. Until recently.
Platforms like SearchScore measure:
Most brands assume they show up in AI. The data usually says otherwise.
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