The AI search glossary

AI brand visibility is how often and how favorably AI assistants name your brand when answering buyer questions. Learn how to measure and improve it.

AI search market share is each AI assistant's slice of total AI search usage. Learn how it is measured, why sources disagree, and how to use it.

AI search monitoring is the ongoing practice of tracking what AI engines say about your brand. Learn how it works, what to track, and how often to run it.

AI search visibility is how present your brand is in AI search surfaces like AI Overviews, AI Mode, and Perplexity. Learn how it differs from model knowledge.

AI search volatility is how much AI answers change between runs and over time. Learn what causes it and how to measure visibility despite it.

AI traffic is website visits that come from AI assistants like ChatGPT and Perplexity, plus the crawler visits those engines make. Learn how to track both.

AI visibility is how present your brand is across AI assistants: mentioned, cited, and described accurately. Learn the three types and how to measure each.

An AI visibility audit measures how often AI engines name and cite your brand, then identifies what to fix. Learn what a real audit checks and what to ignore.

Alt text describes an image for people who cannot see it and for machines that cannot interpret it. Learn how to write it and when to leave it empty.

Anchor text is the clickable words in a link, and it tells engines what the destination covers. Learn the types and how to write it well.

Answer share is the percentage of tracked AI answers where your brand appears. Learn the formula, how it differs from share of voice, and how to measure it.

Article schema tells engines who wrote a page, when it was published, and when it changed. Learn the required properties and why freshness signals matter.

A brand mention is any instance of your brand's name appearing in an AI answer, linked or not. Learn how mentions are tracked and why they matter.

Brand sentiment is how positively or negatively people and AI engines describe your brand. Learn how sentiment is measured, scored, and improved.

BreadcrumbList schema tells engines where a page sits in your site hierarchy. Learn how to implement it and why deep pages depend on it.

A canonical URL tells engines which version of duplicate pages is the real one. Learn how rel=canonical works and the mistakes that hide pages entirely.

Citation accuracy is whether AI engines represent your cited pages correctly. Learn how to audit it, what causes errors, and how to fix them at the source.

Citation frequency is how often AI engines cite your pages as sources. Learn how it is calculated, what it reveals, and how it differs from mention rate.

A citation gap is the set of sources AI engines cite for competitors but never for you. Learn how to find yours and turn it into an outreach target list.

Citation intelligence is the practice of analyzing AI citation data to decide where to publish and what to fix. Learn what it covers and how teams use it.

Citation monitoring tracks when AI engines cite your pages as sources in their answers. Learn what to measure, how tracking works, and which metrics matter.

Citation velocity is the rate at which your AI citations grow or decline over time. Learn how to calculate it and why it moves before your visibility does.

Click-through rate (CTR) is the share of people who click after seeing your ad or listing. Learn the CTR formula, current benchmarks, and how to improve it.

Competitive displacement is winning a customer by replacing a competitor's product that is already in use. Learn how displacement deals work and how to run them.

Core Web Vitals are Google three metrics for loading, interactivity, and visual stability. Learn the thresholds and how much they affect rankings.

Crawl budget is how many pages a crawler fetches from your site in a period. Learn what sets it, when it matters, and how to stop wasting it.

Deduplication is how engines collapse duplicate pages into one representative version. Learn how selection works and how to control which page wins.

A deep page sits several clicks from the homepage and carries specific detail. Learn why deep pages get cited by AI engines more than homepages do.

Faceted navigation lets users filter listings by attributes, and it multiplies URLs fast. Learn how to keep it useful without flooding the index.

FAQ schema marks up question and answer pairs on a page. Learn the rules, what changed with rich results, and why AI engines still read it.

First-party data is information you collect directly from your own customers and channels. Learn how it differs from second, third, and zero-party data.

Heading hierarchy is the ordered structure of H1 to H6 tags on a page. Learn the rules and why AI engines lift content by heading.

HowTo schema marks up step-by-step instructions for machines. Learn the properties, what changed with Google rich results, and when it is still worth adding.

ImageObject schema describes an image to machines: dimensions, caption, licence, and creator. Learn when it matters and how it differs from alt text.

Index coverage is the share of your pages engines have actually indexed. Learn how to read the report and what the common exclusion reasons mean.

INP measures how quickly a page responds visually to user input. Learn the thresholds, why it replaced FID, and how to improve a failing score.

Internal linking connects your own pages to spread authority and aid discovery. Learn how to structure it and why orphan pages never get cited.

JavaScript SEO is making script-dependent sites crawlable and indexable. Learn the rendering problem and why AI crawlers make it urgent again.

JSON-LD is the recommended format for adding structured data to a page. Learn how it compares to Microdata and RDFa, and why engines prefer it.

A jump link moves a reader to a section within the same page using an anchor. Learn how to build them and why engines use them for passage links.

LLM visibility is how often and how favorably large language models mention your brand in their answers. Learn how to measure it and what moves it.

LLMs.txt is a proposed file that gives AI models a curated map of your site in markdown. Learn what it contains, who supports it, and whether to add one.

Markdown is a plain-text formatting syntax that converts to HTML. Learn the basic syntax and why AI systems consume content in markdown.

Mention frequency is how often your brand is named across web sources and AI answers in a period. Learn how to measure it and where the number misleads.

A meta description summarises a page for search results. Learn the length limits, why Google rewrites them, and what AI engines do with them.

Noindex tells engines to keep a page out of the index. Learn how it differs from robots.txt disallow and why combining the two backfires.

Open Graph tags control how your pages look when shared on social platforms. Learn the required properties and why link previews break without them.

Page experience is the Google grouping of signals about how a page feels to use. Learn what it includes now and what changed when the report was retired.

Product schema marks up price, availability, and reviews so engines can quote them. Learn the required properties and why AI engines repeat what it says.

Prompt intelligence is knowing which questions buyers ask AI engines and how those answers behave. Learn how to build a prompt set and why it beats keywords.

Prompt-market fit is the alignment between the prompts buyers ask AI engines and the proof your brand supplies. Learn how to measure and close the gap.

Robots.txt tells crawlers which parts of your site they may fetch. Learn the syntax, the AI crawler rules, and the mistake that hides you from AI answers.

Schema markup is the shared schema.org vocabulary that labels what your page content means. Learn the main types, how to add it, and what it earns you.

Semantic HTML uses elements that describe their meaning, not their appearance. Learn which elements matter and why parsers depend on them.

Server-side rendering builds the HTML on the server before sending it to the browser. Learn how SSR works, how it differs from CSR, and why AI crawlers need it.

Share of voice is your brand's share of all conversation in a market, including AI answers. Learn the formula, what it predicts, and how to measure it.

Structured data is machine-readable markup that tells search and AI engines what your page means. Learn how it works and why AI answers depend on it.

Synthetic traffic is automated, scripted traffic that a tool sends to a website, API, or network on a schedule instead of real users. Teams use it to test uptime, speed, and key flows before a customer notices a problem.

URL parameters pass data in the query string and multiply crawlable addresses. Learn the types and how to stop them fragmenting your site.

X-Robots-Tag delivers indexing directives in the HTTP header, so it works on PDFs and images. Learn the syntax and when to use it over a meta tag.

An XML sitemap lists the URLs you want crawlers to find, with last-modified dates. Learn how to build one and what it does and does not guarantee.