Reference

The vocabulary of AI-native marketing

A precise glossary for the AI visibility discipline. If a vendor uses these words loosely, ask harder questions.

The discipline of structuring content so it becomes the cited answer inside AI assistants like ChatGPT and Perplexity. Successor to SEO.

Optimizing for generative answers across LLMs. Focuses on inclusion in synthesized responses, not link rankings.

Practical playbook for being indexed, cited, and recommended by large language models. Covers citation surface, training data, and retrieval.

The umbrella metric: what % of category-relevant prompts mention your brand across major LLMs, weighted by sentiment and position.

Your brand's mention rate vs. competitors across a defined set of commercial-intent prompts. The AI-era version of SOV.

The aggregate of pages, schema, structured data and authoritative references an LLM can pull when synthesizing an answer about your brand.

Automated infrastructure that generates and runs thousands of commercial-intent prompts across multiple LLMs to measure brand presence.

Engineering brand-adjacent content and structured signals so LLMs interpret your brand within the desired category and use case.

Mapping the chain: LLM mention → click → user decision → purchase → revenue. Required to measure ROI of AI visibility work.

A framework for tracking and optimizing brand presence across heterogeneous models (GPT, Claude, Gemini, Perplexity, Yi/01.AI).

When an LLM invents a competitor or misattributes your category. A correctable failure mode of poor citation surface.

A go-to-market model where the AI answer is the first touchpoint — replacing the search-result-first funnel of web 2 marketing.

One last thing

If AI doesn't recommend you, your business is already invisible.

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