Terms We Are Known For
These are the core terms we use when we talk about AI visibility and business identity. Each definition is written in plain English so owners can follow the same language we use across Business Visibility Group.
-
Business identity concepts
-
Search Presence Engineering
Search Presence Engineering is the process of engineering a business identity so AI systems and Google can consistently interpret, classify, and recommend it. It focuses on structured clarity, entity alignment, and trust signals, not keyword tricks or link schemes.
-
Unified Visibility
Unified Visibility is the state where a business is recognized consistently across search engines, AI systems, maps, and discovery platforms, instead of appearing as disconnected or incomplete versions of itself.
-
AI Identity
AI Identity is how AI systems currently see and label a business based on the signals they collect and trust.
-
AI Identity Engineering
AI Identity Engineering is the process of defining and structuring a business so AI systems can accurately recognize, understand, and recommend it.
-
AI Understanding
AI Understanding is the level of clarity AI systems have about what a business does, who it serves and where it fits.
-
AI Business Identity
AI Business Identity is the structured picture of a business that AI uses to decide when it is a safe match for a query.
-
Multi Model Visibility
Multi Model Visibility is the ability for a business to appear consistently in answers across several AI models and search surfaces.
-
AI Clarification
AI Clarification is the work of correcting confusing or incomplete signals so AI tools stop guessing and start recognizing the right business.
-
AI Disambiguation
AI Disambiguation is removing conflicts in online information so AI systems stop mixing one business with others that look or sound similar.
-
Identity Signals
Identity Signals are the specific data points that tell AI who a business is, such as name, location, category and service focus.
-
Visibility Signals
Visibility Signals are the patterns that tell AI where and how often a business appears across sites, listings, content and platforms.
-
Digital Identity Clarity
Digital Identity Clarity is a state where major profiles, pages and citations tell the same clear story about a business.
-
-
Industry terms and how we define them
-
Entity Optimization
Entity Optimization is shaping how a business is represented as an entity in search and AI systems so it is easier to trust and show.
-
Entity Mapping
Entity Mapping is laying out every place a business appears online and aligning them so AI sees one consistent entity instead of scattered fragments.
-
Brand Entity Optimization
Brand Entity Optimization is making sure a brand is recognized as the same business across platforms so AI does not split or dilute its authority.
-
Digital Footprint Optimization
Digital Footprint Optimization is cleaning up and strengthening everywhere a business appears online so its presence looks stable and reliable to AI.
-
-
New terms we introduced to this work
- Clear entity recognition and category placement
- Higher confidence for AI systems when selecting a business to mention
- More consistent business facts across AI summaries and citations
- Better inclusion in recommendation style answers
-
GEO
Business Visibility Group describes GEO as Generative Engine Optimization. It is the work that helps generative AI engines read, understand, and show a business with the right facts when users ask related questions. GEO focuses on how models reuse a business identity, not on ranking pages.
-
AI Discovery Optimization
AI Discovery Optimization is adjusting signals so AI systems can actually find and consider a business when they build answer sets.
-
AIO
AIO literally stands for Artificial Intelligence Optimization. It is the work that shapes how AI systems read and reuse the facts about a business across their written answers.
-
Multi Model Inclusion
Multi Model Inclusion is ensuring a business is eligible to appear inside more than one major AI model, rather than depending on a single system.
-
AI Interpretation Layer
AI Interpretation Layer is the quiet layer where AI tools decide what a business really is before they choose to show or skip it.
-
AI Trust Signals
AI Trust Signals are patterns that tell AI a business is safe to recommend, such as consistent details, citations and real world proof.
-
AI Context Signals
AI Context Signals are clues that tell AI when a business is the right fit for a specific situation, search intent or buyer problem.
-
AI Signal Stacking
AI Signal Stacking is intentionally layering multiple clear signals so AI tools see a strong, aligned picture instead of weak scattered hints.
-
AI Identity Framework
AI Identity Framework is the structured model Business Visibility Group uses to define how a business should look to AI across identity, signals and presence.
-
Model Ready Identity
Model Ready Identity is a version of business identity that is clean, consistent and ready for direct use inside modern AI models.
-
Business Context Modeling
Business Context Modeling is describing where a business fits in its market so AI can match it to the right buyers and questions.
-
Cross Model Presence
Cross Model Presence is the outcome where a business reliably shows up inside several major AI systems instead of only one.
-
AI Alignment Strategy
AI Alignment Strategy is the plan for bringing business identity, content and citations into line with how modern AI tools read the web.
-
AI Identity Structure
AI Identity Structure is the way identity elements are arranged so AI can see a complete business instead of disconnected pieces.
-
AI Footprint Modeling
AI Footprint Modeling is designing the overall online presence of a business so AI systems see a stable long term trustworthy footprint.
-
Interpretive Layer Visibility
Interpretive Layer Visibility is how visible a business is at the decision layer where AI chooses which entities to trust and include in answers.
-
Intent Match Clarity
This describes how clearly a business aligns with the intent of a user's question inside AI systems. The stronger the clarity, the more likely the model is to reuse the right facts in its written answers.
AI SEO (AI Search Visibility)
Definition: AI SEO is the work of making a business eligible to be understood, trusted, and recommended inside AI driven search and answer engines such as ChatGPT, Gemini, Perplexity, Claude, and Google AI Overviews.
How we use this term: Business Visibility Group uses AI SEO to mean visibility work designed for machine interpretation, not legacy ranking tricks. AI SEO focuses on entity clarity, identity consistency, structured signals, and corroboration across trusted sources so AI systems can reuse accurate facts about a business.
Why this definition matters: As AI replaces informational search, being “findable” is no longer enough. If AI systems cannot confidently classify what a business is, what it does, and who it serves, the business will be excluded from recommendation sets even if the company has a strong website.
What AI SEO is not: AI SEO is not link building campaigns, keyword density, or publishing generic blog posts to chase rankings. Those tactics were built for traditional Google search, not AI answer engines.
What AI SEO improves: