METHODOLOGY · POSITION 0
Position 0 Glossary
Every metric, methodology term, and scoring dimension used across Position 0's work is defined here. If you've received an AI Visibility Snapshot or are evaluating the P0 Protocol, this is the reference page for what the numbers mean and how they're calculated.
01 - AI Search
AI Search and Visibility
AI Search
The category of search behavior where users query an AI system — ChatGPT, Perplexity, Gemini, Google AI Overview, or Google AI Mode — and receive a generated answer rather than a list of links. In AI search, the system synthesizes a response from content it has crawled, indexed, and assigned credibility to. The brands and sources cited in those responses occupy a new category of visibility that operates independently of traditional search rankings.
AI Presence
The percentage of tracked AI-generated responses in a given category that include a specific brand mention. Measured across a defined set of prompts relevant to the brand's product category, AI presence is the most direct indicator of how often a brand is being recommended by AI systems. A brand with 3.72% AI presence appears in roughly 37 out of every 1,000 tracked AI responses in its category. AI presence is influenced by content depth, technical crawlability, and third-party citation volume — not by ad spend or search ranking alone.
AI Citation
A specific instance of an AI system referencing or recommending a brand, product, or piece of content within a generated response. Citations are the currency of AI search visibility. AI systems build citation patterns over time based on which sources they encounter consistently across crawlable content and third-party references. A brand that earns citations across multiple AI platforms for the same category of query is building durable AI visibility.
AI Crawlability
The degree to which AI systems can access, read, and parse a brand's web content. A page that is dynamically rendered — meaning its content loads in the browser rather than being served as static HTML — may appear fully functional to a human visitor while being nearly invisible to an AI crawler. AI crawlability is a prerequisite for AI visibility: content that cannot be read cannot be cited, regardless of how relevant or well-written it is.
Generative Engine Optimization (GEO)
Also referred to as GEO. The practice of optimizing a brand's web presence, content, and authority signals to improve its visibility and citation frequency in AI-generated responses. GEO applies the same foundational principles as traditional SEO — technical accessibility, content depth, and third-party authority — but directs them toward the specific requirements of AI retrieval systems rather than keyword ranking algorithms. Position 0 treats GEO not as a replacement for SEO but as the next layer of the same discipline.
Position Zero (P0)
Originally, the featured snippet that appeared above the first organic result in Google search — the answer box that gave a user the information they needed without requiring a click. Position Zero now refers to a broader concept: being the brand that an AI system recommends first, before the user clicks, compares, or scrolls. In AI search, there is no page two. The brands that AI systems default to when answering category-relevant questions hold a form of visibility that compounds over time as AI systems reinforce their own citation patterns.
Topic Cluster
A group of semantically related prompts and queries that AI systems associate with a specific subject area. AI engines track which brands appear consistently across an entire topic cluster — not just for a single query. A brand that earns citations across ten related prompts in the sports hydration topic cluster has stronger AI visibility in that cluster than a brand that appears in one prompt at high frequency. Topic cluster coverage is one of the primary signals Position 0 analyzes when evaluating a brand's AI visibility position.
02 - Scoring
Scoring and Measurement
AI Visibility Score
A 100-point diagnostic score that measures how well a brand is positioned to be found, retrieved, and recommended by AI systems. Produced by Position 0 using the P0 Protocol methodology, the AI Visibility Score is calculated across three primary dimensions — Discoverability, Retrievability, and Authority — and reported at the start and end of every engagement. The delta between the baseline score and the post-engagement score is the primary proof of work. Scores are assigned to one of five bands: Weak, Emerging, Competitive, Strong, or Market Leader.
Score Band
The qualitative label assigned to a brand's AI Visibility Score based on its numerical range. Score bands provide category context that raw numbers alone cannot — a score of 58 means something different in a category where the leader scores 62 than in one where the leader scores 84. The five bands are: Weak (0–34), Emerging (35–54), Competitive (55–69), Strong (70–84), and Market Leader (85–100).
Discoverability
One of three primary dimensions in the AI Visibility Score, weighted at 40 points. Discoverability measures how accessible a brand's web presence is to AI crawlers — whether AI systems can reach the pages, read the content, and index it for use in generated responses. A brand with low discoverability may have strong content and a credible reputation, but if its pages are dynamically rendered, blocked by robots directives, or structurally inaccessible, that content cannot contribute to AI visibility. Discoverability is the technical foundation that all other visibility work depends on.
Retrievability
One of three primary dimensions in the AI Visibility Score, weighted at 40 points. Retrievability measures how well the content on a brand's key pages is structured for AI engines to extract, parse, and cite. Pages that score high on retrievability have clear information architecture, structured Q&A content, specific factual claims rather than vague marketing language, and content depth that allows AI engines to extract a complete, citable answer to a query. A page that is crawlable but poorly structured will be read by AI systems but rarely cited.
Authority
One of three primary dimensions in the AI Visibility Score, weighted at 20 points. Authority measures the volume and quality of third-party signals that indicate a brand is credible and relevant within its category. AI systems weight external references — referring domains, editorial citations, review presence, and social proof — when deciding which brands to surface in generated responses. A brand with strong on-site content but a thin external footprint will consistently lose AI citations to competitors that have built broader third-party validation, even when the competitor's content quality is lower.
Content Readiness
A page-level score measuring how prepared a specific URL is to be crawled, parsed, and cited by AI engines. Content readiness is evaluated across structure, depth, and retrievability. A homepage that scores 50% on content readiness has significant structural gaps that limit how much of its content AI engines can extract and use. Content readiness scores are reported separately for the homepage, a key product or service page, and a blog or resource page in every AI Visibility Snapshot.
Citation Presence
The volume and distribution of external sources that reference a brand across the web. In AI visibility analysis, citation presence is measured primarily through referring domain count — the number of distinct external websites that link to or mention a brand. AI systems treat citation presence as a trust signal: a brand referenced across 3,900 external sources is treated as more credible and category-relevant than a brand referenced across 755, all else being equal. Citation presence cannot be improved through on-site work alone; it requires an active third-party outreach and publishing strategy.
Brand Signal Consistency
The degree to which a brand's name, category positioning, and core claims are described consistently across its own content and across third-party sources. AI systems build a probabilistic model of what a brand is and what it does based on the aggregate of everything they can find about it. Inconsistent brand signals — different category labels across pages, conflicting product descriptions, mismatched positioning between owned and earned content — reduce the confidence with which AI systems will recommend a brand for any specific query.
AI Visibility Snapshot
A two-page diagnostic report produced by Position 0 that shows a brand's current AI Visibility Score, how that score breaks down across the three primary dimensions, how the brand compares to its tracked competitors, and the top three highest-impact opportunities for improvement. The Snapshot is the entry point to the P0 Protocol engagement model and is available as a free baseline diagnostic. Every full P0 Protocol engagement begins with a Snapshot score and ends with a post-engagement Snapshot showing the before-and-after delta.
03 - Protocol
P0 Protocol Methodology
P0 Protocol
Position 0's proprietary methodology for getting brands to Position Zero in AI systems — meaning ChatGPT, Perplexity, Gemini, Google AI Overview, and Google AI Mode recommend them first, before a buyer clicks, compares, or scrolls. P0 Protocol is a structured, repeatable, auditable system built on three phases — Build, Broadcast, and Earn — and every engagement produces a measurable AI Visibility Score and a before-and-after proof document at the end of 90 days. It is not a generic GEO service. It is a system with defined inputs, defined outputs, and a documented methodology behind every recommendation.
Build Phase
The first phase of the P0 Protocol. Build establishes the technical foundation required for AI systems to find, read, and understand a brand before being asked to recommend it. This includes schema markup implementation, content architecture improvements, dynamic rendering fixes, structured Q&A development, and any other technical work identified during the baseline audit. A brand that skips the Build phase cannot benefit meaningfully from Broadcast or Earn work — AI systems cannot cite content they cannot access.
Broadcast Phase
The second phase of the P0 Protocol. Broadcast develops the third-party citation footprint that AI systems use as a trust signal when deciding which brands to recommend. This includes content distribution, editorial outreach, publication placement in category-relevant media, and the development of the external reference volume that AI systems interpret as authority. AI systems recommend brands they have seen mentioned consistently across trusted sources. Broadcast is the work of becoming that brand.
Earn Phase
The third phase of the P0 Protocol. Earn is measurement, validation, and proof. Every P0 Protocol engagement closes with a scored proof document showing where the client started and where they landed across all three AI systems and all three scoring dimensions. The Earn phase also includes the tracking infrastructure and ongoing monitoring setup that allows a brand to measure its AI visibility position over time. The delta between the baseline AI Visibility Score and the post-engagement score is the primary deliverable of the Earn phase.
Baseline Score
The AI Visibility Score recorded at the beginning of a P0 Protocol engagement, before any optimization work has been completed. The baseline score establishes the starting point against which all subsequent improvements are measured. Every AI Visibility Snapshot is, by definition, a baseline score — it shows where a brand stands today, not where it will stand after intervention.
This glossary reflects Position 0's current methodology and scoring framework as of April 2026. Definitions are updated as the methodology evolves. For questions about how a specific term applies to your brand's AI Visibility Score, contact Position 0 at position0.com.
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