LLM Authority Index

LLM Authority Index is the AI search intelligence and measurement business within The 3D Chess Media Portfolio. It studies how companies, competitors, websites, and sources appear across AI-generated answers and modern search environments. The central question is simple: When buyers ask AI systems which companies they should trust, compare, or choose, which brands actually make the answer? LLM Authority Index is designed to measure that emerging layer of digital discovery. Its work focuses on questions such as:

Which companies are being recommended?
Which brands appear most consistently?
Who receives the first recommendation?
Which companies repeatedly make the top three?
Which competitors are gaining or losing visibility?
Which websites are being cited?
Which sources repeatedly appear around recommendation events?
How do results differ between AI platforms?
How do results change depending on buyer intent?
How does a company's position change over time?

The objective is to turn AI search visibility into something that can be observed, compared, and measured.

Visit LLM Authority Index · LLMAuthorityIndex.com

Measuring More Than Mentions

One of the core principles behind LLM Authority Index is that: being mentioned is not the same thing as being recommended. Consider two companies. Company A appears in 75% of AI responses but is usually presented as: "Another option to consider.", Company B appears in only 50% of responses but is repeatedly presented as: "My top recommendation for this situation.", A simple mention count may suggest Company A is winning. A recommendation analysis may suggest something very different. LLM Authority Index separates different forms of AI visibility so companies can better understand what is actually happening.

These can include:

Mentions
Recommendations
Recommendation position
Top-three placement
Rank-one placement
Citations
Source visibility
Competitive inclusion
Brand framing
Sentiment
Buyer-intent performance

The distinction matters because different forms of visibility may have very different commercial implications.

AI Recommendation Measurement

Who Is AI Actually Recommending?

A significant part of LLM Authority Index research focuses on AI recommendations. The platform can examine whether a company:

Appears at all
Is presented as a serious option
Receives a recommendation
Appears in the top three
Receives the first recommendation
Is favored for specific use cases
Is consistently outranked by competitors
Appears differently across AI platforms

This creates a more detailed picture than simply asking: "Does ChatGPT know our company?", The more commercially relevant question may be: "When someone is ready to choose a provider, is our company entering the shortlist?".

High-Intent Buyer Research

Not every AI prompt has the same commercial value. There is an important difference between: "What is CRM software?", and "What CRM should a 100-person SaaS company choose?", Both concern the same category. The second question is much closer to a purchasing decision. LLM Authority Index places particular emphasis on commercially meaningful prompt groups, including:

Best-provider prompts
Comparison prompts
Alternative prompts
Pricing and cost prompts
Trust prompts
Use-case prompts
Industry-specific prompts
Company-versus-company prompts
Buyer-situation prompts
Provider-selection prompts

This helps separate general informational visibility from visibility occurring near an actual commercial decision.

Competitive AI Search Intelligence

See the Market, Not Just Your Brand

AI search is inherently competitive. A company does not need to disappear completely from AI answers to lose market position. It may still appear while:

A competitor appears more frequently
A competitor ranks first more often
A competitor receives stronger language
A competitor dominates a particular use case
A competitor receives more supporting citations
A competitor gains visibility across more AI platforms

LLM Authority Index research is therefore designed to compare companies within the same commercial environment. Depending on the study, competitive analysis can include:

Recommendation coverage
Recommendation rank
Rank-one share
Top-three visibility
Competitor overlap
Brand sentiment
Brand framing
Prompt-level wins and losses
Platform-specific differences
Historical movement

The result is intended to answer:

Where are we winning?
Where are our competitors winning?
For which buyer questions does that difference matter most?

Citation Intelligence

Which Sources Are AI Systems Using?

LLM Authority Index also studies the source layer behind AI-generated answers. AI systems can cite or rely on information from a broad ecosystem that may include:

Company websites
Publishers
News organizations
Research
Review websites
Comparison sites
Industry publications
YouTube
Forums
Communities
Government websites
Educational institutions
Other third-party sources

Citation research can examine:

Which domains are cited
Which individual URLs are cited
How frequently sources appear
Which sources appear across multiple platforms
Which sources are associated with particular industries
Which URLs repeatedly surface around commercial prompts
How citation behavior changes over time

This creates another important distinction: The company being cited and the company being recommended may not be the same company. A publication may provide the evidence. A different business may receive the recommendation. LLM Authority Index measures those layers separately.

Citation Indexes

LLM Authority Index publishes citation research designed to show which domains and URLs appear most frequently within defined AI-search datasets. Citation indexes can include measurements such as:

Citation occurrences
Unique cited domains
Unique cited URLs
Citing responses
Citation coverage
Cross-platform citation activity

The purpose is not simply to produce a list of popular websites. It is to create a record of the information sources appearing within defined AI-search markets. As those measurements are repeated over time, they can also help identify changes in the source environment surrounding AI-generated recommendations.

Industry Benchmarks

Measuring AI Search at the Market Level

LLM Authority Index conducts research across individual industries and commercial categories. Rather than studying a company in isolation, industry benchmarks can examine:

Major competitors
Recommendation frequency
Recommendation rank
AI-platform differences
Sentiment
Citation sources
Prompt intent
Competitive concentration
Market leaders
Emerging companies
Historical movement

This allows companies to compare their performance against the market rather than against an arbitrary visibility score. A company may have substantial AI visibility and still be underperforming if every major competitor has more. Likewise, a relatively small company may have modest total visibility but unusually strong performance within a narrow, high-value set of prompts. Context matters.

Company and Competitor Reports

LLM Authority Index also produces company-level analysis designed to provide a more focused view of AI-search performance.

A company report can examine questions such as:

How often are we recommended?
Which AI systems recommend us?
Which competitors appear beside us?
Where do we rank?
What situations favor us?
What situations favor our competitors?
Which sources are being cited?
How are AI systems describing our strengths and weaknesses?
Where are the largest gaps?

These reports can provide a baseline before a company begins an AI-search initiative and a reference point for future measurement.

Longitudinal AI Search Tracking

A single AI-search study is a snapshot. Snapshots are useful. But AI systems change. Models change. Search indexes change. Sources change. Companies change their websites. Competitors publish new research. News coverage appears. Reviews accumulate. Market conditions evolve. For that reason, one of the long-term objectives of LLM Authority Index is to create historical datasets showing how AI-mediated market visibility changes over time. Longitudinal tracking can help answer:

Is recommendation share increasing?
Is a competitor gaining?
Did rank-one visibility improve?
Are new sources entering the citation ecosystem?
Are older sources disappearing?
Are results becoming more or less consistent across platforms?
Are certain prompt groups improving faster than others?

Over time, these measurements can become more valuable than any individual snapshot.

AI Visibility Dashboard

LLM Authority Index is developing dashboard-based visibility tracking intended to make recurring AI-search measurement easier to understand. Dashboard tracking can allow companies to monitor defined prompt clusters and competitive markets over time. Depending on the program, measurements may include:

Recommendation visibility
Recommendation share
Recommendation position
Competitive movement
Citation visibility
Prompt-level results
Historical comparisons
Opportunity identification

The goal is to move AI-search measurement from occasional manual testing toward structured, repeatable market intelligence.

Prompt Clusters

Organizing Research Around Buyer Intent

A large AI-search study can include hundreds or thousands of possible questions. LLM Authority Index organizes related prompts into defined clusters.

A cluster may represent a commercial decision such as:

Pricing
Best provider
Competitor comparison
Alternative provider
Specific use case
Trust and reputation
Industry-specific need
Company selection

Grouping prompts this way makes it possible to measure not just overall AI visibility, but visibility within the kinds of questions most relevant to a company's commercial objectives. A company might perform strongly in educational prompts while performing poorly in provider-selection prompts. Without segmentation, those differences can disappear inside an overall score.

Cross-Platform Research

Different AI systems can produce materially different answers. A company that performs well on one platform may perform poorly on another. LLM Authority Index research can compare results across major AI and AI-search environments. The purpose is not to assume each system represents an independent expert opinion. AI systems can share sources, search results, training information, publisher ecosystems, and company claims.

Instead, cross-platform analysis measures:

agreement
disagreement
recommendation consistency
source overlap
platform-specific behavior.

The disagreement itself can be useful intelligence. If every major system recommends the same three companies, the market may have a relatively stable AI consensus. If recommendations vary dramatically from platform to platform, the market may be much less settled.

Consensus Research

LLM Authority Index also provides research infrastructure and data supporting the Consensus Index methodology used across parts of The 3D Chess Media Portfolio. The Consensus Index concept asks multiple AI systems substantially the same defined question and compares:

Which companies appear
Which companies are recommended
Recommendation position
Areas of agreement
Areas of disagreement
Supporting reasoning
Citations
Source overlap
Changes over time

An important principle behind this methodology is: AI agreement should be measured, not mistaken for proof of objective truth. If six AI systems recommend the same company, the research can accurately report that six systems recommended that company. It cannot automatically conclude that six independent experts proved the company is objectively best.

Original Research

LLM Authority Index is designed to publish original AI-search measurement rather than simply commentary about the emerging industry. That work can include:

Industry datasets
AI recommendation studies
Citation indexes
Competitive benchmarks
Company analysis
Prompt research
Source analysis
Longitudinal studies
Methodology research
Emerging measurement frameworks

The objective is to create repeatable datasets that can be revisited and updated as AI-search behavior evolves.

Research Frameworks

Because AI search remains an emerging discipline, LLM Authority Index also develops and tests research concepts intended to make the market easier to measure. These can include concepts related to:

AI Recommendation Share
Citation Rating
Source influence
Recommendation proximity
Citation centrality
Competitive visibility
Recommendation concentration
Cross-platform agreement

These frameworks should not automatically be interpreted as universally accepted industry standards or confirmed ranking factors. They are measurement concepts intended to create testable ways of thinking about an evolving market. A research hypothesis should remain labeled as a hypothesis. A measurement should remain labeled as a measurement. And an inference should not be presented as established fact.

Measurement and Implementation Are Separate

LLM Authority Index and CiteWorks Studio are related businesses within 3D Chess Media, but they serve different functions.

Measures the environment.

It is intended to answer questions such as:

What is happening?
Where are we losing?
Which competitors are winning?
Which sources are appearing?
How is our position changing?

CiteWorks Studio

Works on the environment.

It focuses on questions such as:

What should we change?
Which visibility gaps are addressable?
Where does our information ecosystem need improvement?
How can the company become easier for AI systems to understand, cite, and recommend?

Keeping measurement and implementation distinct is important. Research should be capable of showing that a client is losing. It should also be capable of showing that a competitor is winning.

Who LLM Authority Index Is For

LLM Authority Index research can be relevant to organizations such as:

Enterprise companies
SaaS businesses
Consumer brands
Marketing teams
Chief Marketing Officers
Founders
Agencies
Investors
Publishers
Competitive-intelligence teams
SEO teams
Content teams
Reputation teams
Research organizations

The common question is: How is AI-mediated discovery changing our market position?

Why 3D Chess Media Built LLM Authority Index

3D Chess Media's background is deeply connected to search, publishing, affiliate marketing, customer acquisition, and digital businesses. For years, companies could measure much of the search environment through familiar metrics:

Search rankings
Search volume
Organic traffic
Paid traffic
Conversion rates
Backlinks
Impressions
Click-through rates

AI-generated answers complicate that system. A prospective customer may now receive a shortlist of companies without clicking a traditional search result first.

That creates new questions:

Were we in the answer?
Were we recommended?
Where did we rank?
Who beat us?
What sources influenced the response?
Did the answer change this month?

LLM Authority Index exists to help make those questions measurable.

From Visibility to Market Intelligence

The long-term opportunity is larger than monitoring whether a company appears in ChatGPT. As AI becomes more deeply integrated into commercial research, recommendation data may provide insight into:

Competitive position
Brand perception
Market concentration
Emerging competitors
Source authority
Buyer consideration
Industry movement
Information gaps
Reputation
Category leadership

That turns AI-search measurement into a form of market intelligence. The question becomes less: "How many AI mentions did we get?", and more: "What is the AI-mediated market telling us about our competitive position?".

Explore LLM Authority Index

Visit LLM Authority Index to explore:

AI-search industry benchmarks
Citation indexes
Market research
Company analysis
Research methodologies
Competitive intelligence
AI visibility measurement
Historical datasets