The Human + AI Standard: Understanding Trust Signals
AI Trust Signals is the only tool that goes beyond "are you visible?" to uncover the key brand drivers of AI authority and human buyer trust -
and give you the action plan to improve them.
Why Trust Signals Matter Now:
Authority is the metric for AI Answers.
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The Challenge: For decades, top organic ranking on Google meant your brand was considered "the best" resource for the buyer's search. But today, AI models are the conveyors of trust and recommendations... and buyers trust AI. So to be trusted by buyers, you need to be recommended by AI first.
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The Solution: AI Trust Signals measure a brand's authoritativeness by analyzing the signals that human buyers look for in trusted brands, and that AI models look for to include them in citations and recommendations..
How Trust Signals Work
Trust Signals are the machine-readable, verifiable, and behavioral ingredients that LLMs and humans rely on to assess credibility.
For AI Models:
Signals act as a confidence score, turning content from mere text into a set of verifiable facts, dramatically increasing the likelihood of citation.
For Human Buyers:
Signals reduce friction, shorten the sales cycle, and build instant confidence by providing transparency (e.g., clear pricing, verified contact info).
The Trust Signals Score: What, How, and Why
The Core Scoring Logic:
The overall AITS Score (e.g., 83%) is calculated from performance across 19 critical signals, categorized into three strategic tiers.
Scoring Scale:
Each signal is scored either Low, Medium, High, or Pass / Fail, reflecting what each AI model understands about your brands signals.
The Goal:
The score gives a clear metric that enables tactical recommendations for improvement of specific signals to enhance human + AI authority.
Three Tiers of Authority:
Trust Signals are grouped into three tiers, indicating their importance and impact
to your brands buyer + AI authority.
Technical
Purpose:
Measure the technical integrity and machine-readability of your site. These are the non-negotiable structural elements required for any LLM to confidently ingest and cite your data.
Authority
Purpose:
Measure the depth, expertise, and authority of your content. These signals prove that the humans behind the brand are credible experts who deserve to be cited as the source of truth.
Brand
Purpose
Measure the real-world social proof and industry recognition. These signals lower the risk for an AI to recommend you by confirming positive customer satisfaction and claims of recognition.
Technical Trust Signals:
Advanced Schema Deployment
Measures deployment of granular schema (Products, FAQs, How-To) that defines content purpose in a machine-readable format.
Answer-Focused Semantic Structure
Evaluates content architecture (headings as questions, paragraphs as concise answers) for confident LLM extraction.
On-Page Contact & 'About' Depth
Assesses richness of identity pages (mission, history, multiple contact options) to confirm the business as an accessible, verifiable real-world entity.
Verified NAP Consistency
Measures consistency of Name, Address, and Phone number across the web (website, GBP, directories), signaling legitimacy.
On-Page Policy & Ethics Transparency
Measures clear presence of Privacy Policy, Terms of Service, and ethics statements, providing factual answers about accountability.
Customer Responsiveness
Measures presence of immediate support channels (Phone, Live Chat) and published service commitments.
Authority Trust Signals:
On-Page Pricing Transparency
Assesses whether the website clearly addresses cost (fixed prices, ranges, estimators), providing factual data for high-intent queries.
Authoritative Outbound Citations
Assesses use of external citations, aligning content with the structural and stylistic patterns of high-trust information like academic papers.
Presence of Author / Team Pages
Measures demonstrated human expertise (names, bios, credentials) allowing the AI to cross-reference and validate E-E-A-T.
On-Page Content Richness
Evaluates depth and substance (detailed explanations, data, examples) signaling an authoritative resource.
Accuracy of Claims
Measures the credibility of the brand's voice by analyzing sensationalist/hyperbolic vs. objective language.
Google Page 1
Measures visibility in the entire first page of Google, making content eligible for LLM inclusion as a pool of credible sources.
Case Study & Testimonial Presence
Measures the use of direct social proof (testimonials, case studies) that LLMs can parse to extract factual outcomes and validate claims.
Educational Content Hub
Measures centralized, topically-organized content libraries, signaling subject matter authority to the LLM.
Content Freshness
Measures the recency of content (publication/revision dates), a critical proxy for accuracy and relevance.
Content Surface Area
Assesses diversity of digital footprint across multiple platforms (YouTube, LinkedIn, Quora, etc.), providing multi-faceted, corroborated authority.
Brand Trust Signals:
Public Review Score & Volume
Evaluates volume and quality of public reviews on reputable platforms (e.g., G2, Capterra, BBB), which LLMs use as primary indicators of trustworthiness.
Brand Values
Assesses whether core values and purpose are articulated, building emotional trust and attracting customers who share the worldview.
Claims of Industry Recognition
Measures display of external endorsements (awards, certifications, media features) which LLMs cross-reference for credible evidence of standing.