Skip to main content

​
Real-World Case Studies

The following cases are based on publicly verifiable data analysis of over 3,200,000+ domains. You can use AI trust assessment tools such as ORBEXA (orbexa.io/verify) to look up the trust score of any domain.

​
Case 1: Trust Score Distribution Among Major Brands

We analyzed the OTR trust scores of well-known global brands. One surprising finding: big brands do not automatically score high. Key finding: The D dimension (Data Quality) is the easiest to improve. Many major brands score well on V/S/G, but their D dimension drags down the total because they lack llms.txt and complete Schema.org markup.

​
Case 2: From BRONZE to SILVER — A Score Improvement Path

A typical small-to-midsize e-commerce site started at a score of 52 (UNRATED). Through the following steps, it reached 72 (SILVER): Week 1: Security Foundations (+8 points)
  • Configured DNSSEC -> S dimension improved
  • Added DMARC record -> S dimension improved
  • Added SPF and DKIM -> S dimension improved
Week 2: Transparency (+6 points)
  • Rewrote privacy policy (from a generic template to a detailed, custom version) -> T dimension improved
  • Added return policy details -> T dimension improved
  • Added complete contact information -> T dimension improved
Week 3: Data Quality (+6 points)
  • Added Schema.org Product markup to all product pages -> D dimension improved
  • Created llms.txt -> D dimension improved
  • Optimized Product Sitemap -> D dimension improved
Total improvement: approximately 20 points, from 52 to 72, jumping from UNRATED to SILVER.
None of this work requires paid tools. DNSSEC can be enabled in your domain registrar’s dashboard. DMARC/SPF/DKIM are DNS records you add for free. Schema.org markup is HTML code. The llms.txt file is plain text. All of it is free.

​
Case 3: The D Dimension Is the Biggest Score Lever

Based on analysis of global e-commerce domains:
  • Fewer than 5% of domains have an llms.txt file
  • Fewer than 30% of e-commerce sites have complete Schema.org Product markup
  • Fewer than 3% have both
This means: if you do what others have not, you are ahead of 97% of your competitors. Every point in the D dimension tells AI agents: “This merchant’s data is structured, complete, and machine-readable.” AI agents will prioritize merchants with high data quality because they can more accurately understand and recommend those products.

​
Your Action Plan

Ranked by priority — start with what makes the biggest impact:

​
Do Today (30 minutes)

  • Check your trust score -> orbexa.io/verify
  • Create an llms.txt file -> place it in your website’s root directory
  • Check robots.txt -> confirm AI crawlers are not blocked

​
Do This Week (2-3 hours)

  • Add Schema.org Product markup to product pages
  • Configure a DMARC record
  • Configure an SPF record
  • Review and optimize your Sitemap

​
Do This Month (1-2 days)

  • Rewrite your privacy policy and return policy
  • Enable DNSSEC
  • Add Schema.org Organization markup
  • Create an agent.json file

​
Long-Term Goals

  • Target trust score of 70+ (SILVER)
  • Adopt the UCP protocol
  • Adopt the ACP protocol (requires developer involvement)
Congratulations on finishing Book 1. You now understand the full landscape of AI agent commerce. Recommended next steps:
Recommended next read: OTR — Open Trust Registry — a deep dive into the six-dimension trust assessment system More case studies: OTR Cases | UCP Cases | SEO Cases