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Case Studies

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12.1 Case 1: AI Shopping Assistant

Scenario: An AI shopping assistant uses OTR trust scores when recommending products to consumers. Implementation:
  1. The user says, “Recommend a pair of running shoes under $150”
  2. The AI identifies 10 candidate merchants
  3. It queries each merchant’s OTR score in parallel
  4. Candidates are ranked by a composite formula (50% product relevance + 30% trust score + 20% price)
  5. The top 3 results are presented with their trust badge
Outcome: Users are significantly more likely to click through and purchase from merchants displaying a GOLD trust badge. Merchants rated SILVER or above see conversion rates approximately 40% higher than UNRATED merchants.

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12.2 Case 2: B2B Supply Chain Trust Assessment

Scenario: A retailer evaluates the trustworthiness of potential new suppliers. Implementation:
  1. The procurement team provides a list of candidate supplier domains
  2. OTR scores are queried in batch
  3. Results are sorted by V dimension (identity verification) and G dimension (governance)
  4. Suppliers rated GOLD or above are prioritized for outreach
Value: The initial screening phase of traditional supplier due diligence — which typically takes 2 to 4 weeks — is reduced to minutes.

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12.3 Case 3: Brand Trust Monitoring

Scenario: A brand monitors the trust scores of all its domains and sub-brands over time. Implementation:
  1. A scheduled job queries OTR scores for all domains daily
  2. Historical data is recorded
  3. Automated alerts trigger when any score drops
  4. A monthly trust health report is generated
Typical alert scenarios:
  • An SSL certificate is about to expire, causing the V dimension to drop
  • A DNS configuration is accidentally modified, causing the S dimension to drop
  • A website redesign removes Schema.org markup, causing the D dimension to drop

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12.4 Case 4: Competitive Analysis

Scenario: Analyzing the trust score distribution of competitors in the same industry. 
Industry: Outdoor Sports Equipment
Competitors analyzed: 20 domains

Distribution:
PLATINUM: 1 (5%)
GOLD: 3 (15%)
SILVER: 5 (25%)
BRONZE: 6 (30%)
UNRATED: 5 (25%)

Key findings:
- Industry average score: 68 (upper BRONZE range)
- D dimension is universally low (most lack llms.txt)
- Leading brands differentiate primarily through V and G dimensions
Next chapter: Reference — Complete technical reference for the OTR protocol More case studies: Getting Started Cases | UCP Cases | MCP Cases