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Case Studies

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14.1 Case 1: A Small E-Commerce Store’s Three-Week Improvement

Background: A small-to-midsize outdoor gear e-commerce store with approximately 500 SKUs, running on WooCommerce, with a domain registered three years ago. Initial state:
  • Overall score: 52 (UNRATED)
  • V: 55, S: 35, G: 40, T: 50, D: 30
  • Had SSL but no DNSSEC, no DMARC
  • No Schema.org Product markup
  • No llms.txt
  • Privacy policy was the default WordPress template
Optimization timeline:
TimeActionDimension Change
Day 1Enabled DNSSECS: 35 to 42
Day 1Added DMARC + SPFS: 42 to 52
Day 2Installed RankMath, enabled Product markupD: 30 to 45
Day 3Created llms.txtD: 45 to 52
End of Week 1Rewrote privacy and return policiesT: 50 to 60
Week 2Created agent.jsonD: 52 to 55
Week 2Added Organization markup to homepageT: 60 to 64
Week 3Optimized Sitemap to include all 500 productsD: 55 to 58
Result: Overall score rose from 52 to 72 (UNRATED to SILVER) Key takeaways:
  • The S dimension has the highest return on investment — two DNS records delivered a 17-point improvement
  • D dimension Schema.org markup was auto-generated by a plugin, saving significant manual effort
  • llms.txt took 15 minutes to write but boosted the D dimension by 7 points

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14.2 Case 2: AI Visibility Optimization for a SaaS Product

Background: A B2B SaaS product providing project management tools, built on a Next.js custom site. Initial state:
  • Overall score: 48 (UNRATED)
  • No structured data of any kind
  • Had HTTPS but no DNS security configuration
  • No llms.txt
  • Policy pages existed but lacked Schema.org markup
Key optimization points: SaaS products differ from e-commerce sites — they do not need Product markup, but they do need:
  1. Organization markup — Structured company information
  2. SoftwareApplication markup — Structured product information
  3. FAQ markup — Structured frequently asked questions
  4. llms.txt — A concise description of product positioning, pricing, and core features
SaaS llms.txt structure example: 
# ProductName — One-line positioning

> Providing ... for small and midsize businesses

## Core Features
- Feature 1: Description
- Feature 2: Description

## Pricing
- Free plan: Limitations
- Paid plan: Price and features

## API
- Documentation: Link
- Status page: Link

## Integrations
- Supported integrations: List

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14.3 Case 3: The D-Dimension Gap for Major Brands

Analysis: An AI trust score analysis of well-known global brand domains reveals an interesting pattern. Many large brands score highly in V (identity verification) and G (governance) because they have GLEIF registrations, Wikidata entities, public company verification, and other credentials. However, they often underperform in the D (data quality) dimension. Root causes:
  • Large brand websites are typically managed by enterprise CMS platforms, and Schema.org markup is not always complete
  • Large brands rarely have llms.txt
  • Large brands’ robots.txt files may be overly restrictive, blocking AI crawlers
Implication: Small and midsize merchants can surpass many large brands in the D dimension. llms.txt, comprehensive Schema.org markup, and AI-friendly robots.txt rules are things large brands frequently overlook but smaller merchants can easily implement.

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14.4 Optimization Efficiency Comparison by Platform

PlatformDifficultyAutomation LevelTypical Time Investment
ShopifyLowHigh (built-in Schema.org)2-3 hours
WooCommerceMediumMedium (plugins required)3-5 hours
Next.js / CustomHighLow (development required)1-2 days
Wix / SquarespaceLowMedium2-3 hours

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14.5 Common Failure Patterns

Failure ReasonSymptomFix
Implemented but not validatedSchema.org markup has syntax errorsUse validation tools after every change
DNS records overwrittenDMARC records lost during domain migrationCheck all DNS records immediately after migration
SSL certificate expiredAuto-renewal was not configuredUse auto-renewal (e.g., Let’s Encrypt)
robots.txt too restrictiveA newly installed security plugin blocked all crawlersCheck robots.txt after installing any plugin
llms.txt is staleProduct line has changed but llms.txt was not updatedReview once a month
Congratulations on completing Book 6. You now have a comprehensive understanding of the AI-SEO knowledge framework. Recommended next steps:
More case studies: Getting Started Cases | OTR Cases | MCP Cases