AI Disclaimer

How AI Is Used

Our ecommerce audit platform combines advanced AI and large language models with automated browser technology to navigate and analyze your website. The AI evaluates your site across six key pillars:

• AEO/GEO — Schema.org markup, FAQ structure, AI and LLM readability
• Agent Readiness — .well-known/ endpoints, llms.txt, MCP server cards, and AI bot policy
• SEO — Meta tags, headers, URL structure, sitemaps, mobile-friendliness
• Content Quality — Product descriptions, calls to action, trust signals
• Performance — Core Web Vitals, load times, resource optimization
• Accessibility — WCAG 2.1 AA compliance, keyboard navigation, screen reader support

Each pillar is scored individually and combined into a weighted overall score. The AI autonomously navigates your site using a real browser, visiting key pages and evaluating each pillar against industry best practices and established standards.

What We Analyze

Our analysis is limited to publicly accessible site data. This includes:

• Static HTML — page structure, meta tags, heading hierarchy, and semantic markup
• Crawlable structured data — Schema.org markup, Open Graph tags, and other machine-readable metadata
• HTTP headers — caching directives, security headers, and server response characteristics
• Observable technical signals — page load behavior, resource sizes, render timing, and Core Web Vitals

Pages We Visit

The AI navigates to the following page types on your site (where available):

• Homepage
• Category listing page
• Product listing page
• Product detail page
• FAQ page (if present)
• About Us page

Methodology Limitations

Because our analysis relies on automated external crawling, there are inherent limitations. Our audit may not fully reflect:

• Server-rendered content — content that depends on specific server-side conditions or user context
• Authenticated states — pages or features behind login walls, such as account dashboards or checkout flows
• CDN behavior — caching layers, edge optimizations, or geographic routing not visible to external crawlers
• A/B test variations — alternate page versions served to different user segments
• Personalized content — recommendations, pricing, or messaging tailored to individual visitors
• Geo-restricted content — pages or features limited to specific regions or countries

Scoring & Recommendations

Scores and recommendations reflect detected signals, not a comprehensive manual audit. Each pillar receives a score from 0 to 100, weighted according to its relative importance (shown in the table above) to produce an overall score.

Score Labels

Findings are categorized by severity (critical, high, medium, low) and include specific recommendations. These recommendations are generated by AI based on detected issues and industry best practices, and should be validated by a qualified professional before implementation.

Human Review

This audit is a starting point, not the final word. A McFadyen Digital commerce specialist reviews the findings with you to:

• Validate which findings are most relevant to your business goals
• Prioritize recommendations based on your specific context and resources
• Identify opportunities the automated analysis may have missed
• Provide strategic guidance beyond what AI can detect

Data Handling