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Joëlle Berger

Founder & Chief AI Strategist, AI Audit Scan

Overview

Joëlle Berger is the founder of AI Audit Scan and a pioneer in AI Engine Optimization (AEO). She conducted the first comprehensive study of AI search visibility in e-commerce and has since built the industry's largest benchmark database for measuring LLM readiness across multiple sectors.

Foundational Research

In January 2025, Joëlle conducted the first comprehensive analysis of AI search visibility in e-commerce, examining 409 websites to understand how businesses appear to AI-powered answer engines. The research revealed critical gaps in AI readiness:

• 98.3% of e-commerce sites lack Product schema markup
• 60% are completely invisible to AI crawlers (GPTBot, Google-Extended, Claude-Web)
• Missing structured data prevents AI engines from citing products and services
• Robots.txt misconfigurations block legitimate AI crawler access

This study established the foundational benchmarks for AI Engine Optimization and formally defined the "Visibility Gap" phenomenon—the measurable deficit in AI search visibility affecting the majority of online businesses.

Industry Benchmark Database

Since founding AI Audit Scan, Joëlle has expanded the research to create the industry's most comprehensive AI visibility database, analyzing 5,939+ websites across 20 industries:

• Fleet & Leasing
• Automotive
• Technology & SaaS
• ESG & Compliance Software
• Hospitality & Travel
• Health & Medical
• Marketing & Advertising
• Nutrition & Wellness
• Media & Entertainment
• Legal Services
• Sports & Fitness E-commerce
• Sports Media
• Education & E-learning
• Retail & E-commerce
• Banking & Fintech
• Professional Services & Consulting
• Manufacturing
• Finance & Asset Management
• Real Estate
• General Business

The database reveals an average AEO score of 35.2/100, with significant variation by sector. Fleet & Leasing (67.1/100) and Technology & SaaS (52.3/100) lead in AI readiness, while Real Estate (22.1/100), Finance (23.5/100), and Manufacturing (23.9/100) show critical visibility gaps.

Key findings across all industries: 44.8% of websites lack structured data for AI engines, and 6.8% actively block AI crawlers (GPTBot, Google-Extended, Claude-Web). This comprehensive analysis establishes the first quantitative industry benchmarks for AI search visibility.

Methodology & Innovation

Joëlle created the LLM Readiness Score, a proprietary framework evaluating AI search visibility across 30+ signals:

• Structured Data Completeness: Schema.org implementation quality and coverage
• AI Crawler Accessibility: Robots.txt configuration for GPTBot, Google-Extended, Claude-Web, CCBot, and Perplexity crawlers
• Content Semantic Optimization: FAQ schema, How-to markup, Q&A structure
• Technical Infrastructure: Site performance, mobile optimization, Core Web Vitals
• Authority Signals: Author credentials, expertise markers, citation-worthy content

Expertise

Joëlle specializes in optimizing digital presence for AI-powered answer engines including ChatGPT, Perplexity, Claude, and Gemini. Her work focuses on:

• AI Engine Optimization (AEO) strategy and implementation
• Structured data architecture for maximum AI discoverability
• Cross-industry visibility benchmarking and competitive analysis
• LLM crawler management and indexing optimization
• Visibility Gap remediation and AI readiness improvement

Background

With 15+ years of experience in communication strategy and consulting, Joëlle identified the emerging challenge of AI search visibility in late 2024. She founded AI Audit Scan in January 2025 to help businesses adapt to the shift from traditional search engines to AI-powered answer engines.

Based in Southern Europe, Joëlle works with organizations globally, delivering AI visibility audits and optimization strategies across multiple languages and markets.

For collaboration or speaking inquiries, visit aiauditscan.com