AEOfix Achieves 70% AI Search Visibility in 6 Days, Proving Answer Engine Optimization Outpaces Traditional SEO

New Case Study Shows AEO Delivers Brand Recognition 15-30x Faster Than Traditional SEO Methods

REMOTE, December 24, 2025 —

AEOfix, a professional Answer Engine Optimization (AEO) service, today announced the release of a comprehensive case study documenting how the company achieved 70% brand visibility across ChatGPT, Claude, Perplexity, and Gemini in just 6 days—proving AEO works 15-30x faster than traditional SEO for brand recognition.

The case study, which tracked brand awareness across four major AI search engines using proprietary monitoring technology, revealed that properly implemented Answer Engine Optimization can deliver measurable results in less than one week, compared to the 3-6 months typically required for traditional search engine optimization.

Note: These results represent AEOfix's own brand visibility measured using our proprietary brand awareness scanning system. Full methodology and detailed metrics are available in the complete case study and research methodology.

Breakthrough Results Challenge SEO Orthodoxy

Starting from zero brand recognition on December 13, 2025, AEOfix implemented comprehensive schema markup, FAQ-structured content, and semantic HTML optimization. Within six days, the brand achieved:

• 70.5% overall AI visibility score across all four tested engines
• 80% mention rate when users asked relevant questions
• 88/100 technical score for Answer Engine Optimization implementation
• 85/100 schema health with 9 distinct schema types deployed
• 90/100 content structure score optimized for AI parsing

AI Engines Index New Brands Significantly Faster

The study revealed notable differences in how various AI platforms index and cite new brands:

• Gemini (72/100) proved fastest to index, showing accurate brand descriptions within 48 hours
• Perplexity (70/100) demonstrated the most comprehensive citations with source attribution
• ChatGPT (70/100) provided accurate descriptions but with more generic framing
• Claude (66/100) showed the most conservative approach, frequently requesting additional context

The comprehensive case study tested five distinct query types across all four engines, conducting 20 individual tests to measure brand visibility, mention accuracy, and information quality.

Key Success Factors Identified

The research identified several critical factors that contributed to rapid AI visibility:

• Comprehensive schema markup: Nine schema types (Organization, Service, FAQPage, Article, Person, WebSite, and supporting types) provided multiple pathways for AI understanding
• FAQ-first content strategy: Structuring all content as question-answer pairs aligned with AI information retrieval patterns
• Direct answers at page tops: 40-60 word summaries that AI engines consistently extracted
• Technical performance: Sub-2-second load times and perfect accessibility scores
• Semantic HTML structure: Proper heading hierarchy enabled effective content parsing

Transparent Methodology Includes Challenges

In an industry often characterized by inflated claims, AEOfix chose complete transparency, documenting both successes and limitations. The case study openly acknowledges that industry-wide "thought leader" queries (such as "Who are the leaders in Generative Engine Optimization?") scored 0/100—AEOfix was not mentioned alongside established competitors.

"This gap was expected for a brand-new company," the report notes. "Industry leadership requires authority signals beyond technical optimization—press mentions, citations, and established market presence that take months to build, not days."

Implications for Digital Marketing

The findings suggest significant implications for how businesses approach online visibility in an AI-first search landscape:

• New brands can establish AI presence in days rather than months
• Traditional SEO timelines may no longer apply to AI search visibility
• Schema markup has evolved from "nice to have" to mission-critical
• Content structure matters as much as content quality for AI discoverability
• Different AI engines have different indexing speeds and citation behaviors

Full Case Study Available

The complete case study, including detailed methodology, day-by-day timeline, technical implementation specifics, and recommendations for replicating results, is publicly available at aeofix.com/case-study-building-aeofix.html

The 3,500-word report includes comprehensive data tables, code samples, performance metrics, and a transparent analysis of what worked and what didn't during the six-day implementation period.