Boosting AI Search Visibility: How Frevana Helped a Fitness Brand Increase Their Visibility Score by 16% in One Week

Executive Summary

In 2025, AI-powered answer engines are reshaping how consumers discover products online. For many e-commerce brands, traditional SEO no longer guarantees presence in AI-generated answers. Frevana partnered with a fitness equipment brand to address this gap. Within just one week, the brand’s AI search visibility score increased from 30% to 46%. This was achieved by building an AI-citable landing page, optimizing their LLMs.txt file, implementing an FAQ section, and providing actionable AEO insights with a real-time visibility dashboard.

Background

The client, a well-known brand in the fitness equipment market, faced insufficient discoverability in AI-driven search environments. Although their marketplace product pages ranked well in traditional search, these links were often excluded from AI-generated answers, leaving them invisible to potential customers exploring product recommendations via ChatGPT, Google AI Overviews, or Perplexity.

Challenges

• Low Initial Visibility: The brand’s AI search visibility score was only 30%.
• Uncitable Product Pages: AI engines avoided citing marketplace product detail pages (like Amazon), reducing exposure.
• Missing LLMs.txt File: Without clear signals for large language models, the brand’s domain lacked essential metadata for AI indexing.
• No Centralized Benchmarking: The team had no way to track or compare AI visibility against competitors.

Frevana’s Approach

1. In-Depth AEO Insights

• Conducted a comprehensive Answer Engine Optimization (AEO) audit.
• Benchmarked the brand’s visibility against competitors in the fitness equipment industry.
• Identified missing signals and structural barriers preventing AI citations.

2. AI-Citable Landing Page

• Designed an intermediary landing page hosting clear, structured, and detailed product content.
• Ensured content readability and citation-friendliness for AI engines.

3. LLMs.txt Optimization

• Audited the missing LLMs.txt file.
• Delivered practical guidelines and implemented optimized signals for model-friendly crawling and referencing.

4. FAQ Section

• Added an FAQ module to the landing page to align with AI’s preference for direct, structured answers.

5. Visibility Dashboard

• Built a real-time AEO visibility dashboard, enabling the team to monitor and compare performance against competitors on demand.

Results

• Visibility Score Increased from 30% to 46% in one week.
• The landing page began appearing in AI-generated answers, capturing visibility that was previously lost.
• Clear LLMs.txt implementation improved AI indexing and product referencing.
• FAQs provided concise, direct answers that AI could easily cite.
• Dashboard empowered the brand’s team with ongoing insights, ensuring AEO became a repeatable growth strategy.

Conclusion

This case demonstrates how Frevana’s AEO-first approach delivers measurable improvements in AI search discoverability. By moving beyond SEO and focusing on AI citation readiness, the brand transformed from being invisible in AI answers to becoming a visible, recommended option within one week.
Frevana’s methodology—combining audits, structured landing pages, LLMs.txt optimization, and actionable dashboards—provides a scalable path for any e-commerce brand navigating the future of AI-driven product discovery.