GEOSNAP × VITESSE EUROPE RESEARCH — SEPTEMBER 2026
AI-Driven Insights in Italian Cycling
We asked ChatGPT, Gemini, and Google AI Studio what to buy in the cycling industry. We analyzed nearly 600 responses across 8 categories, totaling over 10,406 unique brand mentions. This study reveals which brands AI recommends and the specific sources it relies on for its decisions.
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A search for
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Analytical Methodologies
The questions were asked in Italian—the language of the cyclist—using the public interfaces of the three assistants rather than their APIs, as API responses differ from what a real person receives.
Each question was repeated three times to minimize the impact of model variability.
Each prompt is classified by category, sub-category, intent, and budget range.
3 AI models queried
ChatGPT
Gemini
Google AI Mode
Who conducted the research
Geosnap
The leading Generative Engine Optimization platform: measure how your brand is cited in AI-generated answers and discover actionable insights to boost your visibility. Research developed in collaboration with the University of Bergamo.
Vitesse Europe
An Italian media PR and communications agency specializing in cycling, sports, outdoor recreation, and active tourism.
What the search includes
An in-depth analysis of eight distinct categories.
Brand rankings, category by category
Eight comprehensive rankings: mentions, share of voice, reach on queries, average list position, and consistency across repetitions.
First-mention brands in AI models
AI Top of Mind: Which brands are mentioned first, how often, and on which LLMs.
How big of an impact does Italy really have on the cycling world?
How often do LLMs recommend Italian brands for purchase compared to international competitors?
Where the three LLMs differ
Same prompt, different results. Discover which brands appear on only one LLM versus those that capture all three.
The data sources powering our AI insights
The impact of media outlets, e-commerce, and official brand sites on AI-generated search results
Plans, Pricing, and Profiles
How recommendations adapt to specific sub-use cases, budget ranges, and requested product types.
Request the complete search
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