GEO Research Based on 50,000 AI Responses: How AI Search Engines Recommend Businesses

Reachd.ai released a Generative Engine Optimization (GEO) study based on 50,000 responses from five major AI platforms including ChatGPT and Google AI. It reveals that the recommendation mechanism of AI search engines is fundamentally different from traditional SEO, with key findings such as platform independence, non-necessity of structured data, and the importance of enterprise official website information, providing empirical basis for enterprises to formulate GEO strategies.

With the rise of ChatGPT and AI search tools, enterprises are paying attention to GEO (Generative Engine Optimization)/AEO (AI Engine Optimization); Reachd.ai collected 50,000 responses and 350,000 citation data from five platforms, covering real queries in more than 15 industries (e.g., "the best barber shop nearby"). The study is based on direct observation and analysis of AI's actual behavior, not theoretical speculation or migration of traditional SEO experience.

1. The recommendation results of the five AI platforms have extremely low correlation (the correlation coefficient between Google AI and Grok is only r=0.363), so a diversified GEO strategy is needed; 2. Structured data is not necessary—most cited websites have no Schema markup, and pure text content can be cited by AI (e.g., Coca-Cola's FAQ page).

1. 61% of citations come from enterprise official websites, and AI prefers specific and practical information (phone number, business hours, etc.) rather than marketing content; 2. External mention degree (source resilience) is highly correlated with recommendation position—enterprises mentioned by 2+ independent websites are more likely to be recommended.

1. AI recommendation results are stable (87.7% consistent status, 80.1% unchanged position), and the position is "earned" rather than random; 2. Yelp, Instagram, and Facebook have the highest correlation with recommendations, while Google Maps/business profiles are not directly cited.

1. Build topic-specific pages (e.g., a cabinet enterprise's special page on "humidity response"); 2. Include specific verifiable information (contact information, pricing, etc.) on the official website; 3. Establish cross-platform brand mentions (Yelp, Instagram, etc.); 4. Adopt a multi-platform strategy to monitor the performance of each AI platform.

Dimension	SEO	GEO
Number of algorithms	1 (Google)	5 engines with extremely low correlation
Structured data	Helps with ranking	Not necessary
Google Business Profile	Key for local search	Not directly cited
Effective content	Long articles with keywords	Specific facts
Result format	Links	Recommendations
Stability	Fluctuating	Over 80% stable

The study provides empirical data for GEO. The AI recommendation mechanism is not an extension of traditional SEO; its core is to provide specific, verifiable, and cross-platform consistent information. Adapting to this new paradigm is an important part of enterprise digital marketing.