Understanding Your Brand's AI Search Scores Across Different Engines

This article explains why brands may have different AI search scores across engines like ChatGPT, Perplexity, Google Gemini, and Anthropic's Claude. It provides insights into what factors influence each engine's scoring and how to use the variance to identify areas for improvement.

Details

The article explains that the different AI engines - ChatGPT, Perplexity, Google Gemini, and Anthropic's Claude - all have unique approaches to retrieving and evaluating brand information. ChatGPT uses a consensus-based model that looks at third-party sources like Reddit and review sites, while Perplexity focuses on real-time web crawling and Bing indexing. Gemini is more closely tied to traditional Google signals like rankings and schema markup, and Claude relies heavily on the consistency of how a brand is described in its training data. This leads to significantly different scores for the same brand across the engines. Understanding these differences allows brands and SEO consultants to identify specific areas to improve, such as building third-party social proof, optimizing structured content and Bing indexing, or ensuring consistent entity descriptions. The article provides a real-world example comparing HubSpot's strong, consistent scores across engines versus a more typical brand with uneven performance, highlighting where to focus improvement efforts.