ChatGPT and Perplexity agreed on only 1 in 4 local business recommendations (www.clicksdynasty.com)

A recent study by Ravinder Cheema, running a small SEO agency, highlighted significant discrepancies between AI tools ChatGPT and Perplexity in recommending local businesses. When searching for the "best {industry} in {city}, CA," the two platforms agreed on only 24% of their top five recommendations across 20 searches. Notably, they only matched on the same top business once, revealing their different methodologies: ChatGPT favored third-party listings and review aggregators, while Perplexity leaned towards businesses' own websites. This divergence in data sourcing suggests that the tools evaluate local businesses based on distinct criteria, which can lead to highly variable recommendations. This finding is particularly relevant for the AI/ML community as it underscores the need for transparency in data handling and recommendation processes for AI tools. As businesses increasingly rely on AI for visibility, understanding the algorithms and datasets driving these recommendations becomes crucial. For example, the study noted that tools also responded differently based on user sign-in status, indicating that personalization may further complicate the reliability of AI-generated suggestions. As AI use in local searches continues to grow, these insights call for deeper exploration into how AI models rank and recommend businesses, prompting further comparative studies across different platforms and queries.