GEOScan addresses the challenge of brand visibility in the evolving landscape of generative AI search. The platform is designed for teams and marketers seeking to understand and improve how their brands are perceived, cited, and recommended by AI systems such as ChatGPT, Claude, Gemini, and Perplexity.
A central feature of GEOScan is its AI Visibility Score, which quantifies how frequently and accurately a brand appears in answers generated by major AI models. This score serves as a benchmark that organizations can monitor over time to assess their performance in AI-driven search environments. In addition, GEOScan offers Citation Tracking and Analytics, enabling users to monitor when and how their websites are cited as sources in AI-generated responses. This capability records details such as the specific pages, prompts, and models that drive AI referrals, providing a granular view of brand exposure.
The tool also includes Entity Analysis, which examines how generative engines describe a brand in terms of category, attributes, and competitive associations. This analysis helps teams identify and address any misrepresentations at the source, ensuring that the brand is accurately portrayed in AI outputs. Prompt Tracking is another key feature, revealing which real-world questions or prompts trigger mentions of a brand across supported AI systems. This insight allows marketers to prioritize the prompts that are most relevant to their visibility goals.
GEOScan is delivered as a platform that offers comprehensive visibility intelligence for the generative search landscape.
GEOScan is a SEO audit & analysis project. It focuses on understanding and improving how brands are cited and recommended by AI systems in generative search results. It is built as a B2B product for digital marketers. Pricing is paid, from $49. It runs on the web and API.
It is developed by GEOScan, and it first shipped in 2024. Key capabilities include AI visibility score, citation tracking, and entity analysis. The interface is available in English and Spanish. It exposes integrations via a public API.
Summary written by a language model from the project’s public pages.
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