geo-gap-fixer

A brand visibility audit on LLMs measures how often language models recommend your brand versus competitors, identifying specific recommendation gaps so you can generate a prioritized content backlog to close them.

A GEO action plan is a prioritized content backlog generated from an LLM visibility audit, providing actionable content recommendations to increase your brand's recommendation frequency over competitors.

Yes, you need API keys for OpenAI, Anthropic, Google, and Perplexity, along with Python and dependencies like openai, anthropic, and google-genai, to execute the LLM visibility audit and generate the GEO action plan.

To generate a content strategy when LLMs recommend competitors, you run an LLM visibility audit to identify the specific gaps and output a prioritized content backlog with actionable content recommendations to fix them.

The best way to measure brand visibility across multiple LLM platforms is to perform a point-in-time LLM visibility audit using OpenAI, Anthropic, Google, and Perplexity APIs to compare your recommendation frequency against competitors.

The limitation of a point-in-time LLM brand visibility audit is that it captures recommendation frequency and competitor gaps at a single moment, meaning LLM outputs may shift and require repeated audits to track ongoing visibility changes.