Frequently asked questions about AI Discovery.

It examines how AI models guide a user from a need to categories, products, brands and retailers.

The audit draws on ideas familiar from SEO, AEO and GEO, but its purpose is to measure actual model answers and recommendations.

From consumer needs, search-demand data, category questions, brand communication, competitors and purchase scenarios.

Yes. We use available demand signals and search language, then translate them into natural conversations with AI.

The scope can include ChatGPT, Gemini, Google AI Overviews, Meta AI, Perplexity and Claude.

Users often ask for specific brands, products, prices or availability only in the second step.

AI models are probabilistic, so we repeat prompts and measure answer stability.

Yes. In a controlled audit we limit the effect of user history and add persona context deliberately.

We do not pretend to know the full prompt volume inside closed systems. We use demand data and search signals as the best available proxy.

We measure similar phenomena, but deliver a tailored audit, interpretation and recommendations rather than another standard dashboard.

An executive summary, KPIs, a use-case map, competitive analysis, follow-ups, sources and specific recommendations.

Yes. The report can serve as a direct brief for marketing, ecommerce or agency teams.

Yes. A rerun shows whether implementation changed model answers.

We do not promise quick “ranking in ChatGPT.” We first diagnose the situation and identify the actions most likely to matter.

We examine which sources support the answers, whether retail reinforces or dilutes the message, and where gaps exist.

It depends on scope: a screening can take around two weeks, while a deep-dive typically takes several weeks.

Yes. Project scope, inputs and results are treated as confidential.