James Dooley speaks with Benjamin Tannenbaum about what people ask in ChatGPT, Gemini and other large language models because AI search changes query structure and compresses the funnel. They explain that prompts are longer, more specific and often more personal than Google keywords or Reddit posts, which forces marketers to adjust content coverage and distribution. Benjamin Tannenbaum describes search density, one shot behaviour, and why brands should update key pages for high priority intents because relevance to specific constraints increases selection in AI answers.Where to Listen to This EpisodeAI Search Data Reveals How Users Actually Think is available across all major podcast platforms. Choose your preferred platform below.Listen to AI Search Data Reveals How Users Actually Think on TransistorListen to AI Search Data Reveals How Users Actually Think on Pocket CastsListen to AI Search Data Reveals How Users Actually Think on Amazon MusicListen to AI Search Data Reveals How Users Actually Think on AudibleListen to AI Search Data Reveals How Users Actually Think on CastroListen to AI Search Data Reveals How Users Actually Think on CastboxListen to AI Search Data Reveals How Users Actually Think on Podcast AddictListen to AI Search Data Reveals How Users Actually Think on DeezerListen to AI Search Data Reveals How Users Actually Think on RephonicListen to AI Search Data Reveals How Users Actually Think on MetacastListen to AI Search Data Reveals How Users Actually Think on Player FMListen to AI Search Data Reveals How Users Actually Think on SpotifyListen to AI Search Data Reveals How Users Actually Think on Listen NotesListen to AI Search Data Reveals How Users Actually Think on Podcast GuruListen to AI Search Data Reveals How Users Actually Think on PodchaserListen to AI Search Data Reveals How Users Actually Think on PodverseListen to AI