The GEO Show

Welcome to episode 23 of The GEO Show, the briefing on generative engine optimization, LLM citations, and AI search visibility. Brought to you by GEOforge.

In this episode, Paris Childress, founder of Hop AI and co-founder of GEOforge, records a September 8, 2026 solo news roundup. The lead story is Semrush and Exploding Topics finding that 57.5% of AI users said chatbot information caused them not to buy, then nine more beats on mentioned versus chosen, single-check misclassification, Reddit citation collapse, five-engine source overlap, Google AI Mode citation architecture, production UI collection APIs, Claude retrieval versus citation, historical AI data moats, and Mastercard's agent shopping forecast.

In this episode:

πŸ›’ Semrush/Exploding Topics: AI talks buyers out of purchases
A vendor-sponsored Semrush and Exploding Topics survey of 2,338 US adults (Sept 7) found 57.5% of AI users said chatbot information caused them not to buy. 65% said AI had at least partially replaced Google for product research. Among weekly AI users, 73.6% bought from an organic AI recommendation. Paris's GEO take: purchase exclusion, reputation, and buyer risk now sit beside discovery.

πŸ“Œ  Latent Space: mentioned is not chosen
Latent Space's Frontier AI visibility tracker (6,762 answers, 161 categories) shows Kysely in 42/42 answers but first choice only once. GPT-5.6 Sol and GPT-6 Astra category leaders differed in 33/121 comparable categories. Mention share of voice can overstate commercial visibility; recommendation role and sentiment matter.

🎲 Surfaced by: one AI check can misclassify visibility
Across 536 combinations with at least five checks, 80% of appearance cases were inconsistent; a single check matched the majority only 72.2% of the time on inconsistent sets. Paris: target roughly 30 to 40 runs per prompt before volatility flattens.

πŸ“‰ Surfaced by: ChatGPT Reddit citations 37.9% to 3.4%
In fixed cohorts across two 14-day windows, ChatGPT Reddit citations collapsed while Perplexity (50% to 44.7%) and Gemini (30.8% to 33.7%) stayed comparatively stable. Off-site GEO must be engine-specific.

πŸ”—  Intender: only 8% source overlap across five engines

27,924 citations from 3,600 searches: 8% overlap across all five platforms; 71% of 4,625 domains on one engine only; 65 domains in all five. No single AI citation ecosystem.

πŸ—ΊοΈ Nicholas Sitter: Google AI Mode citations flip by question type
Entity-wrapped citations: 87.6% for recommendation-style prompts, 19.8% for explanatory prompts, 0% for generic informational queries. Tag and report prompts by buyer stage and intent.

πŸ”Œ querying.ai: production UI collection as a GEO API
Real customer-facing responses across seven surfaces from about $20/month, not model API output. Paris: UI and API results diverge in testing; API-only trackers can mislead.

πŸ§ͺ Is My Brand in AI: Claude retrieval vs citation
Named-brand sites retrieved in only 33% of run-brand pairs via Claude API web search; 62.7% of retrieved domains cited. Shaky design (API + three runs), but retrieval and citation still need separate metrics.

πŸ›οΈ Similarweb: historical AI visibility as a data moat
If nobody sampled an answer when it happened, replaying the prompt today does not reconstruct it. Historical depth separates data companies from prompt trackers.

πŸ€– Mastercard: AI agents shopping and paying by 2030
Forecast: 300M-plus shoppers may routinely use AI agents to shop and pay by 2030. Teen trust signals already lean agentic. Paris: build agent-ready sites across discovery, recommendation, selection, and transaction.

If this briefing is useful, subscribe to The GEO Show so we can keep walking through the studies, platform changes, and citation data that actually move AI visibility.

πŸ’¬ Question: If AI is already talking buyers out of purchases, does your GEO reporting still stop at whether you were mentioned?

What is The GEO Show?

The GEO Show is about generative engine optimization (GEO) and AI search: how B2B brands win AI visibility in ChatGPT, Perplexity, Google AI Overviews and AI Mode. Each episode breaks down what is changing in the way AI assistants and answer engines find, cite, and recommend brands, and what marketers should do about it.

The show is built for B2B SaaS marketers, SEO and content leads, and founders who want their brand to show up when buyers ask AI for answers instead of scrolling a page of blue links. If you own organic growth, demand generation, or brand, you will come away with practical GEO tactics you can test, a clear read on the latest AI search news, and better ways to measure AI visibility when traffic alone no longer tells the whole story.


Episodes mix a few formats:




  • Solo deep dives on GEO strategy, from how large language models choose which sources to cite to how content, earned media, and brand mentions shape AI answers.


  • News breakdowns on the latest moves from OpenAI, Google, Perplexity, and the rest of the AI search landscape, and what each change means for your pipeline.


  • Expert guests, including SEO and GEO practitioners, content and PR leaders, agency operators, and founders building for AI search.


  • The Friday catch-up with regular co-host Simon Young of Question.Marketing, where the two unpack the week's biggest AI search stories and debate what actually works.


Your host is Paris Childress, CEO of Hop AI and co-founder of GEOforge. Paris brings a practitioner's view of GEO and AI visibility, focused on what B2B teams can apply right away, not hype.


Learn more about GEOforge at https://getgeoforge.com.


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