Observed Signal · Feb 26, 2026 · Research Report · Source: https://martechseries.com/feed/ · Impact: 3/5 · Sentiment: Negative
B2B Brands Risk Obscurity on AI Platforms, Study Finds
SEMAI analyzed 25,540 URLs cited by ChatGPT, Google Gemini, and Perplexity over a 60-day period and found each AI platform cites materially different content types. Blogs (41–55%) and webpages (38–47%) together account for more than 90% of AI citations, but platforms diverge on niche sources: ChatGPT cites LinkedIn, Wikipedia, and academic/research-backed content more than Gemini or Perplexity; Perplexity emphasizes comparison and solution pages; Gemini favors brand-owned blog content and avoids community sources. SEMAI argues that optimizing for a single channel (e.g., Google) can leave B2B brands invisible to buyers who begin research on AI platforms. SEMAI’s visibility platform tracks ChatGPT, Perplexity, Gemini, and Claude and offers LLM search volume metrics, cluster classifications, and AI-generated content calendars; a free AI visibility audit is available on its site.
Study reveals that major AI search/LLM platforms cite different content types, meaning B2B marketers optimizing only for Google risk losing visibility across AI-driven discovery — this has direct implications for content strategy and measurement.
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Key Takeaways & Evidence Grounding
- SEMAI analyzed 25,540 URLs cited by ChatGPT, Google Gemini, and Perplexity over a 60-day period.
- Blogs account for 41–55% of AI citations; webpages account for 38–47%; together they drive over 90% of citations.
- ChatGPT cited LinkedIn posts (1.1%), Wikipedia (2.0%), and academic/research-backed content (2.2%) at higher rates than Gemini or Perplexity.
- Perplexity cites comparison and solution-specific pages at scale; Gemini prefers brand-owned blog content and largely avoids community sources.
- SEMAI’s platform tracks brand visibility across ChatGPT, Perplexity, Gemini, and Claude, providing LLM search volume, Weak/Average/Strong cluster classification, and AI-generated content calendars.
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Boosting B2B Brand Visibility in Generative AI Responses
MarTech published an analysis using the GEO tool Brandi to measure how often B2B technology brands are cited in generative AI answers. The study tracked over 1,000 English-language prompts across 29 B2B brands and four AI engines (ChatGPT, Perplexity, Grok and Google AI Mode/Gemini). Key findings: many B2B suppliers have low AI visibility (only 21% of brands appeared in more than 25% of relevant AI answers; one-third appeared in under 5%), owned website content drives more citations than earned media, and multimedia and platform content (YouTube videos, LinkedIn long-form posts) materially affect citation rates. Wikipedia and Reddit proved less important for B2B citations. The author concludes B2B companies need data-driven GEO strategies that include owned content, video, and platform-specific content to improve presence in AI-generated responses.
AI Visibility Depends on Who Writes About Your Brand
AI-generated answers are becoming a distinct discovery channel with different citation signals than traditional Google rankings. Multiple studies and vendor experiments (BrightEdge, Moz, Muck Rack, Semrush, Ahrefs) show large gaps between pages that rank in Google’s organic top 10 and sources cited by AI Overviews or chat-based engines: independent editorial coverage and bylined author entities are strongly favored. The article recommends treating earned media as infrastructure (lead with the claim, use named credentialed authors, maintain steady distributed placements, refresh quarterly) and measuring "citation share" across AI engines (ChatGPT, Google AI Mode/Gemini, Claude, Perplexity) to track where buyers actually find brand recommendations. The piece frames the May 2026 Google core update and the rise of AI Mode/AI Overviews as evidence that marketers must add AI citation tracking to SEO and PR workflows.
Business sites dominate Gemini’s local AI citations
Steady Demand analyzed 1,487 local-service queries (14,472 citations) across 50 U.S. metropolitan areas and 10 verticals, finding AI-driven discovery is fragmented across engines, locations, and categories. Gemini cited business websites in nearly 60% of cases—outperforming directories, review platforms, and forums—while ChatGPT cited Reddit and directories more often. Repeating identical Gemini queries produced overlapping cited sources only about 40% of the time (grounding drift), and Gemini returned the same top business in roughly 7% of repeats. Cross-engine overlap was low: Gemini and ChatGPT cited the same domains only ~8% of the time and named the same top business in 4.2% of identical prompts. By contrast, Google’s local pack showed ~90% top-result stability. The report recommends SMBs monitor multiple AI engines and run repeated queries to measure AI visibility.
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