Observed Signal · Jul 23, 2026 · Research Study · Source: https://martech.org/feed/ · Impact: 3/5 · Sentiment: Neutral
Semrush: ChatGPT Shows No Clear Brand Leaders
A Semrush analysis of 1,094 U.S. topic categories found that ChatGPT (LLM) responses rarely name a single, consistent brand owner across buyer questions. Only 15.2% of categories met Semrush’s threshold for a clear leader (appearing in four of five prompts and leading by ≥5 percentage points), leaving 31.2% with an emerging leader and 53.7% with no consistent leader. Visibility varied by question type and was especially fragmented in the highest-demand categories, which accounted for 98% of AI search volume yet produced just 11.3% clear owners. Semrush also found that traditional SEO metrics only partially predict AI visibility: branded search volume correlated with category ownership, while organic traffic, Authority Score, and citation counts often did not.
Study from a major SEO vendor (Semrush) highlights how LLM-driven answers fragment brand visibility and shows that conventional SEO metrics only partially predict AI visibility—important for marketers but not an industry-shifting platform policy or technical change.
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Key Takeaways & Evidence Grounding
- Semrush analyzed 1,094 U.S. topic categories using five buyer prompts (definitions, comparisons, alternatives, use cases, purchase decisions).
- Only 15.2% of categories (166 categories) met Semrush’s criteria for a clear brand leader.
- 31.2% of categories had an emerging leader (brand appeared in at least three prompts without a decisive lead); 53.7% had no consistent leader.
- Among the half of categories with the most AI search activity, only 11.3% had a clear owner; those high-demand topics represented 98% of AI search volume in the study.
- Branded search volume aligned with category ownership, while organic traffic, Authority Score, and citation counts often did not; only 21% of the most-cited domains were also the brand most frequently mentioned in ChatGPT responses.
Connected Companies & Entities
2 Entities mapped“A Semrush analysis found that only 15.2% of topic categories had a clear brand leader across a series of related buyer questions, suggesting...”
“OpenAI is testing multi-advertiser placements in ChatGPT while adding new targeting and campaign tools that expand its ad platform....”
Ontology Mapping & Concepts
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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.
AI Engines Disagree by 2× on Which Brands to Recommend
Treyci, an AI visibility intelligence platform, released measurement data showing that major AI engines (ChatGPT, Perplexity, Gemini, Grok) sharply disagree on which brands to recommend in buying-intent queries. In one B2B software category, one engine referenced tracked brands in 81% of answers while another did so in only 43%, a nearly two-fold visibility gap. The study scored over 1,200 AI answers from 100 buying-intent questions per category, repeated three times per engine monthly. Key findings: AI answers are probabilistic (same prompt yields different vendor lists across sessions), engines cite third-party reviews and publications rather than vendor websites, and adoption is ahead of measurement—only 41% of 100 B2B SaaS companies published llms.txt files. Founder Keith Schilling emphasizes that brands must measure the distribution of answers across engines, not rely on single screenshots.
Study: AI visibility often diverges from SEO rankings
Fractl analyzed how three large language models (GPT-4o, Gemini 2.5 Flash, and Claude Sonnet 4.6) referenced brands across eight industries and compared those references to traditional SEO metrics from Ahrefs. While more than 90% of brands showed alignment between search authority and AI visibility, notable outliers existed: about 5% of brands (471) were underrepresented in model responses and about 4% (377) overperformed relative to their SEO footprint. Only 11% of brands were referenced by all three models, and model-specific recall patterns (e.g., Claude favoring SaaS/insurance, Gemini favoring travel/healthcare) create measurement and strategy challenges. The study concludes brands should measure AI recall separately, strengthen third-party corroboration, and fix categorization signals to improve AI recall.
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