Observed Signal · Feb 27, 2026 · Research Study · Source: https://martech.org/feed/ · Impact: 3/5 · Sentiment: Neutral
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.
Findings quantify how generative AI models cite B2B brands and show that many suppliers lack visibility; this affects discovery, demand generation, and SEO/GEO strategy as customers shift from traditional search to AI-driven answers.
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Key Takeaways & Evidence Grounding
- Research used Brandi to analyze more than 1,000 English-language prompts across 29 B2B brands and four AI engines: ChatGPT, Perplexity, Grok and Google AI Mode/Gemini.
- Only 21% of brands appeared in more than 25% of the AI answers; one-third of brands appeared in fewer than 5% of AI answers.
- Domains in the top 10 cited by AI averaged 25% visibility; brands outside the top 10 averaged 7.6% visibility.
- YouTube appeared among the top 25 cited domains for about 75% of brands; LinkedIn appeared in the top 25 domain citations for 37% of brands.
- Owned media was cited more than twice as often as earned media in AI answers for the B2B brands studied.
Connected Companies & Entities
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Related Market Signals & Shifts
Recent verified developments and strategic activity across this market segment.
B2B PR to Influence AI Buying Recommendations
MarTech published guidance on how B2B brands must adapt public relations and content strategies to appear in AI-generated answers that increasingly drive software buying decisions. Citing a March 2026 G2 survey of 1,000+ B2B buyers (71% use AI chatbots for vendor research; over half start buying with an AI query) and research from Magenta Associates showing five brands capture 80% of top AI responses in a category, the article argues brands need a "dual-path" PR approach. One path preserves earned media and backlinks for human discovery; the other focuses on structured content, consistent entity signals, and measurement of AI-driven decision outcomes so AI systems can parse, verify, and recommend vendors accurately. The piece also notes AI shortlists are often four to seven brands versus ten blue links on a Google results page and reminds readers MarTech is owned by Semrush.
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.
GEO Eats SEO: Get Cited in AI Answers
An industry analysis argues that search-engine ranking (SEO) is being supplanted for many users by Generative Engine Optimization (GEO): the practice of getting content explicitly cited inside AI-generated answers. The article cites SparkToro data showing fewer than one in three Google searches end in a click and claims Google’s AI Mode yields roughly 93% no‑click queries. It notes tools emerging to track brand citations across ChatGPT, Perplexity, Claude and Gemini, and cites Capston.ai projections that over 40% of product discovery will begin inside AI-native platforms by late 2026. The piece highlights Coinbase enabling AI agents with wallets and launching Coinbase Advisor, and warns that a June 12 U.S. export-control directive forced Anthropic to disable its Fable 5 and Mythos 5 models—illustrating that model availability is now a geopolitical risk. Recommended actions include testing citation presence across models, rewriting pages for extractable claims, and adopting provider diversity.
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