Resonance launches GEO Search: the AI visibility engine for B2B technology brands

• 110,000 LLM queries. 463,000 web searches, 113 B2B tech sectors. 946,000 brand mentions
• As 89% of buyers now use generative AI during their vendor research, the new battle isn't SEO, it's being selected by AI.

LONDON, Nov. 10, 2025 /PRNewswire/ -- Resonance today announced the launch of GEO Search, a free tool that allows B2B brands to see exactly what generative AI models say about them during the buying process and what drives visibility.

Built on the largest AI search research project carried out to date in B2B technology marketing, GEO Search is powered by over 100,000 buyer-intent prompts run through the latest generation of large language models, generating more than:

• 946,000 brand mentions from 34,000 companies
• 1 million URL citations categorised
• 113 B2B tech sectors benchmarked

The findings reveal that AI search is creating a new battleground for visibility and that public relations and earned media are now the primary drivers of whether a brand appears in LLM-generated buying recommendations.

Recent research from Forrester indicates that 89% of B2B buyers now use large language models (LLMs) like ChatGPT, Claude, and Gemini at some point during their vendor research. Unlike traditional search, AI does not return a list of links. Buyers no longer click through to ten blue links. The shortlisting now happens inside the model. It generates a single answer, and that answer influences vendor selection.

"If you are not visible in AI answers, you are invisible to the buyer," said Claire Williamson, Founder and CEO of Resonance.

Key Findings from the GEO Study

Across 100,000 prompts, there were four constants:

• Earned media drives AI visibility: Publications are the number one source LLMs cite when shortlisting vendors.
• Analyst reports and peer-review sites dominate during evaluation (like G2, Gartner, IDC, TrustRadius)
• One size does not fit all, GEO visibility varies by sector. Cybersecurity buyers read different sources than DevOps buyers. DevOps buyers read different sources than Cloud Infrastructure buyers. There's no single algorithm, you must understand your category.

"The myth is that AI search is random. It isn't," said Tom Fry, CTO and co-founder "LLMs follow patterns, and those patterns can be influenced. Once you know which sources AI trusts in your category, you can shape visibility. The research proves that in AI search, citations and brand mentions are the new clicks."

A new category of search

GEO Search introduces a new category: GEO Search Engine for brands. Instead of showing web results, GEO Search:

• Reveals the questions buyers are asking inside LLMs ("Best DevOps platforms for scale")
• Shows the answers LLMs generate in real time
• Exposes which competitors appear beside the brand
• Reveals how the LLM is framing the brand's positioning

Users can simply enter their brand or category and instantly see how AI responds. "For the first time, brands can see the AI 'shortlist' they're being compared on. This isn't SEO anymore. This is LLM-based vendor selection."

Resonance is making GEO Search available free to the public so that every brand can understand how they show up inside AI-driven research.

Try GEO Search:
https://geosearch.co/

The AI visibility problem

Most marketing teams assume that showing up on Google means showing up in generative AI answers. That assumption is now false. GEO Search testing shows three emerging shifts:

1. AI introduces new competitors for incumbent brands
2. Some brands are framed incorrectly
3. Many brands are missing entirely

Resonance helps brands influence their AI positioning, from buyer narrative ownership to content and messaging signals that LLMs trust, Resonance runs AI visibility programmes for B2B technology brands.

Methodology (for analysts / press)

• 113 B2B tech segments analysed (from cybersecurity to orchestration platforms)
• 500 buyer-intent queries per segment
  (covering awareness → evaluation → purchase decision)
• Queries run in buyer context using persona + intent overlays
• LLM outputs analysed for:
• brand mentions in answers
• URLs cited
• source types (media, analysts, peer reviews, communities, vendor)

Segments follow 12 intent types including:

• informational
• benchmarking
• comparison
• purchase decision
• technical evaluation
• risk/compliance
• community validation

Full dataset & visual explorer:
https://geosearch.co/

Media contact
Priscillia.chun@resonancecrowd.com
Account Director

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