Analyst Relations (AR) has long been a critical discipline for tech and B2B companies. When done well, AR:
- Shapes category definitions and trends
- Improves how you’re described in research reports and client briefings
- Builds credibility with buyers, partners, and investors
- Drives visibility that leads to shortlisting and sales opportunities
That traditional model of AR isn’t going away. But the world around it is changing.
The New Discovery Reality
Buyers no longer start their journeys exclusively in analyst portals or industry events, or even googling. Increasingly, they start with generative AI systems like ChatGPT, Perplexity or Gemini, asking questions like:
- “Who are the leading vendors in [category]?”
- “What are the best tools for [problem]?”
- “Which emerging players are disrupting [space]?”
That's a challenge. These systems can’t see what sits behind analyst paywalls. They rely primarily on open-web content. The articles, blog posts, news coverage, thought leadership, customer reviews, and public data available to be crawled and retrieved. As a result, even companies that analysts love can be less visible to LLMs if their footprint on the open web is too light. This is where GEO comes in, and why AR must evolve.
AR’s New Dual Mandate: Credibility and Discoverability
Traditional AR builds credibility. GEO-oriented AR ensures discoverability. In the GEO age, AR teams must bridge these two worlds.
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Traditional AR Strength
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Still Vital Because…
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Needs to Evolve Because…
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Building analyst relationships
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Drives accurate positioning, credibility, inclusion in reports, and trust with buyers.
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Analyst praise can be hidden behind paywalls, making it difficult for AI systems unless it’s published in a public, crawlable form. AR must work to release excerpts (in line with rules), secure media mentions, and push coverage out into the open web.
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Clarifying value proposition
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Analysts help you sharpen category fit, narrative, and market differentiation.
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That clarity must also be reflected in web-visible content using buyer/analyst language, so LLMs connect your brand with the right category and attributes.
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Influencing shortlists
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Analysts shape RFPs, market maps, and buyer shortlisting.
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More buyers now form AI-generated shortlists, which only include brands that appear in public sources. Analyst mentions must be repurposed as discoverable content.
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How AR Can Adapt for GEO
Here’s how AR teams can evolve their playbooks:
Publish Analyst Recognition in Public Spaces
- Work with analyst firms to release complimentary reports, excerpts, or quotes.
- Publish press releases, blogs, and infographics that reference your analyst achievements.
- Use structured data / schema markup so LLMs can associate your brand with the correct category.
Seed Authoritative Content on the Open Web
- Create thought leadership content echoing the terminology and market framing analysts use.
- Contribute to industry media, open benchmarking studies, and encyclopedic sources that AI systems crawl using analyst insights and references where possible / allowed.
- Maintain accurate brand and product profiles on LinkedIn, and similar platforms and use social media to echo analyst insights and sentiment.
3. Use Analyst Assets as Content Fuel
- Don’t stop at “we’re in the report.”
- Repurpose analyst recognition into blogs, social posts, sales enablement, and PR campaigns.
- Track LLM mentions of your brand as a new KPI alongside report inclusion.
AR can be a Growth Engine in the GEO Era
Analyst relations will always be about relationships and credibility. But in the GEO age, it must also be about visibility to AI-driven discovery systems. Being cited by analysts is valuable, but it also has to be seen by the LLMs that are beginning to shape buyer decisions.
By combining analyst influence with AI discoverability, AR can evolve from a reputation function into a true growth engine, ensuring that when buyers ask an AI “Who should we consider?”, your name is there.
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