10 Analyst Firms, 1M+ URLs: One Firm Owns the Citations, and It Is Not the Research You Think
Gartner. Forrester. IDC. The big three names in industry analyst research influence trillions in annual enterprise IT spending decisions. For four decades, their Magic Quadrants, Waves, and MarketScapes have shaped how enterprise buyers pick vendors. So when AI search engines answer “what’s the best CRM platform” or “who leads in cybersecurity services,” you would expect analyst research to be front and center.
OtterlyAI analyzed 1,028,959 unique URLs cited across six AI Search platforms (ChatGPT, Google AI Overviews, Google AI Mode, Perplexity, Gemini, and Microsoft Copilot) over a 24-hour window, then filtered to citations from 10 recognized analyst firms’ own websites.
Two findings stand out, and together they rewrite the assumption above. First, Gartner owns 81.7% of all analyst-relations-site citations. Second, 96% of Gartner’s citations come from its Reviews product, not its analyst research. AI engines are citing Gartner’s user-review directory, not its Magic Quadrants.
Key Findings (TL;DR)
- One firm dominates. Gartner accounts for 81.7% of all analyst-relations-site citations in the dataset. S&P Global (home of 451 Research) is a distant second at 12.3%. Every other firm sits below 2.5%.
- It is not the research getting cited. 96% of Gartner’s citations point to its Reviews subfolder (gartner.com/reviews/), the peer-review product. Only 4% come from Gartner’s research documents, articles, newsroom, and everything else combined.
- Review category pages do the heavy lifting. Gartner Reviews “Market” pages alone (comparison pages like “best supply chain planning solutions”) drive 78.8% of all Gartner citations and 82.1% of Gartner’s review citations.
- The flagship research barely registers. Gartner’s gated research documents accounted for under 1% of its citations.
- Two firms scored zero. HFS Research and Constellation Research recorded zero citations in 24 hours.
- The Gartner paradox stands. Gartner blocks GPTBot, ChatGPT-User, OAI-SearchBot, Google-Extended, and CCBot in robots.txt, yet still dominates. Its visibility flows through indirect channels, which makes the position fragile.
What Is Analyst Relations, and Why Does It Still Matter?
Analyst relations (AR) is the discipline of building relationships with industry analyst firms that publish research, evaluations, and forecasts about technology markets. Firms like Gartner, Forrester, and IDC employ thousands of analysts who cover specific categories: cybersecurity, cloud infrastructure, CRM, AI platforms. They produce comparative evaluations (the Magic Quadrant, the Forrester Wave, the IDC MarketScape) that enterprise buyers reference when making technology decisions worth millions of dollars.
AR teams at technology vendors invest heavily in influencing these analysts. Briefings, demos, customer references, and analyst days all feed into how a vendor gets positioned. The output shapes procurement shortlists, vendor selection committees, and the language used in enterprise RFPs. The premise of the whole discipline is that analyst research carries third-party authority.
This study asks a narrower question: when AI search engines answer buyer questions, do they cite that analyst research? The data says they cite something else entirely.
Two firms (Omdia and GlobalData) operate large owned trade publication networks. The other eight are single-domain publishers. That structural difference turns out to matter a lot for AI visibility.
Scope of Study
OtterlyAI monitored 1,028,959 unique URLs cited across the six AI Search platforms over a 24-hour window. From that dataset, we filtered to citations from the primary websites of 10 analyst firms: Gartner, Forrester, IDC, ISG, HFS Research, Everest Group, Constellation Research, S&P Global (451 Research), Omdia, and GlobalData.
For each citation we recorded the firm, the cited URL, the URL’s subfolder or content type, the citation count, and whether the domain blocks major AI crawlers in robots.txt.
Two notes on scope. This analysis counts citations to the analyst firms’ own domains only. It excludes owned trade publications (covered in the trade-pub note below). And a 24-hour window is a snapshot. Citation patterns shift with prompt volume, AI engine updates, and indexed content freshness.
Where Analyst Citations Actually Come From
Finding 1: Gartner Owns the Category
When you rank the 10 firms by their own-domain citation share, the distribution is steep.
Gartner.com and spglobal.com together hold 94% of all analyst-relations-site citations. The remaining eight firms split the last 6% between them, and two of them (HFS Research and Constellation Research) recorded less than 0.2% of all AI citations.
Finding 2: AI Cites Gartner Reviews, Not Gartner Research
This is where the story turns. We broke Gartner’s citations down by which part of gartner.com they pointed to.
96% of Gartner’s citations come from its Reviews product (gartner.com/reviews/), the peer-review platform formerly known as Gartner Peer Insights and Gartner Digital Markets. This is user-generated review content, where verified practitioners rate software they use. It is not the analyst research that AR teams spend years and six-figure budgets trying to influence.
The single biggest driver is Reviews “Market” pages: comparison and category landing pages like “best innovation management tools” or “best supply chain planning solutions.” These pages alone account for 78.8% of all Gartner citations.
Meanwhile, Gartner’s gated research documents (the Magic Quadrants and analyst reports that define the firm’s reputation) accounted for under 1% of its citations. The most prestigious analyst content in the industry is close to invisible in AI answers. The crowdsourced review directory is what gets cited.
Why does this happen? Review category pages are structured exactly the way AI Search engines like to cite. They answer a clear buyer question (“what are the best tools in category X”), they are openly accessible rather than paywalled, they carry a consistent comparison format, and they are widely linked from vendor sites and third-party pages. The flagship research has the opposite profile: gated, long-form, and behind a login.
Finding 3: The Role Of Trade Publications: Where Omdia & GlobalData Really Live
Two firms in the dataset have a meaningful trade-publication footprint, and for one of them, that footprint is the only visibility they have.
| Analyst firm | % from own site | % from Trade pubs |
|---|---|---|
| Omdia | 0.7% | 99.3% |
| GlobalData | 43.6% | 56.4% |
| S&P Global | 99.6% | 0.4% |
| Gartner | 100% | 0% (no trade network) |
| Forrester | 100% | 0% (no trade network) |
| Everest Group | 100% | 0% (no trade network) |
| ISG | 100% | 0% (no trade network) |
| IDC | 100% | 0% (no trade network) |
Omdia is the clearest example of a structural visibility inversion. Only 0.7% of Omdia’s citations come from the Omdia brand domain (omdia.tech.informa.com). The remaining 99.3% flow through the parent network around it, with techtarget.com delivering the vast majority. Omdia analysts are doing the analyst work, but the citation value is flowing through TechTarget’s editorial properties, which do not block AI crawlers.
This matters for AR teams. Pitching an Omdia analyst for inclusion in a research report is a slow, relationship-driven process. The reward, in AI visibility terms, is a citation on omdia.tech.informa.com that captures less than 1% of the parent group’s AI footprint. Pitching the same story to a TechTarget editor for coverage on SearchStorage or ComputerWeekly delivers citations through domains that the AI engines actively index and reference, capturing the other 99% of the visibility. Same parent company, completely different visibility math.
GlobalData shows a similar pattern at smaller scale. 56.4% of its AI footprint comes from trade properties: Verdict, Pharmaceutical Technology, Clinical Trials Arena, and the Mining/Power/Offshore/Ship/Airport Technology network. The main globaldata.com domain delivers only the minority share.
The other eight analyst firms in the dataset have no trade publication network at all. Their entire AI visibility footprint depends on their primary research domain. If that domain has a content access problem (paywall, robots.txt, JavaScript rendering issue, crawl failure), there is no secondary channel to fall back on.
This is one of the strongest single takeaways from the data. Owning a trade publication network is a structural advantage in AI visibility. Single-domain analyst firms have nowhere else to surface.
Finding 4: The Gartner Paradox: Blocking the Bots While Dominating the Citations
Gartner accounts for 81.7% of analyst-relations-site citations. Gartner also blocks the major AI crawlers in its robots.txt according to OtterlyAI’s Crawlability Checker:: ChatGPT (GPTBot, ChatGPT-User, OAI-SearchBot); Google-Extended, and CCBot.
- GPTBot (OpenAI’s training crawler)
- ChatGPT-User (OpenAI’s user-triggered fetch agent)
- OAI-SearchBot (OpenAI’s search index crawler)
- Google-Extended (Google’s AI training crawler)
- CCBot (Common Crawl, used by multiple AI training datasets)
How Is Gartner Still Getting Cited?
Other AI Search Engines: Gartner.com is still very much getting cited via other AI Search Engines like Google AI Mode; Google AI overviews and others.. A few mechanisms explain how the citations still flow.
Bing’s pre-existing index. ChatGPT Search, Microsoft Copilot, and Perplexity all draw on Bing’s index for live search results. Bing crawled Gartner long before Gartner’s current robots.txt rules were in place, and Microsoft Bing’s crawler (Bingbot) is not in the blocklist. So Gartner content sits in Bing’s index, and AI engines query that index for citations.
Third-party citation chains. Vendors quote Gartner statistics on their own websites with “according to Gartner” attribution and a link back to gartner.com. AI engines crawl the vendor pages, see the Gartner attribution, and surface gartner.com as the source. The original Gartner page does not need to be re-crawled for the citation to occur.
Pre-blocking indexed content. Gartner’s robots.txt block was tightened progressively over 2024 and 2025. The Gartner content currently being cited is largely pre-block crawl. As that index ages, the citation supply will increasingly shift toward press releases, predictions, and free analyst commentary that Gartner still allows on more open subdomains.
Forrester and IDC Go the Other Direction
While Gartner closes doors, two of its main competitors are integrating natively with AI platforms.
Forrester launched Forrester AI (originally called Izola) in 2023 as a generative AI tool trained exclusively on Forrester research. In March 2026, Forrester certified its AI app for Microsoft Teams. In April 2026, Forrester launched a Forrester AI agent for Microsoft 365 Copilot, available free to existing Forrester license holders. The strategy: keep the research gated, but make it accessible inside the productivity tools where buyers and analysts already work.
IDC went further. In December 2025, IDC announced a collaboration with AWS to integrate IDC’s full research catalog (billions of analyst-validated data points) into Amazon Quick Research, an AI-powered research agent inside Amazon Quick Suite. Quick Research draws on IDC’s analyst-validated intelligence to answer business research queries for AWS customers. AWS picked IDC explicitly, noting they wanted to partner with firms that brought “very high-quality, very deep insights.”
These are different bets. Gartner is betting that gated AI inside the paywall (AskGartner) will hold long-term subscription value, even if it costs public discoverability. Forrester is betting on the Microsoft channel as the primary distribution surface for AI-mediated research. IDC is betting on embedded licensing into cloud AI platforms.
If you believe AI-mediated discovery becomes the dominant research workflow for enterprise buyers over the next three to five years, the Forrester and IDC strategies look better positioned than Gartner’s. If you believe enterprises continue to pay for gated AI access because their internal data needs that protection, Gartner’s strategy holds. The dataset will tell us which is right within 18 to 24 months.
What This Means for GEO Teams
The data points to three operational shifts for marketers, content strategists, and SEO leads working on AI Search visibility.
1. Check that your website is not blocking AI Search bots.
Gartner blocks the major AI crawlers in its robots.txt, yet still leads on citations because Bing’s legacy index and decades of third-party links carry it. Most brands have no such cushion. If the bots cannot reach your content, your AI visibility is capped before any other work begins.
For any team that has not audited its crawl posture in the last 12 months, this is the highest-impact thing to check. The block is often unintentional, set by a security team or a CDN default rule, and the cost stays invisible until you measure it. Run your domain against GPTBot, ChatGPT-User, OAI-SearchBot, Google-Extended, and CCBot, then fix what is blocked.
2. Build the content format that gets cited.
The citation data shows AI engines reaching for structured comparison pages, not prestige assets. Gartner’s most-cited content is its review category pages, which answer one clear buyer question, stay openly accessible, and use a consistent layout. That is a repeatable template you can apply to your own pages: question-led headings, open access, structured comparisons, and content other sites want to link to. Reference-grade pages get cited; gated long-form does not.
3. Pitch where the citations live.
Analyze which exact domains and URLs AI Search engines cite for the prompts that matter in your category, then concentrate content and digital PR effort there. The cited source is often not the one with the best brand name, so chase the citation data rather than the reputation. Depending on your category, your GEO strategy may not require analyst-relations placements at all.
What This Means for Enterprises and Analyst Relations Teams
If your company works with analyst firms, this data changes how you should think about that investment. Three points matter.
1. Know which type of content gets cited.
The prestige asset and the cited asset are not the same thing. AI engines pulled 96% of Gartner’s citations from its Reviews product, and under 1% from its research documents. A Magic Quadrant placement still carries weight in sales cycles and procurement, but it is close to invisible in AI answers. When you brief an analyst or negotiate a research engagement, ask where the resulting content will live and whether that location gets cited. A mention inside a gated report has a different AI footprint than a presence on an openly crawlable review or category page.
2. Know which analyst firms get cited.
AR budget is finite, and the citation distribution is lopsided. Gartner and S&P Global together hold 94% of analyst-site citations in this dataset. Most other firms barely register, and two recorded nothing in 24 hours. That does not make those firms worthless, since analyst influence runs through briefings, advisory, and buyer trust that never show up as a citation. But if AI visibility is one of your goals, weigh each firm’s citation footprint before committing spend, rather than assuming every recognized analyst name carries equal AI weight.
3. Keep your reviews and positioning on brand, because AI reads them.
Since review pages are what AI engines cite, your presence on those platforms is now an AI visibility lever, not just a sales-enablement checkbox. Make sure your profiles on Gartner Peer Insights, Gartner Digital Markets, and similar review platforms are complete, current, and consistent with how you describe yourself everywhere else. Encourage verified customer reviews so your category presence is strong. Keep your product naming, category framing, and key differentiators on brand across these platforms, so the signals AI picks up from third-party review sites match the story you tell on your own site. Inconsistent positioning across these sources gives AI engines mixed signals about what you are and which category you compete in.
Final Conclusion
The answer to the title question is yes and no.
Yes, analyst-relations content matters for AI visibility, but in a narrower and stranger way than expected. Gartner dominates, holding 81.7% of analyst-site citations, and analyst brands do surface for enterprise tech queries.
No, it is not the analyst research doing the work. 96% of Gartner’s citations come from its crowdsourced Reviews product, and its flagship research documents account for under 1%. AI engines are citing a user-review directory that happens to live on an analyst firm’s domain. For the other nine firms, most are barely visible at all.
For GEO-SEO teams, the lesson is concrete. The asset that earns AI citations is a structured, openly accessible, question-led comparison page, not a prestigious gated report. Chase the format that gets cited, audit your crawl access so AI engines can reach it, and measure what AI references in your category rather than what looks impressive on a slide.
Got a GEO experiment idea? Let’s collaborate
At OtterlyAI, we don’t write about AI Search from the sidelines. We test it. With the community, we run and update a public GEO Experimentation Tracker showing what we are running and what moved AI Search. If you are running your own GEO experiment, email rick.tousseyn@otterly.ai and we may feature it with your name attributed.
👉 Want to measure your AI Visibility? Start with OtterlyAI and our GEO Guide.
👉 Want to check if you are accidentally blocking AI crawlers like Gartner is? Run your domain through the OtterlyAI Crawlability Checker inside the GEO Audit.
