Where this data comes from

AI answer engines — ChatGPT, Grok, Google AI Mode, Google AI Overview, Perplexity — are rapidly becoming the first stop for B2B software research. Buyers ask “what’s the best software for X” and receive curated answers with citations. Those citations function as recommendations.

Understanding which content gets cited — and why — is the new frontier of B2B visibility strategy. We used Rankscale to export citation data across a B2B software category, capturing every URL cited across multiple query themes and five regions.

The result is 8,571 total citation occurrences across 3,773 unique URLs and 1,767 distinct domains. Every number in this analysis is drawn directly from that dataset.

Vendors dominate — overwhelmingly

The single most important finding in the entire dataset: 60.3% of all AI citations point back to a vendor’s own website.

Not a journalist. Not an analyst. Not a review site. A software vendor, publishing content about its own category.

This finding holds across every content type we examined. Even in the broad “blog” category — which intuitively feels like independent editorial — it splits roughly half-and-half once you separate vendor content marketing from genuine independent publishing.

The implication is profound. AI visibility is not a PR and media relations challenge. It is a content publishing challenge — and the content you need to publish is primarily on your own domain.

Three content types capture nearly everything

Across 8,571 citations, the content landscape is surprisingly concentrated. Three URL archetypes — listicles, glossary pages, and review portals — account for the overwhelming majority of what AI engines cite.

Everything else — YouTube, Wikipedia, Reddit, LinkedIn, news media, academic research — fills in the remaining margin. Valuable, but not the primary battleground.

The top domains driving the conversation

Looking at the domains generating the most citations reveals the competitive landscape clearly. Note the mix of vendor-owned and third-party sources — and the relative absence of media or news outlets.

Listicles: the counterintuitive playbook that actually works

1,530 citation occurrences flow through “best X software” listicles. These are the single highest-volume citation type in the dataset.

The counterintuitive part: many of the highest-cited listicles are published by vendors themselves — and they include themselves in the ranking.

Vendors are openly writing “the best software in our category” posts, ranking themselves alongside competitors, and AI engines cite these pages as if they were neutral third-party assessments. The top-cited vendor-written listicle in our dataset is the second most-cited URL in the entire study — across all 3,773 URLs.

The “independent blog” category accounts for 25.7% of listicle citations — but this figure is likely overstated. Many of those sites are agency SEO content farms or vendor-adjacent publications rather than genuinely impartial sources. The true independent third-party share of listicle citations is closer to the comparison portal slice at around 12%.

This is not a grey area. Publishing a “best software in your category” post, including your own product, and doing it well enough that AI engines treat it as a credible source — this is the dominant playbook. Every week you don’t have that content is a week competitors collect citations you don’t.

Glossary pages are a quiet winner hiding in plain sight

887 citations go to definition-style “what is X” content. Of those, 71.2% are published by software vendors themselves.

This is the most lopsided finding in the dataset. When an AI engine answers “what is a CMMS?” or “what does CAFM stand for?”, it overwhelmingly cites vendor-published definition pages — not Wikipedia, not TechTarget, not academic sources.

The winning pages are not sophisticated. They are simple, well-structured definition pages that explain a category term clearly and completely. The leaders in this category — large platform vendors — don’t have anything technically impressive on these pages. They just have one well-structured definition page per acronym, and they published them years before the AI visibility conversation started.

The investment required is minimal. The upside — being the cited source every time a buyer asks what your category even means — is disproportionate. This is the clearest example in the dataset of a low-effort, high-return AI visibility play.

Review portals are AI infrastructure, not just sales tools

Gartner, G2, Capterra, Comparesoft, Software Advice, and TrustRadius appear in the dataset at a frequency that belies their relatively small number of cited URLs.

Gartner alone delivers 134 citations from just 23 URLs — a citation density of 5.8 per URL. That is the highest citation-per-page ratio of any major source category in the entire dataset. A single well-maintained Gartner Peer Insights profile generates more AI citations than almost any other content type on a per-page basis.

The implication is significant for how teams prioritise. Review platform maintenance has traditionally sat in the sales or customer success function — managing testimonials, requesting reviews, responding to ratings. The data reframes this completely. These platforms are AI visibility infrastructure.

An unclaimed, outdated, or poorly maintained listing on Gartner, G2, or Capterra is not just a missed sales signal. It is a missed AI citation — potentially thousands of times per month, across five AI engines, in every market where buyers are researching your category.

Reddit matters more than its citation count suggests

Reddit generates 109 citations in the dataset. That is a small number in absolute terms — 1.3% of all occurrences. But the distribution within that 1.3% is striking.

A single Reddit thread on a relevant subreddit ranks among the top 15 “best of” sources in the entire dataset — alongside content from major platforms, comparison portals, and well-resourced vendor blogs.

This is not a coincidence. LLMs treat peer-to-peer buyer conversations as high-trust signals. The reasoning is straightforward: real buyers comparing notes on industry subreddits are not optimising for search rankings or AI citations. The content is therefore treated as more authentic than vendor-published material.

The right play here is not aggressive community marketing. It is genuine participation — answering real buyer questions in relevant communities, without a promotional agenda. The citations that result are among the most valuable in the dataset because they signal buyer trust to AI systems.

Editorial media is nearly invisible to AI engines

This is the finding most likely to disrupt traditional B2B marketing budgets.

Only ~1% of citations in the dataset came from genuine editorial or news media. Trade press coverage, journalist features, industry analyst reports, and traditional PR placements are — in terms of AI citation volume — almost entirely absent from the citation landscape.

The brands generating the most AI citations are not doing more PR. They are not chasing analyst reports or trade press bylines. They are publishing relentlessly on their own domains.

The data suggests a clear reallocation of attention. Content resources that currently flow toward PR campaigns, journalist relationships, and media outreach should be partially redirected toward owned content publishing — specifically the three archetypes that generate the majority of citations: listicles, glossary pages, and optimised review profiles.

Geographic concentration is both a risk and an opportunity

88% of citations in this dataset come from a single region. The international spread — across four other major markets — accounts for only about 8% of all occurrences combined.

This finding cuts both ways. It is a risk for brands that assume AI visibility in one market translates globally. It does not. AI engines are regionalised in meaningful ways, and citation landscapes vary significantly across geographies.

But it is also an opportunity — specifically for brands with genuine international presence. The equivalent “best of” and “what is” content clusters in non-English markets are typically far less developed than their English-language counterparts. Competition for AI citations in Portuguese, Spanish, French, and German markets is dramatically lower than in English.

What to do with this data

The dataset paints a clear picture. AI visibility in B2B software categories is a content publishing challenge, not a PR or media relations challenge. The brands generating the most citations have mastered owned media — not earned media.

Six concrete actions follow from the data, ordered by the citation leverage each delivers.

Methodology

Citation data was exported from Rankscale across a defined B2B software category. The export covers 3,773 unique URLs and 8,571 total citation occurrences across five AI engines: ChatGPT, xAI Grok, Google AI Mode, Google AI Overview, and Perplexity. Five regions were included: GB (dominant at 88%), PT-BR, ES, PT-PT, and FR.

Vendor vs third-party classification: any domain with at least one product, product blog, or owned content row was treated as a software vendor. The top blog and listicle domains were manually audited and obvious vendor sites appearing only via blog content were reclassified. All remaining domains were treated as third party.

The “independent blog” category likely overstates genuinely impartial coverage. Many domains in this category are agency SEO content farms or vendor-adjacent publications. True independent third-party coverage is closer to the comparison portal slice.