Published
This leaderboard ranks the source domains AI engines actually pull from when answering sales-tool questions, measured across ChatGPT, Gemini, Google AI Mode, and Perplexity over the 30 days ending June 18, 2026.
The pattern is blunt and it repeats all the way down the list: engines reach for discussion and explanation first, and for product pages last.
The practical lesson, stated once and up front: you earn AI citations by being discussed off-domain, on Reddit, on YouTube, in editorial explainers and aggregators, not by publishing on your own product site. The biggest vendor-attributed source in this entire dataset is a blog (ZoomInfo's pipeline.zoominfo.com), and the two biggest sources overall are a community forum and a video platform.
One disclosure before the table: Amplemarket both published this leaderboard and appears in it. amplemarket.com is the most-cited actual-vendor domain (2,253). Read this as a measured, reproducible snapshot of what AI engines cite, not as an endorsement or a ranking of content quality.
The full methodology is below and every number is traceable.
The leaderboard: source domains AI engines cite most for sales-software questions
This is a ranking of source domains, the websites an engine returns as citations in its answer, not a ranking of tools or vendors. The data comes from AirOps, a third-party AI-search analytics platform that tracks which sources AI engines cite, measured across ChatGPT, Gemini, Google AI Mode, and Perplexity in the US over the 30 days ending June 18, 2026.
A note on the "Type" column: we simplified AirOps' own domain categories into a smaller, reader-friendly set of source types for readability, but the citation counts are AirOps' unaltered figures.
Source: AirOps, a third-party AI-search analytics platform. Category prompts across 22 topics, US, over the 30 days ending June 18, 2026.
The three findings that matter
- The top three sources are not vendors. Reddit (community, 4,620), pipeline.zoominfo.com (editorial blog, 2,819) and YouTube (video, 2,451) sit above every product page. AI engines reach for discussion and explanation first.
- The biggest "vendor" source is a blog, not a product. pipeline.zoominfo.com is ZoomInfo's editorial content operation, confirmed as an articles/case-studies/insights publication, not a pricing page, and it is cited 2,819 times. Content earns citations; product pages do not.
- Owned vendor domains rank, but only when they publish. The vendor domains that appear high, amplemarket.com, saleshandy.com, cognism.com, unifygtm.com, salesmotion.io, are the ones running real editorial libraries, not the ones with the biggest products.
Engine mix: where Amplemarket's own citations come from
A note on scope, because it is easy to misread: the engine breakdown available here is Amplemarket's own citations split by engine, not the whole leaderboard's citations by engine. It answers "where do our citations come from," not "which engine cites the most across every domain."
Read it as Amplemarket-specific.
Source: AirOps engine breakdown, US, May 19 to June 18, 2026. Counts are Amplemarket's own citations by engine and sum to 2,253. Each engine also has a citation rate, the share of that engine's answers that cite Amplemarket at all (Google AI Mode 35.5%, Gemini 30.1%, ChatGPT 12.9%, Perplexity 10.5%); those rates use different denominators and are not additive.
For Amplemarket, Google AI Mode and Gemini together drive roughly 77% of citations (1,724 of 2,253), more than 2.5 times the combined weight of ChatGPT and Perplexity. The buyer's instinct ("what does ChatGPT cite?") names the wrong engine: for this brand, most citations are won on Google's AI surfaces, which lean heavily on the same community, video, and editorial sources ranked above.
Optimizing only for ChatGPT leaves most of the citation opportunity unaddressed.
Implications: how to actually get cited by AI
Read the leaderboard backwards and it becomes a playbook. If AI cites community, video, and editorial content above product pages, then the way to get cited is to be present where the citations come from.
Concretely:
- Be discussed on Reddit (the #1 source). Real threads, "X vs Y," "anyone using...," honest complaints and recommendations, are the single most-cited source type. You cannot fake this, but you can earn it by being genuinely good and genuinely discussed. Monitoring and participating honestly in the subreddits where your category lives is now AEO work, not just community work.
- Publish on YouTube (the #3 source). Demos, walkthroughs, and review videos are cited heavily. Video is an under-built surface for most B2B sales vendors and it punches far above product pages.
- Run an editorial blog, not a product-page farm. The single biggest vendor-attributed source is a blog (pipeline.zoominfo.com). The vendor domains that rank, amplemarket.com, saleshandy.com, cognism.com, are the ones with real content libraries. Pricing and feature pages barely register as sources.
- Get into aggregators and "best-of" roundups. zapier.com (806) ranks as a source largely on the strength of its "best X tools" roundups and integration guides. Third-party listicles are cited; earning a spot in them is leverage.
- Optimize for Google's AI surfaces. For Amplemarket, roughly 77% of citations come from Google AI Mode and Gemini. AEO that ignores them is optimizing for the minority.
The uncomfortable summary: relative to the effort poured into it, your own product site is among the least-cited surfaces in this dataset. Citations are earned off-domain, in community, in video, in editorial, in aggregators.
Methodology
This leaderboard is built so a skeptic can rebuild it.
- Tool: AirOps, a third-party AI-search analytics platform that measures which sources AI engines cite in their answers.
- What's counted: a citation is a source link an engine returns in its answer. We rank source domains by raw citation count over the window. We do not score content quality, traffic, or rankings, only how often AI engines cite the domain as a source.
- Prompt set: category prompts spanning 22 topics (AI-SDR tools, cold-email deliverability, B2B data providers, sales engagement, buying-intent signals, and more). These are category questions ("which AI-SDR tools..."), not brand questions, so the source pool is competitive by construction.
- Engines: ChatGPT, Gemini, Google AI Mode, Perplexity.
- Geography: United States.
- Window: 30 days, May 19 to June 18, 2026.
- Type labels: we simplified AirOps' own domain categories into a smaller, reader-friendly set of source types; the groupings are ours, and the counts are unaltered.
- Verification: the domain figures were cross-checked against a live AirOps domain export on June 20, 2026; the ranking and the source-type pattern held. pipeline.zoominfo.com and saleshandy.com were independently confirmed as editorial/content publications (not pricing pages) on the same date.
Disclosure: Amplemarket built and published this leaderboard, and amplemarket.com is one of the ranked domains, the most-cited actual-vendor domain in the set.
The metric is mechanical (an engine returns your link, or it does not), and the inputs, topic count, engines, geography, window, and the analytics tool used, are all published so the result does not have to be taken on trust. This is a measured citation snapshot, not an endorsement, and not a ranking of content quality.
What this is and is not: General-purpose "top cited domains" leaderboards already exist publicly, and they consistently find Reddit, YouTube, and Wikipedia at the top across the entire web.
This piece is different in scope, not in spirit: it is a sales-software-category source leaderboard with vendor domains attributed, so a sales marketer can see exactly which of their peers' and competitors' domains are being cited, and that the biggest vendor source is a blog, not a product.
How this connects to our other data guides
For comparisons of the individual tools whose domains appear above, see our roundups: best AI SDR tools, best AI sales agents, and best sales intelligence platforms.
For a capability score across 231 features (a different dataset entirely), see the feature-bracket analysis.
For how AI-native search is changing prospecting itself, see find leads the way you think with AI search.
