If you ask an AI engine to recommend a marketing automation platform, which sources does it lean on to answer? In a small sample of 6 marketing automation queries run across Perplexity and ChatGPT, the engines produced 47 citations spread over 34 unique domains, and the single most cited source was techradar.com with 5 citations. No vendor owned the answer. This post breaks down that pattern and what it suggests for a martech vendor trying to get named.
I’m Andrii Byzov, a fractional CMO for B2B tech who runs AI search optimization for B2B SaaS. Marketing automation is a crowded, high-intent category, so it is a useful lens on how AI engines pick sources. The numbers below come from one narrow sample, so read them as directional, not precise.
Key takeaways
- Across 6 marketing automation queries, the engines gave 47 citations over 34 unique domains, a wide and fragmented spread.
- The top source was techradar.com with 5 citations, ahead of a tight cluster of domains tied at 2 each.
- That cluster mixed reviews, analysts, aggregators, and vendors: zapier.com, gartner.com, hubspot.com, activecampaign.com, brevo.com, customer.io, klaviyo.com, ortto.com, and salesforce.com.
- The pattern suggests AI engines blend independent and owned sources rather than trusting any one type.
- The honest read: earn presence across source types and improve your odds, because no single page wins the citation outright.
The top sources
The standout is a review and roundup publisher, not a vendor. TechRadar led with 5 of the 47 citations, more than double any other single domain in the sample. After it, the citation count flattens fast into a cluster of domains tied at 2 each. The drop from 5 to 2, and the long tail of single-citation domains that make up most of the 34, is the real signal here: citation share is fragmented.
Here are the most cited domains in the sample.
| Rank | Domain | Citations | Type |
|---|---|---|---|
| 1 | techradar.com | 5 | Review / roundup |
| 2 | zapier.com | 2 | Aggregator / comparison |
| 2 | gartner.com | 2 | Analyst |
| 2 | hubspot.com | 2 | Vendor |
| 2 | activecampaign.com | 2 | Vendor |
| 2 | brevo.com | 2 | Vendor |
| 2 | customer.io | 2 | Vendor |
| 2 | klaviyo.com | 2 | Vendor |
Several other domains, including ortto.com and salesforce.com, also sat at 2 citations, which underlines how flat the field is below the leader.
The pattern
Three things stand out. First, an independent review site outranks every vendor. That fits a wider habit in AI answers of leaning on third-party coverage when a buyer asks for a recommendation, because a roundup reads as comparison rather than pitch. Second, the citations are split across very different source types in roughly the same breath: a review publisher, an aggregator in zapier.com, an analyst in gartner.com, and a row of vendor sites. The engines are not picking one trusted lane and staying in it. Third, the spread is wide. With 47 citations landing on 34 domains, most sources are cited once, and even the runner-up cluster only gets to 2.
What it means for a martech vendor
If you sell a marketing automation platform, the data suggests your owned site is necessary but not sufficient. Vendor domains do appear, so a clear, answer-shaped product and comparison page still earns citations. But the leader was a review site, and analysts and aggregators sat right alongside the vendors. To raise your odds of being named, you likely need presence in the source types the engine actually pulls from, not just your own pages.
In practice that points to a few moves. Earn credible independent reviews and get included in the category roundups that publishers like TechRadar produce. Make sure your comparison and alternatives pages are clean, factual, and structured so an engine can lift an answer from them. Keep your entity data consistent so the model knows what you are and who you compete with. This is the everyday work of generative engine optimization, and it maps directly to the broader picture in my AI search visibility benchmark for B2B SaaS.
Because the field is so fragmented, share of citations is winnable in pieces rather than in one stroke. No single page dominates, so steady gains across reviews, analyst mentions, and your own answer-shaped content compound into a better chance of being the cited answer. For how to write pages engines will actually quote, see how to write content for AI search.
The honest caveat
This is one small sample: 6 queries, 47 citations, two engines. A different query set, a different week, or a different engine mix would shift the ranking, and the cluster tied at 2 citations is close enough that small changes could reorder it. So treat techradar.com leading and the vendor cluster behind it as a directional read of how AI sources marketing automation answers, not a fixed leaderboard. The direction is the useful part: AI blends reviews, analysts, aggregators, and vendors, and no one controls placement inside these systems. The work improves your odds of being the cited answer over time, which is the realistic promise of AI search optimization. If you want to talk through where your category sits, I’m on LinkedIn.
FAQ
Which sources does AI cite most for marketing automation platforms? In this sample of 47 citations across 6 queries on Perplexity and ChatGPT, techradar.com led with 5 citations, ahead of a cluster tied at 2 each that included zapier.com, gartner.com, hubspot.com, activecampaign.com, brevo.com, customer.io, klaviyo.com, ortto.com, and salesforce.com. It is a narrow sample, so read it as directional.
Do vendor websites get cited by AI for marketing automation queries? Yes, but they share the stage. Several vendor domains each earned citations, yet a single review site led the count, which suggests engines blend independent reviews with vendor and analyst pages.
How many domains did AI cite across these marketing automation queries? The 6 queries produced 47 citations over 34 unique domains, a wide spread with no dominant source. Citation share is fragmented, so a vendor competes against reviews, analysts, aggregators, and peers at once.
What should a martech vendor do about AI citations? Earn presence in the source types AI pulls from: independent reviews, analyst and comparison coverage, and answer-shaped owned pages with clean entity data. The goal is improved odds of being cited, not a guarantee.