AI Visibility
I Looked at Every URL Perplexity Cited for 6 Buying Questions. 14 of 23 Belonged to a Vendor.
A small, honest teardown of 23 URLs Perplexity cited across six buyer questions in our own database. Most of them were vendors' own marketing pages. One was a Reddit thread.
Our own database has been storing the URLs that AI engines cite since June. Every visibility check writes them to a sources column, and until recently nothing read that column. When I finally went looking, I found 236 stored URLs, and then spent an afternoon working out that most of them were worthless.
Here is the part I'd rather not publish. Of those 236 URLs, 213 came from checks we'd labelled chatgpt, which ran through a model with no web grounding. We pull URLs out of the answer text with a regex. For a grounded engine that gives you real citations. For an ungrounded model it gives you URLs the model remembered from training, which is why those rows are full of bare homepages: later.com, hootsuite.com, ads.reddit.com. They aren't citations. They're recall.
That leaves 23 URLs from grounded Perplexity checks, spread across 6 questions and 2 products, collected between 17 June and 9 July 2026. It's a tiny sample. I decided to write it up anyway, because the shape of it contradicted what I expected and I'd rather publish 23 real citations than 200 fake ones.
The counts
I ran the 23 URLs through our own classifier, the same code that labels sources in the product:
| Type | Count |
|---|---|
| Article (blog post, feature page, guide) | 15 |
| Listicle ("best X", "tools for Y") | 7 |
| Community thread | 1 |
| Review site (G2, Capterra, Wikipedia) | 0 |
| Comparison page ("X vs Y") | 0 |
Then I went through them by hand, because the classifier answers "what shape is this page" and the question I actually cared about was "who owns it". Fourteen of the 23 were on the domain of a company selling a tool in the category the question asked about. Not a journalist writing about the category. The vendors themselves, describing themselves, quoted back to the buyer as an answer.
Four were written by someone who wasn't selling anything: a Reddit thread, an Indie Hackers thread, a Medium post by an indie developer, and a LinkedIn article. The rest were blogs belonging to companies adjacent to the question, like Ahrefs and Semrush writing about brand monitoring, or Mercury writing about marketing tools for startups.
The full list
For "How do I monitor when AI assistants cite my competitors but not me?":
ahrefs.com/blog/brand-mentions/radarkit.ai/blog/monitor-competitor-mentions-in-ai-search/turboaudit.ai/ai-monitoringreddit.com/r/ProductMarketing/comments/1k10tlt/top_5_tools_to_monitor_your_brands_presence_in_ai/semrush.com/blog/ai-visibility-toolkit/
For "How do I monitor Reddit for high-intent buyer conversations in my niche?":
catchintent.com/blog/how-to-find-buyer-intent-signals-reddit/catchintent.com/social-listening/catchintent.com/tools/reddit-intent-analyzer/linkeddit.com/blog/reddit-buying-intent-signals-guiderelato.com/blog/reddit-monitor-agent/
For "What's the best tool for finding potential customers on Reddit who are actively looking to buy?":
linkeddit.comlinkeddit.com/blog/how-to-find-customers-on-redditogtool.comreplyagent.ai
For "Best tools for indie hackers to find paying customers through Reddit marketing?":
medium.com/@faustoct1/side-tools-how-indie-hackers-promote-their-products-for-free-indefinitely-ebd64f0cf3b8redditgrow.ai/blog/best-reddit-tool-indie-hackers-2026indiehackers.com/post/as-a-solo-indie-maker-what-are-your-go-to-tools-for-building-and-growing-your-product-380ee3dffbreddit-radar-marketing.com/use-cases/indie-hackers
For "digital marketing for startups":
bolsterbiz.com/blog/10-best-digital-marketing-strategies-for-startups/mercury.com/blog/best-marketing-automation-tools-startupsstartup.google.com/products/linkedin.com/pulse/best-free-marketing-tools-startups-diginext-info-xybscusekaya.com/blog/budget-friendly-marketing-tools-for-startups
Notice the third question. Three of its four citations are a competitor's homepage or a page one click from it. linkeddit.com and ogtool.com and replyagent.ai are small tools with the kind of domain authority that wouldn't get them onto page one of Google for that query. The engine cited them anyway.
What I think this means, with the caveat that it's 23 URLs
The advice I keep reading is that AI visibility comes from being on the big third-party properties: get on G2, get into the listicles, get mentioned on Reddit. In this sample the big properties were absent. No G2. No Capterra. No Wikipedia. No product comparison pages. One Reddit thread out of 23.
What the engine reached for instead was whichever page most directly answered the question, and a lot of the time that page belonged to a small vendor who'd bothered to write it. catchintent.com got cited three times for one question, on three different pages of their own site. That is a company that wrote about buyer intent signals on Reddit and got quoted for it.
If that holds up at larger sample sizes, the first move for a small product isn't outreach. It's writing the page. Which is convenient for me to conclude, so treat it with the suspicion it deserves.
The Reddit finding is the one I keep chewing on. We spent a year building around the idea that Reddit threads are what AI engines quote when buyers ask for tools. One citation out of 23 is not that. It's not zero either, and the one that appeared was a thread titled "Top 5 tools to monitor your brand's presence in AI", which is a listicle that happens to live on Reddit.
Two things this exercise broke
The classifier put the Indie Hackers thread in the listicle bucket. Its URL contains tools-for, which matches a listicle hint, and indiehackers.com isn't in our list of community hosts. So a community thread got labelled as a ranked article. Both are now fixed in our backlog.
The bigger one is that we were storing ungrounded model output in the same table as real citations, with no column saying which was which. Anyone reading that table, including me, would have drawn conclusions from 213 hallucinated URLs. The sources column now only means something when the engine was grounded, and we should have written that down when we built it.
If you want the same read on your own category, our visibility checker runs the questions and shows you what got cited. The methodology page covers how we ask, what we extract, and what the method can't see, including this exact limitation.
I'd like to redo this with 50 questions across categories I'm not selling into. When I do, I'll publish the numbers whether or not they agree with this post.
Frequently asked questions
What sources does Perplexity cite for software buying questions?
In our sample of 23 cited URLs across six buying questions, 14 were pages on a vendor's own domain (their homepage, their blog, or a product page), 7 were ranked list articles, and only one was a Reddit thread. No G2, Capterra, or Wikipedia pages appeared at all. That is a small sample from one engine and should be read as a data point, not a rule.
Is it worth writing your own pages if AI engines cite vendor sites?
In this sample, yes, more than we expected. Half the cited vendor pages were plain blog posts or feature pages on small tools with no real domain authority. If the engine is willing to quote a small vendor's own page, publishing the page that answers a buying question directly is a cheaper first move than trying to get onto a review site.
How many questions do I need to track to know what AI cites about my category?
More than six. Six questions gave us a directional read and not much else. Somewhere between 30 and 50 questions per category, checked repeatedly over time, is where the counts stop swinging on a single answer.
Does Perplexity cite Reddit for buying questions?
It did once in 23 citations here, on a question specifically about monitoring brand presence in AI tools. Reddit shows up in AI answers, but in this sample it was a minority source rather than the dominant one that a lot of GEO advice assumes.
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