My client's site started getting cited in AI after 2 weeks (just from Reddit)
When Ticket Tailor came on as a client, I was still half convinced this whole thing might not work.
I was telling people I could get their brand mentioned when someone asks ChatGPT for a recommendation, and most of them looked at me like I was selling magic beans. Ticket Tailor took the bet anyway, which I still appreciate, because they turned out to be one of the clients that proved the model actually held up.
The situation was almost annoying, because the product was good. Ticket Tailor is a genuinely fair ticketing platform, none of the Eventbrite fee gouging. But if you opened ChatGPT and asked "what's a good Eventbrite alternative," it wasn't there. And that question, or some version of it, is exactly how people were starting to shop. Nobody was opening ten tabs to compare anymore. They asked an AI, got three names, and picked from those. Ticket Tailor just wasn't in the three.
So I went looking for where the answer actually comes from. And over and over it came back to Reddit. You ask an AI to recommend a tool and, if you look under the hood, there's usually a Reddit thread doing most of the talking. That was the door.
The work after that was slow and unglamorous. I spent time inside the communities where event organizers actually complain, the small event subs, the nonprofit folks running fundraisers, people quietly furious about ticketing fees eating their margins. And every time, one rule: Ticket Tailor only got mentioned where it was an honest answer to what someone was already asking.
Then about two weeks in, I got an email I wasn't expecting. It was the client, thanking me, telling me they'd just seen a huge jump in traffic coming from AI. They noticed it on their own analytics first and reached out. That's when it stopped feeling like a theory to me. The AI referral line had visibly moved, in two weeks, off Reddit work.
I typed "best Eventbrite alternative" into ChatGPT myself right after to see it, and there it was in the answer. First time. I actually sat there for a second.
Here's the thing though. That whole process was me doing it by hand, tracking everything in my head and a mess of spreadsheets. So after a few clients I turned the messy version into a real product. That's AEORank.
AEORank is the whole loop in one place. It tracks the exact prompts your buyers ask, shows whether you or a competitor owns each answer, tracks those competitors head to head, audits where you're weak, surfaces the specific threads and sources feeding the answers you're losing, turns all of it into a task list, and reports the movement over time.
This is also where the part everyone gets burned by gets handled. Reddit is brutal. Fresh accounts get shadowbanned, links get stripped, comments vanish overnight, and half the DIY attempts I see die there. We don't post from throwaways. It's aged accounts with real history and karma, each with its own persona, never cross-commenting each other, and the brand only ever goes where it genuinely fits the thread. That combination is why the comments actually survive and keep getting cited, instead of getting nuked a day later and taking your citation down with them. You never touch an account, a proxy, or a ban.
Discovery, tracking, competitor view, audit, reporting, execution, and accounts that don't get deleted. One thing instead of five.
The takeaway I keep coming back to is simple. The brands landing in these threads right now are quietly becoming tomorrow's default answer. Everyone else is going to wake up invisible, not because their product is worse, but because no model ever learned to say their name.
Great share. It's a good reminder that being part of relevant conversations can matter as much as traditional SEO now.
I help busy founders clear their operational backlog by handling repetitive, time-consuming tasks they don't have time for.
From CRM cleanup and spreadsheet organization to lead research, documentation, and data management—I take care of the work that keeps getting pushed aside.
You stay focused on building your business while I handle the rest.
Amazing! Congrats.
I'm aware that Reddit is used widely in foundation model training, but using that to do AEO is so obvious that I'd be concerned this will no longer work as a marketing channel. That's my main concern - plus the issue of ensuring you're really adding value at the same time and not just spamming Reddit.
Any thoughts on that?
The two-week turnaround is the part I'd want to poke at, because that's faster than I'd have guessed.
I run a scanner that reads Reddit for buying-intent threads and I pulled 30 days of it last week: 147 threads, 78 subreddits, 8 products. One thing in there might complicate the picture. The threads with the strongest buying intent were consistently the quiet ones. High intent (60+ on our scoring) averaged 12 upvotes. Low intent averaged 57. Roughly a 5x gap, in the opposite direction from what you'd assume.
Which makes me wonder whether the threads that feed AI citations and the threads where someone is actually deciding are even the same threads. A 400-upvote "best Eventbrite alternative" megathread is a great citation source and a terrible sales conversation. The 6-upvote one where a nonprofit is asking about fee structures is the reverse. Both matter, but you'd work them completely differently.
Did the AI referral traffic convert, or just show up? That's the number I'd want.
(On accounts surviving - I automated the reading, then got greedy and tried automating some of the replying, and got shadowbanned promoting a Reddit tool on Reddit. Learned that one the expensive way.)
The upvote inversion matches what I keep seeing. The thread that teaches a model your name and the thread where someone is about to buy are usually not the same thread, and one blended number will read as progress either way.
The harder part is the question you ended on. A citation appearing is easy to measure. Whether it moved anything is not, because the baseline drifts on its own and two weeks is short enough that ordinary variation can look like a result. Without a before and after on the same set of questions, a jump you caused and a jump that would have happened anyway look identical.
Curious whether the 5x gap holds across verticals, or whether it is specific to the eight products in that pull.
Yeah, you're right and I don't have a clean answer to it. What I reported is a citation showing up, not one I can prove I caused. There's no frozen question set with a real baseline behind it, so a two-week jump and normal drift look the same from where I'm sitting. If I'm honest the "two weeks" is the softest part of the whole thing.
The version I'd actually trust: pick 30-40 questions before touching anything, run them weekly for a month to see how much they wobble on their own, then start posting and keep running the same list. Without that do-nothing month up front I'm mostly reading tea leaves.
On whether the 5x holds across verticals, I wouldn't bet on it. It's 8 products, and a couple of them had big "best X alternative" megathreads sitting in the low-intent bucket dragging the average up, so the mean is carrying a lot of weight. Pull the median instead and the gap probably shrinks. I'd want a few hundred threads across more categories before calling it a pattern and not just what my eight happen to look like.
The part I'm more confident about is the split you named. The thread that teaches a model my client's name and the thread where someone's picking a tool this week are usually different threads, and if you track one blended number you can't tell which one moved. That's what I'm trying to build around now.
The do-nothing month is the part most people skip, and it is the only thing that makes the after-number mean anything. Without it you are reading drift as impact.
On the median, agreed, and it is worth splitting the pull by whether the thread was a roundup or someone describing their own situation. A megathread and a 6-upvote question are not the same unit, so averaging them averages two populations.
The wobble is data too. If a question's answer changes week to week with nobody touching it, that is a question you cannot use as a measurement anchor at all.
I help busy founders clear their operational backlog by handling repetitive, time-consuming tasks they don't have time for.
From CRM cleanup and spreadsheet organization to lead research, documentation, and data management—I take care of the work that keeps getting pushed aside.
You stay focused on building your business while I handle the rest.
This tracks with something that just happened to us today, live. Posted a genuinely helpful, non-promotional reply to a real question in r/SEO from an account that existed but had basically zero history — auto-removed within minutes, "low CQS score," invisible to the actual thread. Content had nothing to do with it. The account had no standing, full stop.
What you're describing is the fix, not a hack: aged accounts, real karma, a persona that's consistent enough to be trusted rather than flagged. That's a genuinely different cost structure than "post good comments and hope" — it's infrastructure, not copywriting.
One thing I'd be curious about: how do you handle the tension between "aged account with real history" and "brand only ever goes where it genuinely fits the thread"? Feels like the second constraint is what keeps the first from decaying into karma-farming, but it also caps how fast you can scale accounts vs. how fast you find matching threads.
Interesting seeing Reddit become the bridge between search and AI answers. The hard part is not posting more, it’s finding real conversations where the product actually fits.
Really useful writeup, and the "only answer where it is genuinely the answer" rule is the part I would underline too.
One technical thing I ran into last week that fits right under this: even after the mentions exist, the AI crawlers have to be able to read your own site, and mine quietly could not. My robots.txt was inviting them in, but a bot-management rule at my CDN was returning 403 to the actual AI user agents. I only caught it by requesting my pages as those exact bots: a made-up bot name got 200 while the real AI ones were blocked, which is how I knew it was targeting them specifically. On top of that my localized content was injected with JS, so the crawler saw the wrong language entirely.
So before investing in the mention layer, it is worth fetching your own pages as the AI bots and confirming they get real, readable HTML back. Otherwise the citation you worked for lands on an empty shell. Curious whether you check crawlability as part of the AEORank audit.
Using aged accounts with separate personas is the part that makes me hesitate, because it can cross from useful participation into coordinated astroturfing very quickly. A more defensible moat would be helping clients earn genuine mentions from independent customers and communities, even if that is slower and harder to scale.
the "honest answer to a real question" constraint is doing all the heavy lifting here. most people trying to game AI citations skip that part entirely and wonder why their posts get nuked. the uncomfortable truth is that this only works if the product is actually good enough that recommending it is genuinely helpful — which filters out like 90% of the people who'll try to copy this playbook
Really cool to see this play out with actual data, the "honest answer to a real question" caveat is the part I'd bookmark, feels like the whole thing hinges on that.
We've been doing something similar with our own Reddit presence for trimy.io, just genuinely answering questions in smaller communities without pitching anything, and it's slow the way you describe, no shortcuts, just showing up. Good to hear it can actually move the needle on AI citations too, that's a nice bonus on top of the community goodwill.
Appreciate you sharing the real mechanics instead of just the headline result, this is the kind of post that's actually useful to bookmark. Good luck with AEORank!
The part I’d be careful with is measuring “cited in AI” separately from buyer intent. I’d split the prompts into three buckets: job-to-be-done searches, competitor/alternative searches, and curiosity/research searches. The competitor/alternative bucket is usually the one that tells you whether this is moving actual purchase behavior, not just creating a nice screenshot.
The "fresh accounts get nuked" part is painfully real — I had two posts removed by Reddit's filters just this week (new account + new domain link = instant spam signature, apparently the account age matters more than the content).
The observation about AI answers being sourced from Reddit threads matches what I see too, and it's a genuinely important shift. Where I'd push back a little: managed personas that "never cross-comment each other" is the part that would keep me up at night as a client. When coordinated networks get caught, Reddit tends to ban the brands they promoted, not just the accounts — at which point every citation you built becomes a liability. The slow version (real account, real name, only answering where you'd answer anyway) seems like the only one that compounds without that tail risk.
Curious how you think about that risk for clients — is there a disclosure line you won't cross?
My team is interested in using Reddit more aggressively, may try using this. Do you offer a discount for startups?
Spot on about Reddit being brutal. The moment a throwaway account drops a product link, it gets shadowbanned instantly, and LLM scrapers ignore low-karma spam threads anyway. Participating naturally where people are actually asking for alternatives is literally the only way to build citations that survive. AEORank looks like a really clean way to map out where those conversations are happening without doing it all in messy spreadsheets.
I signed up but the pricing put me off. I would suggest to have a free trial and keep the charges for comments and posts. Also, your biggest clients would be agencies like mine but $199 per website can be expensive.
Also, maybe the AI can pull the product/service description from the website itself for less friction?
Reddit showing up that fast tracks with what we've seen. We've been
building links for a pre-launch product and the pattern that surprised
us: platforms where you publish content into someone else's template
almost always wrap your links in nofollow, but platforms where you
control the raw HTML don't. Same tier of domain, completely different
outcome.
Curious whether the AI citation is coming from the Reddit thread itself
ranking, or from the client's own pages getting picked up as a result.
Those need pretty different follow-up strategies.
yeah reddit platform is really getting soo much views and users i also facing same thing when i post about my product first sale 2 more sale i got from reddit and i literally shocked when i see it get me soo much motivated to continue build and shipped new products
If you're looking for API-level access to track where AI engines cite your brand, there's actually a dedicated endpoint for this now at API Serpent's AI Rank API — it queries ChatGPT, Claude, Gemini, and Perplexity in a single call and returns a normalized citation score + source URLs.
The use case is exactly what you're describing: brand monitoring across LLMs, not just traditional search.
Hey, great story!
I'm also building an AI SEO tool right now and seeing how much Reddit influences AI answers. Quick question — how did you find those specific small communities (like event subs) to start posting in?
Good luck with AEORank!
the gap between "posting about your product" and "being the person who knows the answer" is everything on Reddit
Useful case study. The distinction I would make is between citation sources and buyer-intent sources.
A broad Reddit thread can teach an AI model that a product belongs in a category answer, but the quiet thread with a very specific workflow pain is often where the buyer is actually deciding. Those need different work: one is about being named accurately, the other is about reducing risk for a person with a job to finish.
For infra/payment/SaaS products, I think the landing page has to support both. It should expose concrete facts that can be cited: who it is for, who it is not for, pricing/fees, integration path, failure modes, security/reliability details, and comparison boundaries. Otherwise Reddit mentions may create visibility, but the model and the buyer still lack enough evidence to recommend or trust it.
The best signal would be: same prompt set before/after, citation movement, and then whether visits from those answers reached activation or conversion.
Interesting results. It's always valuable to see real data instead of assumptions. Thanks for sharing your experience.
This is a fascinating approach. The Reddit → AI citation loop makes total sense — I've been noticing the same pattern with my own product.
One thing I'd add: the "aged accounts with real history" point is crucial. I tried posting from a fresh account and got shadowbanned within days. The organic, genuine contribution approach is the only thing that actually survives long-term.
Curious — how do you handle niches where the Reddit communities are very small or highly moderated? That's the challenge I'm running into with content creators.
The way I see it is that AEO / AIO / GEO (whatever acronym you choose to call it) is all about amplifying the white hat tactics of SEO and ignoring the "hacks." Sure, FAQ schema can help (LLMs love structured content) but it's all about that EEAT at the end of the day.
And Reddit is definitely top tier when it comes to getting cited by AI answers...but you're right, it's a slow burn. I'm still dragging my heels on starting my Reddit engagement plan because I'm used to being a lurker, lol.
I am still waiting no response from any platform
There's a technical layer under this thread that nobody mentioned: even when the Reddit mentions exist, your own site has to be readable by the crawlers that follow them. Mine wasn't - JS-only SPA, so the AI bots saw an empty shell where all the landing copy should be. I only found out because I fetched my own pages the way their bots do. Prerendering fixed it. Worth checking before investing in the mention layer, otherwise the citations have nothing solid to land on.
On the persona debate in the comments: I'm doing the DIY version for my own product - one account, my real history, disclosure when I mention my own tool, and most comments with no product in them at all. Slower, but nothing to purge, and the discipline of "only answer where you'd answer anyway" keeps teaching me things about the product - the threads tell you what people actually can't do.
And the upvote inversion described above matches my (much smaller) experience: the quiet thread where someone describes their exact workflow pain is where a recommendation lands. The megathreads feed the models; the small ones feed the funnel. Different jobs, both worth doing.
There's a technical layer under this thread that nobody mentioned: even when the Reddit mentions exist, your own site has to be readable by the crawlers that follow them. Mine wasn't - JS-only SPA, so the AI bots saw an empty shell where all the landing copy should be. I only found out because I fetched my own pages the way their bots do. Prerendering fixed it. Worth checking before investing in the mention layer, otherwise the citations have nothing solid to land on.
On the persona debate in the comments: I'm doing the DIY version for my own product - one account, my real history, disclosure when I mention my own tool, and most comments with no product in them at all. Slower, but nothing to purge, and the discipline of "only answer where you'd answer anyway" keeps teaching me things about the product - the threads tell you what people actually can't do.
And the upvote inversion Telman describes matches my (much smaller) experience: the quiet thread where someone describes their exact workflow pain is where a recommendation lands. The megathreads feed the models; the small ones feed the funnel. Different jobs, both worth doing.
Hello, I’m a software engineer interested in building AI-powered SaaS products. I’m here to learn from other founders and developers, exchange ideas, and connect with people working on interesting projects. Nice to meet you!
Wow Thank You. This is refreshing.
This matches what I just learned the hard way. Product Hunt and LinkedIn sent zero users to my Chrome extension, while the useful conversations started with one specific workflow pain. The distinction in the comments between citation traffic and buying intent feels important. Did the client see signups or paid conversions from the AI traffic, or only visits? That would show whether Reddit created awareness or actual demand.
The two-week signal is real, but the aged-persona-account approach is the part that eventually breaks: platforms get better at detecting it, and one purge takes your citations down with it. I watched the same dynamic in the Microsoft partner channel for 20 years, whoever owns the trusted recommendation layer owns demand. The durable play is making your actual customers loud in those threads, not renting personas to do it.
That's cool, my issue is that all of my posts from reddit get auto-removed
This is a clean case study. The “product was good, AI just never said the name” part is the scary bit, because that used to be an SEO problem and now it’s a recommendation problem.
Reddit as the source layer makes sense too. Models remix what’s already trusted in the wild, so if you’re invisible in those threads you’re invisible in the answer. Turning the spreadsheet chaos into AEORank is the classic IH move, feel the pain by hand, then productize the loop.
I’m in a neighboring lane with Make it RAIN. Less “does ChatGPT recommend you,” more “once a builder has something shipped, how do they get buyers, pricing, and a 30-day path without drowning in tabs.” Built it after doing that mess myself: https://ReliableAINetwork.com
Testing whether links still get stripped on my account, so if this URL vanishes I’ll know I’m still gated. Either way, strong writeup. Two weeks to a visible AI referral jump is a hell of a proof point.
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Looking for 5–10 design partners to shape it.
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#BuildInPublic #SaaS #DevOps #Stacck
Cool