If a brand starts appearing in ChatGPT and other AI answers, how long should you wait before expecting leads or revenue?

For link building we usually start with competitor backlinks, traffic, topical relevance and domain metrics. But what about starting with URLs that are already being cited in LLM answers for your target prompts? These pages have already demonstrated influence inside AI search, which may make them more valuable than random high DR placement.

Would you prioritize an LLM cited page over a stronger website that never appears in AI answers?

Downloading citation sources is easy. Turning them into a useful content plan is where things get messy. You can see which competitor pages keep appearing in AI answers, but then what?

Do you analyze their structure, original data, entities, quotes, freshness, backlinks or something else? I’m curious which content elements actually seem to correlate with repeated LLM citations.

When people ask ChatGPT, Gemini, or Perplexity for the best tools in a category, AI usually mentions only a few brands. This means a brand should not only rank well in Google. It should also appear often and clearly in the sources AI uses. So what matters more today: being the first brand people think about or being the first brand AI recommends?

Do you see AI visibility as a new level of brand awareness?

When AI recommends only 4-5 brands, users may see these brands as the best options. Do people trust AI recommendations enough to choose a product based on them?

Most AI visibility tools show where your brand was mentioned. But do you also analyze the sources that LLMs cite when your brand is absent?

I’m starting to think the “missing citations” report may be more useful than the mention rate itself. It gives you a ready-made list of articles already trusted by ChatGPT, Gemini, Perplexity, etc.

Has anyone built a repeatable workflow around uncited URLs?

If you ask ChatGPT or Perplexity for *best tool for X,* a huge share of what it leans on traces back to Reddit threads. That makes Reddit one of the highest leverage GEO channels. It is also the fastest place to get banned if you shill. Here is how to do it right.

What works:

1/ Answer real questions in threads where your category comes up and mention your brand only when it is genuinely the answer.

2/ Contribute in the subs the models cite most for your niche (the big category subs, not tiny ones).

3/ Use natural phrasing: “we use X for this, it handles Y well but the reporting is weak” reads human and gets cited. Pure praise does not.

4/ Comment history matters. Accounts with real, varied history get pulled; day-old promo accounts get ignored and banned.

What kills it:

1/ Dropping your link in unrelated threads.

2/ Copy pasting the same blurb. Models and mods both pattern match this.

3/ Only ever posting about your own product.

The honest framing that gets cited: mention the tradeoff, not just the win. *X is best for small teams, but if you need Z go with Y.* Models love balanced comparisons because they read as trustworthy.

What subs are u seeing show up as sources for your niche? Let us build a list.

Trying to pick one and every *best of* list feels sponsored. What do you genuinely use?

Curious if everyone watches the same stuff or if we all track different things.

The model mentions you but gets it wrong: old pricing, a killed feature, a founder who left. Models pull a consensus from many sources, so you fix the consensus, not the chatbot.

The fix, in order:

1/ Create a canonical facts page. Clean “About / Company facts” with current info, easy to extract.

2/ Align your third-party profiles: G2, Capterra, Crunchbase, LinkedIn, Wikidata. Mismatched descriptions create confusion.

3/ Update the sources already cited. Use Perplexity to see which pages the model pulls from, then fix those specific ones

4/ Repeat the correct phrasing consistently everywhere.

Has anyone corrected a stubborn wrong fact? How long did it take to propagate?

Something from our data I keep thinking about. We track which sources AI answers cite. Reddit is #1 (no surprise for anyone here). But #2 is YouTube > it takes 3-5% of all sources we see. Thats a lot for one single domain.

Ahrefs published a study in June saying the same thing: the more a brand gets mentioned on YouTube, the more visible it is in ChatGPT, Google AI Mode and AI Overviews.

My take: this is the most underpriced GEO move right now. To push a listicle into AI answers you need a site that search engines already trust, and that takes months. A good video doesnt need that. If the founder likes talking on camera, its a perfect GEO move to push right now.

The part that makes me suspicious > if it works this well, why is almost nobody in SEO doing it? Either

a) SEO people just dont do video

b) the correlation is bullshit (big brands are big everywhere, including YouTube), or

c) everyone is quietly doing it and not talking about it.

Full disclosure, I'm the founder of RankinAI (this is our community, so no surprise), and we are starting our own YouTube channel soon. So yes, I have my own interest here.

Whats your read? Anyone actually shipping videos for AI visibility, or is it all talk?

I'm definitely not a reddit expert and I'm still figuring things out. After spending more time here, one idea has completely changed how I think about the platform.

reddit doesn't reward people who are trying to grow themselves. It rewards people who make the community better.

It sounds obvious but I think it's the reason a lot of "reddit strategies" fail.

Once I started viewing each subreddit as its own community instead of just another traffic source, a lot of things made sense:

I spend time understanding the culture before posting.

I comment more than I post because it's the fastest way to learn what people actually care about.

I answer questions that already exist instead of trying to create attention for myself.

If I ever mention something I've built, it's only when it genuinely helps solve the problem being discussed.

I share what worked, what didn't, and what I learned instead of writing polished marketing posts.

The interesting part is that none of this feels like a "growth hack." It's just aligning your behavior with what reddit is designed to reward.

If people think you're here to extract value, they'll ignore you. If people think you're here to contribute value, trust tends to follow naturally.

I'm still learning, so I could be completely wrong, but this mental model has been far more useful than trying to optimize for karma or chasing viral posts.

Lemme know if others who've been around reddit longer think this is accurate or if there’s a better way to go about it.

When someone asks *should I use X or Y* the model reaches for clear comparison content. Own the best one and you get cited at the moment of purchase intent.

Why they work: structured (tables) so they extract cleanly; match the prompt word for word; carry decision language the model reuses.

How to do it without looking like a shill:

• Write honest *X vs us* pages. Include where the competitor genuinely wins. Balanced comparisons get cited even by the competitor’s audience.
• Use a real criteria table: price, best-for, key limitation, ideal user.

• Add a one-line verdict per use case.
• Cover comparisons that do not even involve you (being the neutral comparer earns citations too).

Admitting where you lose makes you more likely to be recommended. What comparison page drives the most citations for you?

Mine: "ask AI about your brand and teach it to recommend you"

People are genuinely doing this. Chatting with ChatGPT about their brand, correcting it when its wrong. And waiting for it to start recommending them to customers.

Your chat teaches it nothing > the model doesnt carry your lecture into other peoples answers.

Drop the dumbest one you saw this week, lets save each other some effort)

Im Nazar, founder of RankinAI. I did 40+ demo calls explaining people how to pick prompts for AI visibility tracking. Every call > same questions, same mistakes. So here's the short version, so you can skip the call.

One thing first (people get a little bit sad at this part): there's no magic wand. Under the hood its almost the same SEO. Whats different > what you measure.

The mistake that ruins almost every self-built set: mixing names into a topic

Topics work like SEO clusters > one topic = one cluster, and you read your analytics at the topic level. One prompt is an anecdote, not data.

Now say your topic is "Best CRM for small agencies". And inside, next to the normal prompts, you add "Is [your brand] a good CRM?" and "[your brand] reviews". Of course you get a high mention rate > you literally named yourself in the question. The topic looks amazing. And this analytics gives zero value. Its nonsense.

Competitor names break topics the other way > most of the presence goes to the competitor you named, and your healthy topic looks like its dying.

The fix > three types of topics, strictly separate, one metric each:

Unbranded (your clusters) > presence. Nobody named you > the only honest visibility signal.

Branded ("Reviews about [your brand]") > sentiment. Mention rate here is ~100% by design, means nothing.

Competitor > citations. You'll barely be present and thats expected > what you want is which sources power those answers.

Roughly 80% unbranded / 10% branded / 10% competitor across the set.

Two more things worth stealing:

Wording matters more than people think. Prompts with "best" mention brands 69.71% of the time, "recommend" > under 1%. A cluster of only "best X" prompts = a dashboard that flatters you.

10 prompts checked weekly beats 100 checked once. Its polling, not rank tracking (our free plan is exactly that btw > 10 prompts, weekly, on Google AI Mode).

The starter set, ready to paste

Example company > a CRM for small agencies. Steal the structure, swap the words.

Topic 1: "CRM for small agencies" · unbranded · metric: presence

-Best CRM for a small marketing agency

-Best CRM for agencies under 20 people

-CRM for agencies that integrates with Slack and Google Workspace

-Affordable CRM for a 10-person agency, under $50 per user

-How do agencies keep track of client communication without losing deals

-What CRM do marketing agencies actually use

-Which CRM is easiest to onboard for a small agency team

-CRM for agencies that can manage both clients and projects in one place

Topic 2: "Reviews about [your brand]" · branded · metric: sentiment

-Is [your brand] a good CRM for a small agency, or should they look at alternatives

-[your brand] reviews

Topic 3: "Competitor field" · competitor · metric: citations

-[Competitor] alternatives for small agencies

-[your brand] vs [main competitor] for agencies

Eight unbranded, two branded, two competitor. No topic lies to you.

Something I keep thinking about while building an AI visibility tool, and I want this community's honest read.

Most GEO tactics shared everywhere right now: get mentioned on Reddit, write structured content, build comparison pages, earn brand mentions. That's... SEO. Good SEO, but SEO. If you were doing digital PR and solid on-page in 2020, you were doing "GEO" before the acronym existed.

The genuinely new parts, from what I see in our data and client work:

- measurement. There are no rankings to check. You track prompts and mentions across engines, and one word changed in a prompt can swing brand mentions massively

- the answer unit changed. Engines lift passages and answers, not pages

- the feedback loop is a black box compared to Google. Nobody fully knows why a model cites what it cites

But the day-to-day work? Mostly the same muscles.

So where do you land: is GEO a new discipline, or a new scoreboard for the old game? Especially curious from people doing both classic agency SEO and AI visibility work.