Reddit and YouTube for AI Visibility: What You Can Do

Reddit's robots.txt has two directives. Both say no, to everyone. That is one of the two names Chapter 8 ended on.

Neither of these is a channel

Chapter 8 ended on two names. YouTube mentions topped the largest correlation table at 0.737. Reddit discussion was the strongest predictor on the one engine where anything predicted. Two names, both handed here.

It also said neither is a placement you buy, and handed the question here. So here is the answer, and it is not a posting strategy.

These two platforms are structurally different from each other, and both are different from the open web. One reaches engines through commercial contracts that can be canceled. The other lets anyone watch and almost nobody read.

Neither is a surface you optimize. Both behave like infrastructure somebody owns. So what do you do?

Which changes what you should do, and mostly it means doing less of what you were sold.

Reddit is not a channel. It is a contract.

Start with the file every crawler reads first.

Eight lines, and five are comments. The two directives have no exceptions, no named agents, no allow list.

The comments point at two other doors: the Public Content Policy, and a subreddit for non-commercial research.

Both doors lead to one room. Have you read either?

The Public Content Policy says it in one line: you may use Reddit content for non-commercial uses, "but talk to us if you have commercial purposes in mind."

The unauthenticated JSON endpoint that used to serve any subreddit as structured data returns a 403 now. The Data API terms close the last door explicitly.

Their section 2.4 grants no rights to use content "for other purposes, such as for training a machine learning or AI model, without the express permission of rightsholders."

No ambiguity there.

Section 3.2 repeats it as a prohibition rather than an omission. So how does any Reddit content reach an engine?

By contract. A small number of them.

Now price the whole arrangement, because it is smaller than the discourse suggests.

Reddit's Other revenue line is mostly data licensing. It ran at 43 million dollars in the second quarter of 2026. Against 762 million in advertising.

Roughly 5% of revenue: split across every licensee.

The largest of those contracts may be ending. The Google deal is reported at 60 million a year. In July 2026 Reddit was reported to be weighing whether to renew. Internally. Quietly.

The stock fell 9% that day. Which tells you how the market reads that channel.

So hold the whole picture. Reddit blocks every crawler. It forbids training through its API. It licenses to a handful of buyers, for about a twentieth of its revenue. That is the whole arrangement.

Is that a surface you optimize? No. It is a pipe two companies negotiate over. Either can hang up. We would not build on that.

Which is the first thing this chapter tells you not to build on.

Reddit is defending that pipe in court, which tells you how it sees the asset.

In October 2025 it sued Perplexity and three data-scraping companies. The complaint is worth reading for its method, not its law. The method is a trap.

Reddit says it planted a test post visible only to Google's crawler. A marked bill.

Their words: "Within hours, queries to Perplexity's answer engine produced the contents of that test post."

The claims are not copyright infringement. Three counts sit under the DMCA's anti-circumvention provisions, and three are state-law claims.

Then the ruling, on 31 July 2026, and it matters beyond this case.

The court let the core circumvention claims proceed. It held that a bot-detection system counts as "a technological measure that effectively controls access." Even where a human can still read the page.

Read what that establishes. Routing around a CAPTCHA to collect public content is now a claim that survives a motion to dismiss.

The trafficking count went. So did the two economic claims under state law, as preempted. The conspiracy count survived, and nothing is decided on the merits.

But if you buy data from anybody who scrapes, that ruling is your risk too. Do you know who your vendors buy from?

Reddit treats access to its content as a thing you buy or a thing you steal. There is no third category, and you are not in the first one.

A strange position for a platform built on public posting. We would plan around it.

One more thing about Reddit, and this one is useful. When it does get cited, it does not concentrate where you would guess.

A vendor study of 1,486 business software queries found 365 subreddits appearing across results. Only 96 reached an answer box. The top twenty absorbed half of all appearances.

Now the names. The most cited were narrow. A customer relationship management subreddit at 25 citations. A software-as-a-service one at 14. Self-hosting at 11.

Not the giant general subreddits: the small specific ones.

A second vendor found the same shape from the other end. The median cited comment: 38 upvotes. And 71% of cited threads sat in subreddits under half a million members. Small rooms. Cheap rooms.

Both numbers come from companies selling visibility software, so hold them loosely. But they agree with each other, and they point somewhere counterintuitive.

What gets surfaced is not the popular thread. It is the specific answer, in the narrow room, where somebody asked your exact question. One person, once.

A much smaller target than a Reddit strategy. And a cheaper one.

YouTube is not closed. It is asymmetric.

YouTube runs the opposite way, and the asymmetry is the finding.

Google's Gemini API documents it plainly. You pass a YouTube URL straight into a request. The model watches the video.

Their constraints: public videos only, ten per request, no length cap on the paid tier.

So Google's model can read any public video on the platform Google owns. So can you, through the same documented route, with an API key.

Which is where most write-ups of this stop, and it is the wrong place to stop. Two things complicate it.

First, that door is marked temporary. Google's own banner: the YouTube URL feature "is in preview and is available at no charge. Pricing and rate limits are likely to change."

Second, and this is the real asymmetry, watching is not the same as having the text.

The caption track is what every transcript-based tool needs. The Data API is one sentence long on who may download it.

The method "requires the user to have permission to edit the video."

Read what that closes. You can pull captions for one set of videos: your own.

Not your competitor's. Not the review ranking you fourth. Not the tutorial naming a rival in the title.

You can have a model watch all three. You cannot have the file.

Ask anyway: a 403. "The permissions associated with the request are not sufficient to download the caption track." Not yours to read.

So the practical consequence, stated plainly. Nobody outside Google can build a transcript corpus of videos they do not own.

Which is a narrower complaint than the field makes, and a more useful one. Any competitive YouTube number built on transcript text came from scraping, estimation or a vendor's private index.

Ask which one. Ask it now that a court has said routing around bot detection survives a motion to dismiss.

Worth knowing before you buy a dashboard built on one. Which one are you paying for?

What the rules actually say

Both platforms have brand participation rules. One set is enforceable law. Most GEO advice acts as though neither exists.

Start with the law, because the exposure is real and priced.

The Federal Trade Commission's rule on consumer reviews and testimonials took effect on 21 October 2024. It bans six things. Fake reviews. Buying reviews of any sentiment. Undisclosed insider reviews. Company-controlled review sites. Review suppression. Fake social-media indicators.

The civil penalty runs to one number: 53,088 dollars per violation.

In December 2025 the Commission sent warning letters to ten companies. Not determinations, but a signal about where attention is going.

Then the older instrument, and it is the one that names your exact situation.

Read the first two sentences again. An online community, a section for one product category, members asking and answering questions.

That is a subreddit, described by a regulator, before subreddits were the strategy.

The standard behind it is broader than most people think. Any connection that "might materially affect the weight or credibility of the endorsement," and that the audience would not expect, "must be disclosed clearly and conspicuously." Clearly. And conspicuously.

The duty does not stop there. Employers are expected to train staff and monitor compliance.

Now the useful half, because the rule is narrower than the panic around it.

Reddit's own rules are softer than the law. Worth reading for what they are.

The famous nine-to-one ratio, one self-promotional post in ten, lives in Reddiquette. That is informal guidance rather than the enforceable content policy.

So it is a norm the community polices, not a rule the company enforces. Which is harsher? The community, every time.

The company is now paying attention, for a new reason.

In July 2026 Reddit reported catching roughly 25,000 net new spammy posts and comments a day. It uses language models to find "coordinated patterns of fake behavior and artificial hype." Models catching models. Which side is your agency on?

Reddit's own post never says what the spammers are after. The trade coverage does.

EMARKETER, on 6 July 2026: as marketers optimize for AI answers instead of Google results, "a new spam economy is emerging."

So the motive is not Reddit traffic. It is getting cited.

So the tactic your agency may be pitching is already being run at scale. And caught at scale.

Though read Reddit's own enforcement numbers before you assume the risk is evenly spread.

In its most recent transparency report, covering late 2025, spam was 54% of administrator removals.

Go back to the January to June 2024 report, which broke the categories out further. Spam was 66.5% there. The category covering vote manipulation and artificial promotion: 1.8%.

Which is the honest picture: Bulk spam is the volume problem. Coordinated brand manipulation is a small labeled slice.

So the enforcement risk is real, and uneven. The legal risk in Table 9.3 does not care about distribution at all.

Four readers, four exposures

The legal exposure in Table 9.3 is not evenly distributed either. Where you sit decides which row you should worry about.

First, business software. Your category is where the concentration data came from. Those narrow subreddits are real rooms where buyers compare tools.

Your exposure is Example 8. A support engineer answering a thread is your best asset and your likeliest violation. The difference is one sentence.

Second, consumer and ecommerce. You carry the highest exposure in this chapter. Reviews are your channel. The review rule is the one with a number attached.

Audit how you solicit reviews before you audit anything else. Any incentive conditioned on sentiment, anywhere in your flow, is this week's job. Find it now.

Third, regulated categories. Health, finance, legal.

Your own regulator almost certainly has stricter endorsement rules than the Commission's. This chapter is the floor, not the ceiling. Ask your compliance team before step 5, not after.

Fourth, publishers and creators. You are on the other side of this. YouTube's declaration checkbox is your obligation, not the brand's.

The platform pushes legal disclosure to both of you. Which means a brand's failure to disclose becomes your problem too.

Traced to source

Fifth time. Chapters 5, 6, 7 and 8 each walked five claims back to origin. Same method here.

One query, walked

Take one query and follow it, because the abstractions above have a shape you can see. Somebody types what your buyers type: best tool for X, or alternatives to your competitor.

Ask what the engine has to work with. Four or five slots, not ten.

What fills them? On the independent numbers: mostly official sites, news and vertical publications, at roughly four fifths of citations.

Then the rest. One slot might be a video. One might be a thread in a subreddit with 40,000 members. Somebody asked your exact question there two years ago and got eleven replies.

Now ask what you could have done about each.

The official and vertical sources: that is Part II and ordinary coverage. The video: yours is measurable, everyone else's is not.

The thread: you could have answered it, with disclosure, when it was posted. You cannot answer it now in a way that reads as anything but late.

Which is the honest shape of this work. It is not a campaign. It is a presence you either had or did not have when somebody asked.

The rest of the corpus

Two platforms is not the whole off-site world, and Chapter 3 named the others. G2. Comparison pages. Your competitors' alternatives-to posts.

So take the verdict on those, briefly, because it differs from everything above.

They are open. No robots.txt wall, no licensing contract, no edit-permission gate.

Which means an engine can reach them the ordinary way, and so can you. You can read your category's comparison pages today. Free, in a browser.

Review sites sit between. Most run their own terms. Most have a front door. Most are explicit that you may solicit reviews.

Which puts them under Table 9.3 rather than under this chapter's platform mechanics. Solicit freely. Never condition on sentiment.

Then the alternatives-to page written by a competitor. That one is not a corpus problem at all.

It is a page describing you, that you did not write, ranking for your name. The response is a better page of your own. Which is Part II.

So the whole off-site corpus is three tiers: Open pages you can read and answer. Review platforms with rules and a front door. Then two large platforms that are closed or asymmetric.

Most budgets are aimed at the third tier. Most return sits in tier one. Where is yours?

What these platforms are actually good for

This chapter has been negative for six sections. Here is the honest case on the other side.

Three things are genuinely worth having, and none of them is a visibility tactic.

The first is the only unfiltered read you will get on your product. Step 2 of the artifact is not a marketing exercise.

Somebody described your onboarding to a stranger, unprompted, in their own words. No research budget buys that sentence.

The second is measurement. YouTube is the one platform where your own footprint is fully readable by you. You can pull captions for your own videos.

Which makes your own channel the cheapest place to test one thing. Is the language you use the language buyers repeat? Chapter 5 gave you the method.

The third is durability. Answering a real question in public outlasts anything else in this book. It sits there, dated, attached to your name, useful to the next person with the same problem. For years.

If a model reads it, good. If not, a customer did.

That is the whole case, and notice it does not depend on anything an engine does.

The direction of travel

Everything above describes the platforms as they are. Now the part that should change your allocation. The trend runs against Chapter 8.

Google said so itself, on the record, in May 2024.

The sentence came after the week AI Overviews suggested glue on pizza. "We updated our systems to limit the use of user-generated content in responses that could offer misleading advice." Limit. Their word, not ours.

The same post calls forums "a great source of authentic, first-hand information" in the sentence before. Both halves are true, and only one of them got engineered.

Then the measurement, and here you have to be careful.

Conductor tracked Reddit's citation share falling through late 2025 and into 2026. It puts the share at 2.02% in October and 1.01% by January, measured across engines rather than on any single one.

Take one thing from that: the direction, not the decimals.

Because the same datasets cannot agree what the level is. Chapter 6 carried 1.8% for ChatGPT across all queries. Promptwatch had ChatGPT Search steady at 3.83% in midsummer. MaxAEO reports 8.1% on ChatGPT, on recommendation-intent prompts only.

Different denominators, not a trend. Anyone drawing a line through them is drawing it through three different questions. Not one trend.

Which is the whole problem with this evidence base, stated once. Almost every number you will be quoted here comes from a company selling visibility software. Including ours. Weigh us accordingly.

Then, six days before this chapter was finished, the argument made itself.

That Promptwatch 3.83% held from 18 July through 7 August. On 14 August it broke. The average from 14 to 17 August was 0.52%, an 86% fall in four days.

Google's surfaces did not do that. AI Overviews drifted down 11% across the same weeks, AI Mode about 30%. Gradual, both.

Nobody has said why, and the vendor calls its own finding provisional. It cannot rule out a fault in its own collection.

So do not build on it. Build on the shape of it.

A surface reached by contract can change overnight, with no announcement, and you find out from a dashboard. That is what not a channel means in practice. Would you have noticed?

So weigh the independent measurement separately, and it is more sober.

An academic study of 602 controlled prompts and 21,143 citations found YouTube the most cited single domain. Reddit came third. Both real, and both small: YouTube around 2.6% of citations, Reddit around 1.5%.

A second, of 366,087 citations, found social media platforms at 10% of all citations put together.

Which is a real channel. It is not the channel a 0.737 correlation makes you picture.

One more finding, and it explains why every share in this chapter looks small. A study of 55,936 queries found generative engines return 4.3 URLs per response, against 10 for traditional search.

Fewer than half the slots. So every domain competes in a smaller room. Single digits mean more here.

The same study found something else. Roughly 37% of the domains generative engines cite never appear in traditional search at all. Which cuts both ways for you.

Fewer seats. Different guest list.

What this costs

Price it before you fund it, the same way Chapters 7 and 8 did. Community work has three costs, and only one is obvious.

The visible one is time, and it is expensive time. Answering well in a technical subreddit takes somebody who knows the product. Really knows it. Who is that, here?

That is a support engineer or a founder. Not a coordinator, and not an agency writer with a brief.

The second is compliance overhead. The Endorsement Guides expect training and monitoring, not just a disclosure line. So any program with more than two participants needs a record of who was told what. Write it down.

Small, but real. It appears in nobody's proposal.

The third is the one that ends most programs. Public participation means public criticism. In a thread you cannot edit, attached to your name, permanently.

Somebody has to be willing to answer the hard reply. If nobody senior is, the program stops after the first bad thread. You have paid for the setup.

Against that, the honest return. A count you can measure. A corpus you can read. And no published evidence linking either to an AI answer.

Which is a smaller promise than the category makes. Fund it accordingly, or do not fund it.

If you are already doing it

Some readers will get here having already run undisclosed accounts. So take the remediation path rather than the lecture.

Stop first, and stop today. Every further post compounds an exposure that is priced per violation.

Then find out what exists. Four questions: which accounts, which threads, whose idea, and was anyone paid?

Take that to whoever owns legal risk before you take it anywhere else. This chapter is not legal advice and the next step genuinely is.

Do not mass delete. Deleting is what investigators look for. Reddit's license terms already bar partners from using deleted content. So removal does not clean the corpus you were worried about.

Then rebuild it, disclosed. In most cases the posts were useful and only the attribution was missing. A cheaper repair than people fear.

The objections this chapter has to answer

"Reddit threads outrank my site for my own category terms. I can see it. You are telling me not to compete there?"

No. We are telling you what competing there consists of: answering, disclosed.

Answer where you are named, with disclosure, and that is competing. What this chapter rules out is the version with no disclosure on it.

A second, and it is the strongest commercial objection.

"Everyone in my category is doing it. If undisclosed seeding works and nobody enforces the rule, I am choosing to lose."

Two answers, and neither is moral:

The first is that the enforcement picture changed. Reddit is running language models against exactly this pattern, at roughly 25,000 items a day. And the Commission sent its first warning letters in December 2025.

The second is that nobody has shown it works. Not one published study, on either platform, has added activity and measured an AI visibility change. Not one.

So the trade is a rule with a per-violation penalty, against a benefit nobody has demonstrated.

A third objection, from a reader who took Chapter 8 seriously.

"You just spent a chapter telling me off-site mentions are what accumulate. Now you are telling me the two biggest sources are closed. What is left?"

Fair, and the answer is in Chapter 8's own table. Branded web mentions sat at 0.664, just under YouTube. Those are ordinary earned coverage.

The open web is not closed. It is only slower, and it was always the larger share.

Then a fourth, which cuts at our sourcing. "Half your citation numbers come from vendors selling visibility tools, including the ones you quote approvingly."

Correct, and we flagged it in the section itself. Hold the independent measurements instead. 602 prompts and 21,143 citations. Then 366,087 citations across twelve models.

Both are low single digits. Ten percent for social overall. Where vendor data and academic data disagree, we printed both. And told you which is which.

Then the one we raise ourselves.

One caveat on method, and it is a strange one. Reddit's block on that file keys to the agent string, not to whether you are a crawler.

Testing on 20 August 2026, curl got the file. So did an invented bot name we made up. GPTBot, Googlebot and bingbot each got a 403. Why those three?

We do not know. What you see depends on how you ask, so we fetched it with a browser agent and checked the Data API terms separately. They say the same thing.

The disclosure this chapter owes you. We sell GEO services. Community and coverage work is the largest line we could bill you for.

This chapter narrows that line to disclosed participation and a counting exercise. Notice what it does not do. It does not sell you a subreddit strategy.

What would change our mind

This chapter says do less. So it should say what evidence would make us say otherwise.

Three things, and any one would move us:

The first is a real before and after. Matched brands. One participating with disclosure, one not. Appearance rate on Chapter 8's schedule.

Nobody has run it. It is not expensive, and the field that sells this has had three years.

The second: an engine saying anything. Any documentation describing how community content is weighted would replace a chapter of inference with a paragraph of fact.

Google's only on-record statement points the other way, at limiting it.

The third is Reddit publishing what its licensees do. Volumes, a partner list, a split between training and retrieval.

Right now the company at the center of this names categories of buyer and nothing else. Which is its right, and it leaves everyone downstream guessing.

Until one of those three arrives, the honest position is the one in Artifact 9.5. Count, participate where you are named, disclose, and do not pay for a causal story nobody has told.

What is left

So the ledger for these two platforms, in three lines:

Reddit reaches engines through revocable contracts worth about a twentieth of its revenue. It blocks everything else.

YouTube can be read completely by the company that owns it and only partially by you.

Then the independent measurement, which puts both in single digits of citations. In a year when the largest engine said, on the record, that it limited exactly this content.

None of which makes them worthless. All of which makes them one thing: a smaller line item than the pitch.

Which is the sentence to take into the budget meeting. Smaller, not zero. There is a difference, and vendors on both sides of this argument keep collapsing it.

What survives is unglamorous and it is the same thing Chapter 8 landed on. Be genuinely discussed, in places you do not control, by people who are not you.

There is no faster version. Every faster version in this chapter is either blocked, undocumented or against a rule with a number attached.

Which answers what Part III set out to ask. You now know what the web around you is made of. And which parts you can reach.

One question is left in this part, and it is narrower and more fixable. Before any of this matters, a machine has to be able to read your page at all.

Chapter 10 is about what a crawler can actually execute. Three earlier chapters have been sending debts to it.