Most of those discussions rank in Google for branded searches (pushing people from buying) and impacting LLMs.

Very few businesses have any strategy around that.

>>> Join us to discuss this topic LIVE and bring your questions!

Don’t Try Reddit Unless You Have a Strategy

Most businesses and agencies treat random Reddit replies or fake, seeded threads as a “strategy.”

Dropping a few posts and tracking links won’t fix your problem or build a pipeline. It won’t show up in SEO. It won’t get cited by AI search.

The best-case scenario is that it will be just a waste of money. A more probable outcome is that it will make your problem worse.

Without a strategy, a better way is to do nothing.

But a smarter strategy is not viewing Reddit as a problem. It is slowly and surely turning it into your competitive advantage.

What do you need to create a Reddit strategy?

• Clear understanding of your product positioning

• Clear understanding of pain points as discussed on Reddit.

This is where I start any Reddit reputation management strategy: What are people complaining about?

To be sure, all pain points should be treated differently:

• There are factual pain points that are simply wrong: Sharing and repackaging raw facts that beat those is the best way (dates, stats, numbers).

• There are “rumors” or outdated misconceptions that keep haunting you. You can keep trying to cry, “THIS IS NOT TRUE” at every corner, but it won’t do any good… Instead, share as many personal stories (in your subreddit) as possible, beating that negative footprint with real-life stories from your customers.

• There are loyal customers who just don’t like any changes. This is common for older brands with a very well-established user base. Whatever new thing you try, they will be unhappy. This crowd is not going anywhere. They love you, and that’s their way to show their love. The best solution here is to make them feel heard and appreciated. These are my favorite negative comments, as these people are very easy to turn into the most loyal, passionate, and ever-loving customers. These could be your driving source of changing sentiment on Reddit.

• There are actual mistakes that need to be acknowledged and apologized for (don’t get defensive or arrogant here! Own your brand’s mistakes and tell Redditors you are committed to learning from those mistakes).

Before doing anything on Reddit, make sure you have a clear, safe, and authentic strategy to deal with all of the above.

Reddit Reputation Strategy: Reactive vs Proactive

Most businesses and agencies build a Reddit strategy around chasing Reddit conversations and replying to angry comments.

Well, it may work elsewhere. On Reddit, this strategy usually results in:

• More negativity (as you make those negative discussions more active by engaging in them)

• No change in sentiment: Your comment is one of dozens or hundreds. It may clarify something, but it won’t influence the overall brand perception (for people or LLMs).

A much more effective way is to own those conversations, and to be the top of the voice.

That means:

• Build your own channel (a subreddit) where these conversations happen

• Address and explain different types of those pain points inside your own subreddit (and make sure they rank and are cited by LLMs)

• Build positive sentiment through sharing factual and relatable content (e.g., expert or customer-driven AMAs, customers’ success stories, stats that reinforce your value proposition, etc.). It doesn’t have to be all about you (rather, it shouldn’t, of course). But you can share relatable stories, trends, and numbers that make your value proposition clear and known.

We have a client who charges more than their competitors (because they are a bigger, more advanced law consultancy), and that’s what Redditors always bring up when discussing them. And here’s how I explained the Reddit strategy to them:

If you have to explain to people why you charge more, you are doing it wrong. Instead, build the authority to a level where there are no questions like that.

And so for them, we focus on expert-driven AMAs, expert news commentary, etc.

It is a different strategy for everyone, but the fundamental principle remains the same: Don’t treat your Reddit reputation management as a band-aid. If you really want to be safe on Reddit, get serious about that and create a long-term strategy!

The beauty of this approach is that, when done right, it won’t just fix your reputation, but it will also become your most effective marketing channel!

Let me know if you need help!

But do we actually know how AI answers are created?

There are many steps there, and we don’t have much insight into most of them.

But first two announcements:

• 👉 JOIN us to discuss this topic LIVE (free, no registration required!)

• 👉 Ask your questions in your week’s AMA on Reddit! This week, the awesome is hosting an AMA on AI, SEO, EEAT and more!

Here’s how AI answers are generated, in a very simplified way:

1️⃣ Training-layer: In many cases, an LLM won’t even go further. It already confidently knows the answer. There are no URLs at this point. Training data doesn’t store links from where it found the answer. If there are citations for these answers, they will be reverse (citing pages that support a pre-written answer)

2️⃣ Retrieval-eligibility: When an LLM decides to search, if your page is found for one of the fan-out queries (which are also largely determined by training data: Which brands it knows to search for, which publications it knows will likely give trusted answers, etc.). Where it is searching is unconfirmed, but mostly Google for now (and likely some partnerships, etc.).

3️⃣ Retrieval-ranking: It finds URLs, now it chooses which ones to “read”. Correct me if I am wrong, but we really don’t have much insight into how it makes a selection.

4️⃣ Extraction: Which content ends up being pulled into the answer? This is where content clarity, structure, etc., likely comes into play.

5️⃣ Citation-slot assignment: So an LLM picked URLs, pulled an answer, etc. Now it chooses what to cite. This is where it gets interesting. It can cite URLs it “read” and pulled answers from (4️⃣), it can cite URLs it never read but retrieved (3️⃣), or it can pull random URLs that never came up in 2-3-4 (from partners, or even hallucinate them). AND YET, this is pretty much all we can see/measure/test. The gap of how URLs got here is huge (see above).

As an industry, we overfocus on and measure 5️⃣, we optimize for 4️⃣, and tend to ignore 1️⃣ (which determines everything).

Let’s put it altogether:

1. Training layer

It is not SEO.

It’s all about building a known brand with a clear value proposition that answers a question or solves a problem in a prompt.

2. Retrieval-eligibility

This step is purely SEO: If your URLs rank well for what an LLM is searching for, it will be found by an LLM.

3. Retrieval-ranking

This is kind of SEO too, even though we really don’t know how LLMs pick which retrieved URL to “read”. It likely depends on:

• Rankings (the closer to the top your URL is ranking, the better the chances are LLMs will visit it to find answers)

• Search snippets (if the search snippet looks very relevant to the question behind the prompt, it will likely be picked for answer extraction). This is where schema may help a lot!!!

4. Extraction

This is kind of SEO too, or Answer Engine Optimization (if you need a new acronym to impress your boss).

5. Citation-slot assignment

This is what SEOs tend to stress about even though there is 0 clarity as to what will ultimately get cited.

Actual URLs that were found and pulled answers from may never get cited.

Google has long been struggling with the definition here. There was helpful content, there were hidden gems, but nothing that would express an idea in a practical way: You need content that is unique enough for it to deserve a click and attention.

Join us to discuss this topic LIVE and bring your questions!

So what is commodity content, and what is non-commodity content and which one do you mean? (Spoiler: I think you need both)

What is “commodity” content? And what is non-commodity content?

As Google’s AI defines it, a commodity is something basic and raw that can be bought and sold in commerce with two key characteristics:

• Its value is the same no matter who produces it (e.g., one barrel of oil is the same price regardless of who sells it)

• It is never a final product (it is used to produce more complex goods). If we extend this terminology to content, commodity content is something that be easily repackaged in an AI answer.

Well, in other words, it is ~90% of content that is being digitally produced these days (actually likely much more than that with AI generating this type of content within seconds).

It is also what, ironically, LLMs have been training from so far (that’s why they needed Reddit so desperately).

The non-commodity content, as a term, was first introduced by Danny Sullivan (thanks for the slide @Jean-Christophe Chouinard). I am pretty sure Danny actually came up with the term because it sounds like him very much :)

Here are the actual examples:

Running shoe store content:

• ❌Commodity content: “Top 10 Things to Consider When Buying Running Shoes” (Standard advice on sizing, arch support, and cushioning).

• ✅ Non-commodity content: “Why This Customer’s Shoes Collapsed After 400 Miles: A Wear Pattern Analysis” (A deep-dive video analyzing the wear pattern on a customer’s shoes after 400 miles, explaining exactly why their specific gait caused the foam to collapse laterally.)

Real estate business:

• ❌Commodity content: 7 Tips for First-Time Homebuyers (General tips on pre-approval, location, and budgeting.)

• ✅ Non-commodity content: Why We Waived the Inspection (And Saved $15k): A Look Inside the Sewer Line (A breakdown of a specific bidding war you won last week: “We offered $15k under list but waived the sewer scope because I personally crawled the line and saw it was PVC, not concrete.”)

Interior design business:

• ❌Commodity content: 2024 Kitchen Trends You Need to See (Photos of green cabinets and brass hardware found on Pinterest.)

• ✅ Non-commodity content: Marble vs. Grape Juice: Why I Refused to Install Stone for a Family of Five (A video explaining why you refused to let a client put marble countertops in a house with three toddlers, showing the stain tests you did with grape juice and turmeric to prove your point.)

Non-commodity content is experience-driven and unique

It cannot be summarized in an answer without giving you prominent credit. That is the biggest part I see here.

Expertise is becoming a commodity. LLMs have expertise.

What they don’t have and never will is experience.

But the thing is, like Gus Pelogia stated, experience can be commoditized too, once it becomes part of training data.

It is a very fine line between providing non-commodity content and making it seen enough for it to become common knowledge…

So what to do?

You become the SOURCE…

It has always been key to building the authority (which drives all other visibility metrics) but it is talked about more these days.

If you are the source of the data or a finding or a trend, your name is much harder to erase from the summary. You are not one of the voices. You are THE voice.

I’ve talked about this a lot: You need to be investing in proprietary research. Your own data is what makes you unique. But it is also not just about building, it is always about doing it right (why would anyone care about your study?) and putting it in front of people who will find it interesting enough to spread,

It is good old content marketing with a new name.

So is “non-commodity content” all I need to publish now?

No

Don’t forget, Google’s guidelines as well as Danny’s presentation are all about SEO (getting you findable in organic search).

The most important SEO strategy out there hasn’t changed at all, “Your site should not exist for SEO only.”

SEO-first approach works until it doesn’t (which usually happens fairly quickly these days).

Your commodity content should exist as long as it helps your users. I am sorry for this commoditized advice (pun intended), but it is still true:

Search engines will like you if your users do. LLMs will like you if your users do.

This is the algorithm we should all optimize for, especially now that LLMs learn and mimic what people do.

Commodity content will help people who are at the beginning of their journey (if you do it right), regardless of how they found it. You need to be helping people at every step of their journey. This hasn’t changed.

So what has changed?

We have a new term to use! As an antonym to “commodity”, “non-commodity content” is something that doesn’t have a universal/flat-rate pricing and cannot be easily repackaged into an AI answer.

But it is not enough. For real impact, your non-commodity content should also make you “top of the voice” in your niche. It will work for organic search and LLM visibility. Otherwise, it may still be commoditized.

If you need help developing an effective content strategy that turns your brand into a destination, ask me how!

There’s not much information LLM platforms would provide us with, so we have to rely on patents and independent studies looking at correlations.

has collected all those available documents, found tactics that are most mentioned everywhere, and put together a list of what seems to move the needle.

I decided to take one step further here and create a bridge between traditional SEO and SEO for AI (GEO) to see how things have really changed.

Join us to discuss this topic LIVE and bring your questions!

Note that SEO is being perceived differently depending on who you ask. In my interpretation below, I am talking about traditional SEO as I see it. And as someone who has been in SEO for more than 20 years, I think I am totally entitled to define it.

So let’s look at those GEO correlations and see if it is “just SEO” or if we need to start doing something differently.

1. URL accessibility = Is the URL accessible to a search / LLM bot?

100% technical SEO, although it is getting a little harder to navigate with more bots that can still access your page, no matter the directions, and new technology trying to control that.

2. Search rank: High-ranking URLs get cited by LLMs

100 % SEO

Not sure if this needs an explanation.

3. Fan-out rank = How visible a URL is for queries that an AI agent is searching for

90% traditional SEO

LLMs choose different queries to search. But these are still keywords…

4. Preview control = What you allow search engines to show their users

I wish we had more than 100% of SEO here.

The fact that LLMs use search snippets is the most solid proof that they depend on traditional search too much!

I have seen many tests showing that LLMs simply cite a search snippet without actually going to the page itself.

5. Query-answer match: Your page should match both the search query and the AI answer

It is, again, 100% SEO, but the term “semantic relevance” is thrown around so much nowadays that I’ll go ahead and give it 95% SEO in case I am missing something.

6. Intent-format match, e.g., Citing listicles when a user is asking for “best” options

We have been talking about intent optimization for many years in SEO. But I’ll give this a 20% of GEO because I think LLMs are just more straightforward with intent than people.

Human searchers may have no intent when searching. LLMs know what they are doing.

7. Topic cluster ranking: Ranking for multiple related queries increases your chance of getting cited

This is 100% SEO because it goes back to traditional rankings.

I’ll give it 20% of GEO just because LLMs do fan out to related queries a lot more. So you need to capture more than “obvious” queries here than in traditional SEO.

8. Answer near the top: Giving a good answer in the first third of your page will get you cited more

“Above the fold” has always been important in traditional SEO.

But I’ll give this one 45% of GEO because LLMs are lazier, so this has become more important than previously.

9. AI-ready structure, i.e., Ask & answer questions on your page like you are explaining things to a three-year-old

Clarity has been important for SEO, but it looks more important for LLMs.

Not a new tactic, but definitely discussed more due to GEO now.

10. “Factually specific”, i.e., Avoid bold claims, stick to the facts

Same as above: It has been important since the launch of featured snippets. But it seems more important for LLMs.

11. “Explicit phrasing”: Avoid vague statements, stick to an active, confident voice

This has also been part of featured snippet optimization, but not necessarily that much discussed.

12. Cite sources (not necessarily linked)

In SEO, this has always been a debate: whether outbound trusted sources add credibility to your page. Many SEO experts recommended linking out to GOV and EDU sources for EEAT…

The effectiveness of this has never been confirmed by any SEO studies (or officially).

In LLMs, there seems to be a consensus that citing sources helps (and studies to support that). Also, sources don’t have to be links.

13. Self-contained passages (+or sentences)

We have been (kind of) talking about this since Google’s passage-based ranking announcement (around 2020), but we definitely talk a lot more about this now.

14. Content visibility, i.e., No hidden content that is accessible through JavaScript

One of the oldest, most forgotten SEO checks: Is the page fully readable with JavaScript disabled? Google has become incredibly good at rendering JavaScript, and I usually skip recommending anything as long as the page looks good in the URL Preview inside Search Console.

It is now fully back, as AI Agents are believed to skip any sections or page elements hidden by JavaScript.

15. Freshness, and the date on the page

It is hard to measure here, so I’ve put 50%/50%.

In SEO, it depends on the query. In GEO, the “freshness” bias may be fully driven by organic search results.

16. Brand entity and trust

I am a little surprised that this one comes at #16

I think being a known and trusted entity is the most important factor for both SEO and GEO.

But I guess it is extremely hard to measure.

17. Length / word count

The debate has existed as long as SEO itself, so it feels like it has entered the “GEO” sector out of habit.

In GEO, though, LLMs seem to have been proven to be too lazy to read further down the page, so the content length debate makes a bit more sense here.

18. Language

Both search engines and LLMs try to surface pages in your language…

LLMs are easier, though. To find pages in your preferred language in Google, you have to change the language settings. In LLMs, you can simply prompt in a different language for it to switch to that language and foreign URLs.

19. Entity consistency

The biggest difference for GEO so far. You need to be consistently described across (and outside of) all possible channels.

Not sure how that could impact citations, but it is definitely important for the answer inclusion.

20. Structured data (schema)

Rich snippets improve clickability, which improves rankings, which improve LLM visibility.

That, or else, pages with schema just tend to be better optimized overall, so they rank for many other reasons.

These are the best ways to explain any correlation between schema and LLM visibility, as far as I can see.

For the lowest three, I am not sure I have an opinion.

• The URL is already known to the AI engine via its training data (not sure how this can be measured…)

• Domain authority doesn’t correlate with anything these days, so not sure why we still talk about it.

• LLMs.txt would be 100% new for SEO if it worked…

If you are looking for help to figure all of this out, I have a free option to connect and discuss!

These links are called citations, and they may appear in-line within the answer and in a separate panel, often to the right of the answer itself.

Generative Search Optimization (GEO) services often prioritize “citation optimization,” but not many businesses understand how those AI citations work.

Understanding the algorithm behind being cited is key to creating an effective GEO strategy. But first a couple of free and unique SEO+AI education opportunities to join this week:

• Please JOIN US to discuss this topic LIVE on Linkedin (and bring your questions!)

• Please ask your questions in this week’s AMA on Reddit hosted by SE Ranking rep Bogdan Krupin!

Here’s what we know about AI citations:

Where do LLMs find citations?

There is no official data answering this question. From exploring overlaps between citation visibility and search rankings, as well as by using independent tests, so far, we know that:

• ChatGPT*, Gemini (and AI Mode), and Grok use Google search

• Claude and Perplexity use Brave search

ChatGPT* also has long-term agreements with top publications which it can cite without searching any external engines.

Maintaining high rankings in both of those search engines increases your site to be cited.

What types of LLM citations are there?

Again, we don’t have any official statements as to how AI citations work but from patents and independent studies, we know about these three types of AI citations:

1. Grounded citations

These are AI citations that influence the answer itself, i.e., LLMs run searches, “read” the content of pages they found, and sync the answer from those pages.

In this case, if found and cited, your content becomes part of an AI answer.

2. Ungrounded (reverse) citations

I refer to these types of citations as “reverse citations” because the process is reversed here: an LLM pulls an answer from its training data (it already “knows” the answer) and then finds URLs that support this answer.

This process likely exists to keep the AI answers more accurate and unbiased.

In this case, citations do not influence the answer content. To be surfaced in an answer, your business needs to be known as a solution to an underlying problem or an answer to a prompt.

We don’t know how many citations are reverse, or how likely each specific LLM is to give answers before searching. The recent NY Times article indicates that half of Gemini citations are ungrounded, but it doesn’t cite the source of that data.

3. Invisible citations

In many cases, URLs are found, retrieved, “read” by an AI agent, and used to create an answer, but they never get cited.

The recent study from Ahrefs indicates that about half of URLs retrieved by ChatGPT remain uncited, but invisible citations can differ based on the source. For example, Reddit threads almost always impact an answer, but very few of them are cited.

4. “Ghost” citations

This is when getting cited didn’t help your brand appear in the answer. This can be due to the “reverse citation” process. This can also happen because your own content that got mentioned didn’t do a good job explaining how your business or your product helps solve the underlying problem, i.e., your brand wasn’t part of your own content context.

According to Kevin Indig, about 60% of citations are “ghost citations”, failing to get the brand included in the answer:

What are the actionable applications?

Knowing how LLM citations work can help you prioritize your GEO strategy better, as well as create content that helps your business’s AI visibility:

Being cited is not a priority

Many GEO strategies focus on the number of “owned” citations for important prompts, i.e., they measure the strategy’s success by how many times your own site is cited. Knowing that citations may not influence an answer or, vice versa, that a URL can be used to create an answer but never cited, helps shift the priority from getting cited to being visible in the answer.

Optimizing for AI citations is still a good idea, but your content strategy should focus on putting your products in context. This way, even if your URL isn’t cited, the answer will still include your product.

Being present in the training data is fundamental

LLMs may or may not search to give an answer. They may search after they have already created an answer, or they may or may not use a page’s content for an answer. Being associated with specific questions in the prompts is the only way to ensure consistent visibility in AI answers.

The training data often defines how LLMs search too. For example, if you prompt ChatGPT, “Best shoes for long-distance traveling”, it will search for specific brands and product names it already knows:

Your GEO strategy should be all about getting cited. It should prioritize building a brand that is known for solving specific problems.

Creating and marketing studies that are driven by your own data is how you do it, if you do it right.

>>> Join us to discuss this topic LIVE on Linkedin!

Cyrus Shepard published a study that identifies 5 common trends among winning websites in Google. One of those winning tactics is publishing unique studies.

As we are creating and marketing data-driven studies for our clients, we also see these consistently become top-cited sources for LLMs:

Data-driven PR campaigns win every race: They do well in Google, they send lots of great links, they get cited by LLMs, they go viral on Reddit, etc.

So, how to market proprietary data?

Find unique angles

You may think you don’t have data that could tell a unique story.

In most cases, you are wrong.

For example, Ramp is a payment processor. Boring? No! They were coming up with great, well-researched articles that are fully driven by their own data!

Use your own data in creative ways!

Don’t publish more than you can promote

This is a common question: How many should I do?

My answer is always the same: Do exactly as many as you can promote properly, because the marketing part is as important as asset creation.

Make sure to:

• Repackage your asset on social media (and then repackage more!)

• Reach out to journalists covering these topics

• If you have a Reddit presence, seed it there. Reddit loves unique studies.

The success (and future organic visibility of your asset) directly correlates with how much effort you put into promoting it.

Buzzsumo has great outreach tools I’ve been using for years.

Prioritize updates over brand new assets

I am a huge advocate of working with what you have already done. I love looking at rankings, citability, backlinks, new data, etc., to see if it is possible to update an asset to give it more life because that usually results in better organic visibility.

When you refresh an old asset, you have an opportunity to work on existing results (improve rankings, re-optimize, focus on what triggered more engagements, etc.) Less work than working on a new asset, better results because you can make more informed decisions!

If you need help brainstorming, let me know! Data-driven PR is what we have been doing for more than 15 years!

SEOs always discover a tactic that works and massively jump into it until it becomes a problem, even for those who are trying to do it right.

Listicles are just one of many examples of this happening, over and over again.

We know they work for LLMs, as the list format is very easy to pull entities from. And the rise of self-serving and commercial listicles has been insane to watch.

Brands were forced into sponsoring their mentions in listicles, and lots of publications were switching to the “Top lists” format to monetise their existence… until Google noticed.

Poorly researched and self-serving listicles are losing organic search visibility now. One of the popular examples is ClickUp, which went aggressive with listicles to lose about 7M in estimated organic traffic over the past 6 months.

This has been well-expected. There has been so much talk about listicles that Google was bound to listen.

The real problem is that shortcuts are not right or wrong as long as you are making a well-informed decision.

Let’s zoom out just a little bit here… I know “GEO” sells, but so far, there are no actual signs that LLMs are driving real, massive visibility.

• Our own study indicates that consumers are not embracing AI as fast as it may seem inside our little tech bubble.

• But ours is not the only study that proves that. Ahrefs tracks online traffic trends and reports that LLM traffic is about 0.26% of the overall inbound traffic digital brands generate.

So why are we so obsessed with LLM optimization?

We are discussing this topic this week. Join us!

• On LinkedIn, we will discuss the topic and answer your question (no registration required! Just come over! Sam Page, an SEO expert and old friend (and the former Global Head of SEO at Amazon Business and Director of SEO at Slack), will co-host the event to share his insights!

• On Reddit, Sam Page is also hosting an AMA (Ask Me Anything) session on anything related to SEO and GEO! Ask your questions! This is a great opportunity to

I am not saying you should ignore where AI is going, to be sure…

I am the one talking about SEO for AI all the time. I even started a dedicated subreddit to curate findings and studies around “GEO”.

But let’s all face it: LLM visibility is not something to lose visibility in other channels for. At least not for now.

Even if something seems to work, on a grand scale of things, among all the tactics you can invest in, LLM optimization shortcuts will likely bring you some minimal results, even if successful.

“GEO” visibility is long-term. It is NOT about shortcuts.

It is about building a relevant, clear brand that is associated with what it does (and problems it solves). It is, first of all, building relevant visibility elsewhere where LLMs are pulling from (Google, Reddit, Youtube, maps, etc.)

It is about being known for what you do.

Shortcuts may work for a few months, but they may cost you fundamental visibility, which will be hard to rebuild.

Get real and build something that will sustain any Google reviews or LLM model changes. And if you need help, ask me how.

One topic that the article failed to give more attention to is the so-called “ungrounded” citations that make evaluating AI Overview accuracy challenging.

“Ungrounded citations” are citations that, basically, have nothing to do with the AI answer itself. This is when an AI answers links “to websites that [do] not completely support the information they provide”.

I found it surprising that the whole concept of citing sources that are not, in essence, actual sources didn’t seemingly surprise reporters who are taught to provide trusted sources for their claims.

Before I explain why this concept of ungrounded answers is actually a huge deal for SEO, here are two exciting opportunities for you to join:

• >>> JOIN US to discuss LIVE on LinkedIn and ask your questions (and/or get featured!)

• The one and only Lily Ray is hosting an AMA on Wednesday, and this is your chance to ask her anything you’ve been trying to figure out! Ask away before it expires!

Source: X

Let’s take a deeper dive into this AI phenomenon because it is not discussed enough, while providing a huge insight into LLM visibility (GEO) as a whole:

What are “ungrounded” citations, and why do I call them “reverse” citations?

An ungrounded citation is a link that an LLM finds after the answer is written.

In other words, the process is reversed here. Instead of using additional infor from URLs it finds, an AI bot will first write an answer based on what it knows and then find URLs that seem to support the answer.

Reverse citations are nothing new.

Back when ChatGPT was just launched, it gave no citations whatsoever. And we demanded. So it started providing URLs that had nothing to do with the answer because the process was reversed:

1. It writes an answer from the training data

2. It gives URLs on the topic (seemingly without “reading” those pages).

Since then, LLMs started searching much more. And they seem to sync answers from those URLs in most cases, but the question has always been there:

What comes first? An answer or the citations?

What influences what?

The NY Times article seems to shed some light.

Roughly 50% of Gemini answers are ungrounded

That is, it pulls answers from within its training data. And THEN finds what to cite.

We know (from leaked Claude docs) when LLMs have to search for answers, i.e., when the answer requires more recent knowledge than the training data realistically can have.

In about half of use cases, LLMs are likely to tell you what they already know.

And that is happening for at least two reasons (in my opinion):

• Training data gives more unbiased, more correct answers because citations can be manipulated (we are well aware of that)

• It is less resourceful than syncing answers from new searches.

Aaron Haynes has an excellent prediction here:

…the part that’s going to get worse: Gemini 3 got more accurate AND more ungrounded at the same time. Those aren’t contradictory - they’re happening at different layers. accuracy is improving in training (the model just knows more). Grounding is degrading in retrieval (the model needs sources less, so it cares about citation fidelity less).

And yet, training data doesn’t store URLs that LLMs once learned answers from. So, to provide you with sources, they need to search for citations that seem to support their answers. And at that point, citations don’t influence answers, nor your brand’s visibility in them.

Why do SEOs need to know this?

Quite clearly, this directly influences the optimization strategy.

If you are only optimizing for “retrieval” (which most SEO / GEO experts seem to talk about, you are very, very far behind.

Product positioning and awareness inside training data are fundamental and crucial for AI visibility. It is also a much more difficult process than simply optimizing for retrieval, and it takes a lot of marketing channels to align with your value proposition.

Digital PR, Reddit marketing, on- and off-site content alignment and visibility - everything should be adding clear, consistent context around your brand, for months and years, loudly enough for LLMs to notice.

If you need help with that strategy, reach out!

In reality, SEO expertise is the foundation of GEO for two main reasons:

• Organic search visibility is fundamental to AI visibility because LLMs primarily use search to research a topic and discover brands or products. Without SEO, your URLs will likely be unfindable for LLMs.

• Most traditional SEO tactics are key to LLM discoverability in one way or another.

Here are those SEO tactics that remain fundamental to AI visibility optimization:

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Keyword research

The conversational nature of generative AI search prompted many SEO/GEO professionals to announce keyword research as “useless” or “dead”.

I consider these claims fundamentally wrong.

First of all, there’s no replacement to the query data. We don’t have any access to the reliable prompt data. Essentially, we cannot know what users are typing as AI prompts to discover brands or products.

Keyword research is still the only source of insights as to how consumers arrive at certain buying decisions. Keywords can be organized by intent, giving you clues on how to structure your site to help your target customers at every step of their research.

Keyword (content) gaps help you identify what your site may be missing and where it is failing to be helpful to customers.

All of that is as useful for organic visibility as for LLM visibility because LLMs mimic people’s buying journeys and mostly take the same steps when helping their users to choose a product to buy.

There’s no way to optimize for prompts because they are likely to be all different and unpredictable. Keyword optimization is all we need to create content and pages that solve your customers’ problems and cater to their needs.

Content optimization

On-site content SEO hasn’t fundamentally changed due to LLMs. Like 5 years ago, we still need optimized content to:

• Help customers when they are still researching their problems (and may not be ready to buy).

• Put your products in a relevant, problem-solving context.

Optimized content may not generate the same amount of traffic these days that it did 3-5 years ago; yet it doesn’t mean you should stop publishing it and focus on “bottom-of-the-funnel” / high-intent queries that generate sales (this is a popular recommendation many “GEO experts” make).

LLMs can take your content, summarize it, and give it to your customers in the form of a comprehensive answer, so they never have to click to your website. But it will likely still influence your customers’ buying decisions because your brand will end up being part of that content, and LLMs will likely recommend them as a solution.

Nowadays, we optimize for buying journeys, but we still use keyword research to understand those buying journeys, and we keyword-optimize content for both search and LLM bots to be more likely to find it, and “understand” that it is relevant to the users’ needs.

Site architecture and navigation

In traditional SEO, flatter site architecture (which ensures no pages are dug too deep into the site) and better internal linking strategy ensure better crawlability and more long-tail keyword ranking opportunities.

In LLMs, clear site architecture ensures that LLMs understand your business better and place your products correctly in the training data.

In both cases, your site navigation should be:

• Well-structured for customers (or LLM bots) to be able to quickly find what they need

• Usable without JavaScript enabled (for it to be usable regardless of the browser (or absence of one) it is being accessed through)

• Clear and focused to reflect your site’s purpose and value proposition.

Link building

Whether any of the LLMs use any authority signals like backlinks, we don’t know. The only hint of Gemini / AI Mode using PageRanks was almost a year ago. So whether backlinks directly influence LLM citability is unknown.

However, backlinks (specifically, linked or unlinked brand mentions) are important for other aspects of LLM visibility:

• Higher organic rankings, which (again) drive LLM findability

• Entity associations (being mentioned/linked to alongside your well-known competitors)

• Authority: Regular and consistent brand mentions and links on authoritative publications make your business more trustworthy (which helps frequent answer inclusion)

All of these indirect LLM visibility signals are achieved by a high-quality link-building strategy (like data-driven digital PR).

Of course, there’s more to GEO than SEO best practices, at least for one crucial reason: GEO relies on different success metrics than SEO. But without knowing and implementing traditional SEO, your chances of being found by LLMs are almost 0.

Many of our leads and clients look at impressions and clicks, which are both solid metrics you want to see growing.

But if we are talking about Reddit in the context of LLM visibility, we consider the following metrics a success:

• More control over branded organic rankings

• More positive brand mentions (especially on Reddit)

• More organic reviews inside the official subreddit

• LLM citability

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Let’s look at each of these in more detail:

More control over branded organic rankings (and more branded searches)

This one is pretty obvious: We cannot control all the sentiment for branded organic search but we do want to balance it with official sources.

Ultimately, we want the subreddit to rank for queries like [brand name], [brand name reviews], and [brand name reddit].

This doesn’t happen overnight and it takes a strategic effort but it does happen. Here is an example of a Reddit pack that includes our client after 5 months of work:

Overall, we want to see:

• More branded searches (growth in impressions and diversity)

• More of the official subreddit ranking for those in top 5

More positive brand mentions on Reddit

We start tracking the brand and competitive mentions right away to better understand gaps in the product positioning and the pain points that are being repeatedly discussed.

As we consistently build our own official narrative, we start seeing the sentiment shifting to neutral and more positive.

You can track the shift through Reddit’s own “Trends” dashboard (especially for bigger brands), and/or you can feed the recent threads into your favorite LLMs and let it analyze what’s changing and what needs to be addressed.

Start tracking your brand name in Reddit’s native dashboard to monitor shifts in brand perspective and product positioning

There will always be negative comments on Reddit (it’s the nature of the community), but balancing them with an authoritative voice and positive reviews works to change the overall context.

More organic reviews inside the official subreddit

Speaking of bad reviews, as I said, they will keep coming, but the goal is for them to start mostly coming into your subreddit, where you can manage them properly (reply, DM, etc. to fix the relationship with the client) as well as balance them with positive ones.

Negative comments coming to your subreddit are A GOOD THING because they will not blow up with more negativity from other users. They will be managed in a timely manner.

We report on the increased customer engagement with the subreddit, and call a growing number of both negative and positive reviews posted there a success.

LLM citability

All of the above progress we focus on contributes to a shift in LLM perception of your brand and the likelihood of your products being included in the AI answer.

The branded subreddit being cited by LLMs is a direct, easy-to-understand metric that clients are always excited about. So we report on those two. We use Peec to track those:

Do you need help building a Reddit marketing strategy focusing on the right metrics? Let’s hop on a quick free call.

[And yep, most businesses and marketers approach this WRONG!]

Let’s get to the bottom of this:

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+++ Also, check out us discussing Reddit marketing in the recent podcast episode

1. First and Foremost: HOW exactly ChatGPT (and other LLMs) uses Reddit to answer prompts

In fact, there are two ways, working independently here:

1.1. Reddit is part of training data.

We all know that OpenAI partners with Reddit on this. Two VERY important things to remember here:

1. Training data doesn’t store URLs! Whatever LLMs learned from Reddit and store for training is not linked (and consequently not cited). What you see cited in AI answers is NOT necessarily what LLMs were trained from.

2. Training data may take months to get updated (for ChatGPT, usually it updates with each new model launch which doesn’t happen that often!). If you spammed marketed on Reddit for the past two weeks, it is not going to be part of the training data too soon.

1.2. Grounding (AI bots searching, finding threads, analyzing them, syncing them in the answer, citing them)

The more visible the threads are in organic search (mostly Google), the higher the chances that they will be cited and/or influence the answer.

Let’s not forget that higher-ranking threads are often 3-5 years old, archived, and impossible to answer.

Another interesting (and VERY important) note here is that ChatGPT routinely uses the SITE:reddit.com operator to dig deeper into the brand sentiment on the platform.

Why do we need to clearly understand all of this?

Based on the above:

• It takes a lot of time for Reddit to start influencing the training data (which is fundamental to AI answers and product positioning)

• Organic visibility of Reddit threads is key to those threads being cited

• (Spam) comments here and there won’t influence your visibility. It’s about consistent, strong voice that can move the needle.

In other words, it takes a more strategic, more holistic approach for Reddit marketing to make any impact on LLM findability.

Is Reddit enough for AI Visibility?

This is my favorite question and the answer is a big NO!!!

Reddit is not used for “discovery”. Which brands make ito the answer is determined by:

• Organic visibility

• Brand awareness (through strategic PR)

• Clear product positioning

• Co-occurrence with other relevant solutions

Reddit is mostly used at the claim verification stage, meaning that ChatGPT wants to make sure all the found options are worthy and trusted enough.

In other words, if you didn’t make it to the list at the discovery stage, your Reddit presence is not going to help!

On the other hand,

If your brand was discovered by Reddit, but you have a suspicious footprint there, you won’t be recommended either

This is the bottom of the LLM-driven funnel. You built a visible brand, but you won’t get recommended until you earn trust. Reddit is one place (of many) to determine your ultimate visibility at this point.

You need:

• High-quality authority-driven presence on Reddit

• Consistent, highly-focused, highly-relevant context for your brand (best achieved through your own subreddit)

• Engaged community / your loyal customers (that will eventually help fix and balance negativity and share authentic product recommendations).

LLMs are getting increasingly good at claiming loud claims and identifying fake reviews. If you want Reddit to help your brand get recommended, you need to do it right. Otherwise, it is a waste of money, which can also ruin your reputation.

If you need help creating an effective, long-term Reddit marketing strategy, get in touch!

For years, customers would routinely research a brand on Google to see if it is trustworthy enough. Hardly ever did they use long tails or look beyond page #1 of Google. So the traditional reputation management task was to “clean up” page one for the major branded searches.

With LLMs searching on your customers’ behalf, this has drastically changed, and we don’t talk about that enough.

>>> JOIN US to discuss LLM reputation management LIVE!

1. They know how to research

While LLMs, just like human beings, may search Google (or other search engines) to identify initial information, they will most likely check many more sources. For example, here’s what ChatGPT checked when simply asked for company information listed on a website:

What I found (and didn’t find)

There is no major website or company profile (Crunchbase, LinkedIn, OpenCorporates, etc.) clearly tied to a brand called “XXX”

No consistent domain (like howtonow.com) surfaced as an established business with identifiable ownership, leadership, or filings.

Right now, “XXX” does NOT appear to be a recognizable company entity—at least not one with:

• registered public filings

• media presence

• or structured company data

This would be classified as:

• Low transparency

• Low operational footprint

• Likely monetized via ads / SEO traffic

And mind you, I didn’t even ask for that investigation. I simply asked to find a company name on the website itself.

2. They fan out to “reviews”, “complaints”, etc., so that humans don’t have to

LLMs decide which queries to use to be helpful. They will use their fundamental knowledge about a product or a brand to research pros and cons thoroughly. If customers have doubts, be sure ChatGPT will confirm them. Here’s what it responded when I asked if Ryze coffee is actually helpful:

What were its sources (beyond its training data):

• Reddit (mainly)

• Mayoclinic as well as health-related publications

• Ryze review at Vice and other publications.

It actually grabbed and summarized reviews from Reddit, calling it “hit or miss”:

For product research, they will likely check known UGC, review, and/or comparison platforms like Reddit, G2, etc. It has been noticed that ChatGPT often uses SITE: command to search inside those platforms:

And be sure, if your customer has a specific question, like “What’s the upfront charge,” LLMs will likely find an answer, however hard you were trying to hide it.

What does it mean for businesses?

Top organic results for your branded search are no longer your only goal. You need to get serious and real about your reputation and own the context:

• Publish real, well-researched, well-referenced studies on your site (I have just shared solid benefits of those)

• Create your own real, well-maintained subreddit to address the common pain points and give your customers a space to share their experience (good or bad, so that it’s not just all bad)

• Keep an eye on ALL the platforms where your customers are sharing their experiences

• Build connections with editors in your niche to keep them updated on your product updates, new studies, etc.

• Keep an eye on your digital footprint consistency and make sure everything is up-to-date

• Work on your site and About page.

• Talk to your customer and sales teams to ensure you are all aware of the most common questions and concerns, and how to address those.

It’s a multi-level, well-integrated strategy these days, vs a linear approach focusing on 10 blue links a few years ago.

I create custom and actionable reputation roadmaps that make this whole process doable. Schedule a free call with me to find out how!

The only official AI visibility optimization guide was published by Microsoft but it didn’t provide any insights beyond common-sense SEO advice.

So we have to rely on independent studies for citation optimization strategies.

>>> Join us to discuss this topic LIVE (and bring your questions!)

The two most recent studies offering some actionable LLM optimization takeaways were:

• An analysis of 8,012 verified ChatGPT citations by Kevin Indig, former Head of SEO for G2

• An analysis of 520 queries and 42,971 citations in AI Mode and Gemini by Daniel Shashko. This study analyzed cited URLs with embedded #:~:text= fragments. In Gemini and AI Mode, when clicked, these citations take you exactly to the sentence that was cited in the AI answer (and that sentence is highlighted). This way, the study analyzed sentences that were used by LLMs to create an answer and cite the sources.

For example, here’s the sentence AI Mode highlights as a partial answer for the prompt “best running shoes for this spring”:

Here are a few practical tips these two studies offer for AI citation optimization:

1. The closer to the top, the better

Both studies align with each other on the most important part: LLMs don’t really like to read. They mostly cite pages that give them answers in the first third of the page.

According to Kevin’s study, 44.2% of all citations came from the top third of the page. The probability of citation dropped significantly after this initial section:

Daniel’s study was very much aligned. Three quarters of all cited sentences were in the first 50% of the page, with the 50% of all sentences appearing in the first third of the page. An interesting note from this study is that LLMs seem to like the very first paragraphs less than the fursth 40% of the page:

The obvious takeaway here: make sure to answer the most important underlying question in the first third of your page. Get right to the point.

Those FAQs you include at the bottom of your 2000-word article may not be that impactful.

2. Write in “Atomic Facts”

Another interesting concept Daniel’s study has introduced is called “atomic facts”. Daniel has found that LLMs prefer short sentences that carry a lot of meaning:

• In his study, 6–20 words covered ~92% of everything that got cited

• LLMs tend to cite full sentences

According to Daniel,

In RAG systems, an atomic fact is a self-contained, single-claim sentence that makes sense on its own. The 6–17 word sweet spot maps directly to this.

For copywriting, this means using a few words to express as much meaning as possible. No long introductions, no unclear and long definitions, no creating descriptions of your products. Get right to the point and get as clear and factual as possible.

Here’s a new free tool that allows you to analyze your copy to see how many “atomic facts” it contains.

3. Make use of lists

This is not the first study showing that LLMs love bullet-point and numbered lists. But it is a good reminder: Use those lists!

4. Am I guaranteed to get cited if I use all those tips?

No.

Danie’s study (as well as a few previous studies) has found very little overlap between citations in AI Mode and Gemini. This means that, while the two LLMs seem to follow the same patterns to pick sources, the outcome remains quite unpredictable.

You can increase your page’s chances of getting cited by using the tactics below, but it is not going to be as predictable as organic rankings.

Also, ranking well in Google gives you much bigger chances to get cited than anything else.

5. Citations vs Answer Visibility

Another important note to make here is that these two studies are looking specifically at LLM citations. While citations may influence an AI answer, making sure your brand is positioned well in the training data is fundamental (and more important) for consistent visibility.

• Organic Google search (as Reddit threads rank for just about any commercial and branded query)

• LLMs (as ChatGPT uses Reddit for training data and frequently cites Reddit threads as sources for answers).

As commonly happens in our industry, most businesses started looking for shortcuts to Reddit visibility.

Here’s what they are doing wrong and why it is inevitably going to backfire:

>>> JOIN us to discuss this LIVE!

1. Posting fake reviews, and the legality of that

Or rather illegality of that….

Here’s how most agencies approach Reddit marketing:

• They buy comments from anonymous accounts recommending a certain brand

• They sponsor new posts from fake customers describing their great experience with the product

Not many businesses realize this is not just unethical, but it is also illegal. FTC made it quite clear:

• Brands cannot post fake reviews, including AI-generated reviews.

• Businesses can’t sell or buy reviews.

• Individuals must disclose in their review if they are connected to a business.

• No selling or buying followers, likes, or views on social media.

There’s an easy form allowing consumers to report businesses that are doing any of the above. It is no joke.

Any agency trying to sell you these services essentially encourages you to break the law.

2. Reaching out to moderators requesting to remove negative threads

This is #1 request from businesses contacting us for Reddit reputation management services: How do we delete those negative threads?

Well, this is a great way to make those mods very angry.

Not only will they likely ban your account from the subreddit, but they will also make the issue public, damaging your reputation even more.

Here’s one example of a huge subreddit making sure businesses that attempt to remove negative threads or sponsor positive reviews are well-known:

After a thorough audit, I can recommend reaching out to mods carefully if both of these conditions overlap:

• The product has changed, and the thread no longer represents the current state of things. Make sure to prepare all the documentation, change log, etc., explaining how the situation has changed.

• The overall sentiment is neutral. Sometimes, some brands are so notorious inside some subreddits that whatever you say will result in the situation getting even worse.

And even in this case, I never recommend asking the mods to remove a thread. It should always be phrased something like “Is there any way to update this thread, as we took a lot of effort in fixing our products to address the listed issues?”

3. Trying the “influencer marketing” approach

Some brands attempt to “hire” well-established Redditors and mods to promote their products on Reddit. This, again, is something that can backfire and cause serious reputation management issues, even when you are open to doing it legally, i.e., allowing them to disclose the affiliation.

Reddit is not like other social media networks you are used to. The path to becoming a mod is very long. You have to be very passionate about the topic to end up a well-known user inside a popular subreddit or a mod.

These passionate people will likely treat any attempt to sponsor their reputation as an insult. And they will likely be very vocal about that.

Doing Reddit marketing right is not just more effective in the long run; it is also the only way to keep your brand safe. Establishing a transparent business entity on Reddit builds trust that no money can buy.

If you are considering marketing on Reddit, ask us how to do it properly!

And it is not just searching… It is also a weird reliance on Google’s indexation and cache.

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About 7 months ago, Aleyda Solis did a test to find ChatGPT citing Google’s search snippet, word-for-word.

A week ago, I did a test to see if ChatGPT reads schema and found that ChatGPT refuses to see updates on the page unless they are indexed by Google. Basically, the steps were as follows:

1. Added a fake company name to a page

2. Asked ChatGPT to find that company name on the page

   1. ChatGPT confidently responded that there was no company name mentioned on that page

3. Requested re-indexation of the page through Google’s Search Console and waited for it to be done

   1. Immediately after it was re-indexed by Google, I used the same prompt, and ChatGPT was able to see the new name right away.

Which version of the page ChatGPT is accessing is a mystery (Google’s cache?), but the reliance on Google’s indexed version is obvious at this point.

Note: When prompted to visit a page, ChatGPT uses a specific bot that is supposed to open a page (regardless of its Robots.txt directives). It is not a search bot. So why does it query Google’s index instead of visiting the page directly remains a mystery.

Another finding from last week was that ChatGPT also scrapes Google’s sponsored results, as it is sending referral traffic from UTMs used only in Google Ads:

And let’s not forget that OpenAI’s browser openly runs on Google search (well, because it is built on Google’s Open Source software:)):

So what does this all mean?

Given that ChatGPT and Gemini are direct competitors, this weird relationship is very interesting to me.

But for SEOs, this means:

• Traditional SEO (technical, content, backlinks) remains not only fundamental but also key to LLM/AI visibility.

• Google is not going anywhere. It seems they have the keys ChatGPT is struggling with.

• Google is better equipped to win this race, unfortunately, as it doesn’t have to rely on third-party indices or data.

• Bing is not good enough (OpenAI tried to use it, but there must have been a good reason why they ended up with Google).

So why don’t ChatGPT citations 100% overlap with Google’s rankings then?

This is one of the more popular arguments among those who try to declare SEO dead. Different studies suggest an average of 30% overlap between ChatGPT citations and top Google rankings (which is huge, in my opinion).

My thoughts:

• These studies don’t seem to take “fan-outs” into account. ChatGPT doesn’t search for prompts or obvious underlying queries. It fans out to what it needs more info on (and pulls the rest from the training data).

• Let’s not forget that OpenAI has lots of partnerships with publishers and may pull citations from those. I once went down a rabbit hole of tracking down unindexed pages to OpenAI partnerships and succeeded.

SEO for AI / GEO / AEO strategy is not all about optimizing for Google. I am not trying to make this point, though. But, so far, Google seems to be the fundamental part of it.

Let me know if you’d like me to talk to you about other parts of it.

I had one clear vision: Create a space for clutter-free updates on what is going on in the SEO for AI / GEO / AEO industry that will cut through the noise.

Here’s the subreddit itself: r/SEO_for_AI

To be sure, I have the whole team of Reddit experts who are much more knowledgeable than I am and manage subreddits and Reddit marketing campaigns for a variety of clients.

But I was determined to do it myself.

I strongly believe that a manager/director/founder needs to do something personally to be able to better relate to and manage a team of professionals.

>>>> Please JOIN ME to discuss this Reddit experiment LIVE on LinkedIn

Here’s what I learned from the process:

1. It damn works for capturing rankings and getting cited by LLMs

If you allow your subreddit to grow organically and naturally, you will soon notice it ranking everywhere. It doesn’t happen quickly because Reddit does have a “sandbox” for new subreddits. You need to build trust with both Reddit and Google by consistently providing true value.

After about 5 times of managing my subreddit, I started noticing it show up in Google (Reddit stacks):

In AI Overviews:

In People Also Ask boxes

2. It is hard and takes time (especially if you ban spam) + consistency

It may not take years (judging from my experiment), but it is going to take a lot of patience. In the first couple of months, you will likely be the only one talking there, earning trust.

If you remain consistent and focus on providing value, the real magic will happen when Reddit starts showing you in other people’s feeds. It is much more valuable than ranking, to be honest, because those Redditors will engage and subscribe (not just read, which is what most Google searchers are coming for).

Ranking may and will fluctuate. Reddit’s organic visibility will be consistent (as long as you remain active), driving engaged members of your community.

Then you will see spam arriving. And here you will have a tough choice: Allow it (and boost your subreddit’s engagement) or remove everything that is fake (trust me, as a mod, you will quickly learn to tell one from the other.

I chose the first option and ended up vigorously removing threads that had one purpose: To get a self-serving mention either in the post or in comments. I started banning members who repeatedly attempted to do it again.

3. It takes REAL expertise

Unless you have a deep understanding of the topic through actual experience and expertise, it won’t work. You cannot just share links or fun/filler content and hope that you will be able to succeed.

That’s why, when managing clients’ subreddits, we always insist on a dedicated person from the company who actually knows the topic well.

4. Most competitors give up before they see it work

This is good news.

I saw lots of people trying to replicate what I was doing. Most of them already gave up on trying because of how hard work it requires to yield any meaningful results.

I talk about Reddit a lot btw:

• How to Do Reddit Marketing without Making Enemies

• 5 Reasons to Create a Dedicated Subreddit

• Reddit as a Gateway to Google Search (and ChatGPT): Do’s and Don’ts

• How to Manage Your Brand’s Reputation on Reddit

• Reddit OWNS the Bottom of the Sales Funnel (And Businesses Fail to Do Anything about That)

Let me know if you need help with Reddit!

>>> JOIN US to discuss this topic LIVE on Linkedin

Meta posted an SEO lead position looking:

…To enhance our web marketing footprint globally. As SEO Strategy Lead, you will be responsible for increasing search visibility, traffic, and conversions across Meta’s B2B and B2C web properties. You will lead and manage a team of SEO specialists, collaborating with various cross-functional teams and leaders to integrate SEO practices across all Meta products and apps

Open AI posted a content strategist position:

We are seeking a full-funnel ‘growth athlete’ with deep expertise in SEO, web strategy, and CRO to help scale ChatGPT consumer and business growth initiatives

Anthropic is now also looking for an SEO lead to:

define and execute the technical SEO roadmap, drive site experimentation and conversion optimization, and make strategic recommendations that shape how we invest in organic growth [and also] define our strategy for emerging search experiences like AI Overviews and answer engines.

What does this mean?

Well, there’s one main thing right on the surface here: The three biggest corporations that drive AI technology and innovation totally recognize the importance of SEO for growth and product discoverability.

I am sure, they all know that organic discoverability is going to change, and like I said many times, SEOs are going to be the only ones figuring this change out. We’ve (SEOs) have been bridging the gap between machine thinking, sellers, and consumers for years now.

But there’s much more into this: All of these companies get it. SEO is no longer an island. It should be integrated into the organization. SEO needs to be part of conversion rate optimization, design, product development, etc.

If there’s one single factor that has driven SEO change, it was this. In most companies, an SEO department was a tight group of weird people, and no one knew what they were doing.

SEO has matured beyond that. My audit kick-off calls all start with “describe your brand’s value proposition and explain your product positioning.”

Wil Reynolds said it best:

Your job as a marketer is going to be more than ever looking for information that can help AI know who you are that your company has buried somewhere and surfacing that. Become a scavenger, find valuable info and get it published and take more ownership of your brand citations.

SEO is no longer about strings of keywords and backlinks (both are still important, but secondary). It is much more cross-channel and product-driven these days. If you are still looking for SEO “to optimize your pages for keywords”, you are just a little behind!

Ask me how SEO for AI can work for your business.

Many SEO experts are still trying to apply old, convenient metrics to AI visibility by measuring:

Traffic from LLM platforms

While it is still a useful metric to monitor, focusing on it is highly limiting because AI answers are not designed to send clicks. They give conclusive and satisfying answers that often remove the need to click anything.

>>> JOIN us to discuss AI visibility LIVE on LinkedIn

In many cases, the solutions or best options listed in AI answers are not even linked (so there’s no referral traffic possible). Or sometimes they are linked to Google search results for further research:

Traffic is no longer representative of the level of visibility. Your product can be listed as a top option (and trigger a lot of conversions) without ever generating any direct clicks from AI answers.

Rankings in AI answers

AI answers tend to list the best options as lists. Logically, the higher your product comes up in a list, the higher the probability that a consumer will choose it. So many business owners want to know and track these rankings, aiming to be listed more and higher.

While some AI visibility tools promise to track your AI rankings, it is, unfortunately, not possible. LMM answers are highly inconsistent. A study by Sparktoro (shared by Rand Fishkin) shows that LLMs are very likely to list various brands when using the same prompt again and again.

What should be tracked instead?

Here are other metrics we need to start focusing on more when tracking and measuring AI visibility:

1. “What LLMs know about me vs my competitors.”

When answering prompts, LLMs refer to what they already know about the world. Even if they search, they will likely turn to their pre-training data to decide what to search for.

The important question should be, “How much LLMs know about your business vs how much they know about your competitors”. An even more important question is, “Where LLMs get it wrong.” This is about identifying outdated, false, or missing information that needs to be addressed (on- and off-site)

You can prompt various platforms to find these gaps of knowledge in LLM training data.

AI visibility analytics platforms (like Profound or Peec AI) can help you run and monitor these prompts on a regular basis.

2. Most impactful citations

Gen AI platforms perform live searches more often these days. They may search Google, Bing, or Brave Search (so organic search visibility is still very important for AI visibility), or they may refer to sources they know (like Reddit, their current partners, etc.).

Citations that influence AI answers are likely to be very inconsistent (just like product rankings inside answers) because AI platforms fan-out to always different search queries. So, chasing every citation you come across is not doable.

However, there are “most influential” URLs you tend to come across from prompt to prompt. This is what you need to focus on to:

• Try and get included

• Fix any misinformation there (if you are already included). In most cases, incorrect training data positioning comes from misconceptions in cited URLs.

AI visibility platforms can collect these most cited sources for you and even report if your brand is included:

[Peec AI reports how many times each URL was cited across all your tracked prompts]

3. Branded search variety, volume, and clicks

There’s an interesting cycle at play here:

• Frequent brand mentions get you included in more gen AI answers. We see it all the time by running digital PR campaigns for our clients. Here’s what we do. Fresh brand mentions “remind” LLMs of your businesses and build trust. So you want to see your brand mentions consistently increase.

• If your brand is included in more LLM answers, more people will search for it (because it is often unlinked). So if you are doing something right, you will see more impressions for your branded searches. So your branded search is a success metric to track.

You can use Search Analytics to do that. Just create a new filter in the “Performance” report to see data for your branded queries.

[Clicks and impressions for branded search, reported by Search Console. The growth of both likely signals of higher AI visibility]

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It was met with a lot of criticism from organic search professionals (we will discuss why), but there are a few cool and actionable tips there that reinforce what I (and many others) have been saying for years.

SEO vs GEO vs AEO

This is the first official guide implementing some new acronyms. While it is a good move, the guide did not do a good job distinguishing between the new ones, or explaining why we need those. According to Microsoft:

• SEO = Keyword optimization

• AEO = Answer Engine Optimization (easy answer retrieval)

• GEO = Making your brand and content trusted by LLMs

That’s a lot of acronyms for something we have been doing as “SEO” for years:

• AEO is pretty much featured snippet optimization (we have been calling Google an answer engine since about 2014, and I have yet to see a clear explanation of how LLMs made those tactics any different, except for a new term - chunking - which also isn’t bringing anything essential new, simply calling the old good “make everything short, clear and factual” a new name)

• GEO is pretty much EEAT optimization, as many of us already saw it.

Regardless, these definitions can be interpreted as follows:

• AEO = on-page optimization

• GEO = brand positioning.

This does not align with my earlier attempts to make sense of all the various acronyms, but I am ok with adjusting, if needed. We don’t evolve unless we change our opinions :)

An actionable checklist to be more visible

Healthy criticism aside (which I think is good for productive evolution), there are quite a few useful things in the guide, none of them being new:

• You need to be more descriptive and intent-driven when optimizing your product pages (both on-page and in your product feeds). Keywords are no longer enough. You need to consider use cases and unique product/brand differentiators, i.e., “best for”.

• Clear, bold claims work only if you can prove them. If you claim your product to be the best in a particular category, make sure to add why you are entitled to say so. “Best for XXX, according to XYZ”. LLMs are easy to be convinced if you state things clearly, but there’s an added layer of trustworthiness there.

  • Avoid exaggerated or unverifiable claims unless you can prove them by social proof or experts’ statements. “AI systems penalize low-trust language”. To be fair, I haven’t seen this in practice, but it might be something LLMs will be doing in the future.

• Add text where you can - that includes detailed alt text for images and transcripts for videos.

• Use Q&As or FAQs where they help provide more context and easier answer retrieval.

None of that is actually new to SEO, but LLMs are a little less mature and a little more human.

In short, make it as clear and convincing as you can. The way I explain it to clients: “LLMs are just like kids: They are easy to convince, but they follow the path of the least resistance. They won’t recommend you to your users unless your value proposition is very easy to understand and unless it is backed up by experts or social proof.”

There’s a repeated mention of schema, which states that structured markup helps without explaining how. My opinion about schema remains the same here: Use it, use it a lot.

When it comes to AI visibility, we don’t know how exactly LLMs may use schema, but it won’t hurt! And since LLMs turn to traditional search engines a lot, it will help because search engines use structured markup and may convince AI agents to click a rich result.

You can read the full guide here (it is not a lot).

It is funny (and sad) that we are excited to see any official guidelines at this point, even quite minimalistic. But so far, it is the most actionable we have!

Let’s talk if you need more than that.