We Don’t Call Ourselves AI SEO Experts. Here’s What We’ve Learned by Actually Doing It

Search has fractured.

Your customers are not just Googling anymore.

They are asking ChatGPT, scrolling Reddit threads, watching YouTube breakdowns, reading Quora answers, and then circling back to Google with a completely different intent than when they started.

AI is pulling from all of these places to generate its responses, and the brands that show up consistently across that entire journey are the ones getting cited, mentioned, and recommended.

At Snippet Digital, we call this Search Journey Optimisation.

Instead of obsessing over a single Google ranking, we help brands show up across every touchpoint where their audience (and AI) is looking.

We’ve been deep in the trenches of AI SEO for a while now, running experiments on our own brand, Keyword Insights, and on client projects.

We are not here to tell you we have cracked the code.

Nobody has.

But we are constantly testing, measuring, and learning, and we want to share what we have found so far.

Everything below is based on real experimentation.

Some of it has worked brilliantly.

Some of it we are still figuring out.

That honesty is the point.

First, Can We Stop Fighting Over What to Call It?

Before we get into the practical stuff, let’s address the elephant in the room.

The SEO industry has spent the last two years arguing over what to call this discipline. Is it AI SEO? Generative Engine Optimisation (GEO)? LLM Optimisation (LLMO)? AI search optimisation? ChatGPT SEO?

I will be honest. I was part of the problem.

I spent way too long debating acronyms on Linkedin and X, weighing in on whether GEO was more accurate than LLMO, whether AI SEO was too vague, whether we needed an entirely new term to differentiate this from traditional search engine optimisation.

Then I realised something. While everyone was arguing about labels, the people actually getting results were just doing the work.

They were experimenting with how to use AI for SEO, testing what made content appear in ChatGPT responses, figuring out what earned citations in AI Overviews. They did not care what it was called.

So here is where I landed.

Call it whatever you want. AI SEO, GEO, LLMO, generative engine optimisation, AI search optimisation, optimising for ChatGPT.

The label does not matter. What matters is understanding how large language models actually work, how they retrieve and synthesise information, and how to position your brand within that process.

That shift in thinking, from debating terminology to studying the mechanics of LLM optimisation, is what changed everything for us.

Once we stopped worrying about names and started building an actual AI SEO strategy based on experimentation, the results followed.

So throughout this article you will see me use these terms interchangeably. They all point to the same thing: making your brand the one that AI systems trust, cite, and recommend.

No, SEO Is Not Dead. You Actually Need It More Than Ever.

Let’s kill this narrative right now.

Every time something new emerges in search, the “SEO is dead” crowd comes out in force.

They did it with social media. They did it with voice search. And they are doing it again with AI.

The reality is the exact opposite.

To do well in AI search, you need to be doing excellent traditional SEO first. The two are deeply intertwined.

AI systems like ChatGPT and Perplexity do not operate in some separate universe from Google.

They pull from indexed web pages, they favour well structured content, they reference sites with strong topical authority, and they trust sources that already perform well in traditional search.

Think about it this way.

If your site has poor technical health, thin content, no topical authority, and weak backlinks, AI is not going to magically discover and recommend you.

The content that AI cites most often is content that is already well optimised for search engines. Good on page structure, clear headings, comprehensive coverage of a topic, and strong external signals all feed into how LLMs evaluate and select sources.

What AI SEO does is add a new layer on top of that foundation.

It expands the scope beyond Google rankings to include citations in ChatGPT, visibility in AI Overviews, mentions in Perplexity responses, and presence across the platforms AI pulls from.

But without the SEO fundamentals underneath, that layer has nothing to build on.

This is why our approach at Snippet Digital starts with solid SEO. We make sure the technical foundations are right, the content strategy is sound, and the authority signals are in place.

Then we layer on AI specific optimisation. Content structuring for LLM citability, distribution across the platforms AI references, citation building, and source of truth management. One does not replace the other. They work together.

The real challenge is not whether SEO still matters. It is attribution.

The Attribution Problem (And How to Start Solving It)

Here is where things get properly tricky.

Traditional SEO has clear attribution.

Someone searches on Google, clicks a result, lands on your site, and you can trace that entire journey in Google Analytics. With AI search, that chain breaks.

When someone gets a recommendation from ChatGPT and then types your brand name directly into Google, that shows up as a branded search or direct visit.

When someone reads an AI Overview that mentions your product and then visits your site later, there is no referral data tying it back to AI.

The traffic is coming, but your analytics cannot tell you where it originated.

This is the single biggest frustration we hear from clients and other marketers.

The results are there, but proving it to stakeholders feels impossible.

But there are ways to start solving this.

We have been experimenting with several approaches:

Self reported attribution

Add a “How did you hear about us?” field to your contact forms, demo request pages, or post purchase flows with AI search as one of the options.

We have been tracking this across client sites and the data is eye opening. You would be surprised how many people will tell you they found you through ChatGPT or an AI Overview when you actually ask them. We will share a screenshot of this setup below so you can see how it looks in practice.

Branded search lift

If your AI SEO efforts are working, you should see an increase in branded search queries over time. Track branded search volume in Google Search Console and overlay it against your AI citation activity. When we started getting Keyword Insights cited more heavily in ChatGPT, branded searches for “keyword insights” went up noticeably.

The correlation is not proof of causation on its own, but combined with other signals it builds a compelling picture.

AI citation monitoring tools

We use tools that track brand mentions across ChatGPT, Perplexity, and AI Overviews. When you can show a client that their brand appeared in X number of AI generated responses last month for Y target queries, that is a measurable data point even if you cannot tie each one to a specific website visit.

There are hundreds of tools and we have a few here you can pick one that works for you.

GA4 referral tracking

One way to track traffic from AI tools in GA4 is by using a regex formula to analyse traffic source data in an Explore report. There are a bunch of articles on how to do this.

None of these methods are perfect.

Attribution in the AI era is messy and will likely stay that way for a while.

But, combining multiple signals gives you a much clearer picture than relying on any single metric.

The worst thing you can do is ignore AI SEO because you cannot measure it with the same precision as traditional search.

By the time perfect attribution tools exist, your competitors will already be years ahead.

Before We Go Any Further: The Spam Problem

Let’s get this out of the way.

There is a wave of “AI SEO” advice out there that essentially boils down to: generate thousands of articles with AI, publish them at scale, and hope something sticks.

Programmatic SEO taken to its most reckless extreme.

Spammy listicles. Pages that exist purely to game algorithms rather than help anyone.

We understand the temptation. The tools make it easy. But we have seen enough to know that this approach is a ticking time bomb.

Google’s spam policies are catching up fast, and AI systems are getting better at identifying low quality, repetitive content.

More importantly, it does not build anything that lasts.

You might see a short term traffic bump, but you are building on sand.

Dejan wrote a great article about this and how Google and other companies might approach this problem.

Here is a quote from the article.

My prediction: Google will have a test-ready classifier within six months and a production version within a year. They’re historically very responsive to public embarrassment, and the volume of self-promotional content flowing through AI Mode answers right now is genuinely embarrassing for a company that spent two decades building webspam defences. – Dejan

Our philosophy is the opposite.

We would rather publish ten pieces of genuinely excellent, deeply researched content than a thousand hollow ones.

Every article, every Reddit comment, every brand mention we help create has to add real value.

If it does not pass the test of “would a real person actually find this useful?” then it does not get published.

This matters more than ever in the AI era because LLMs are increasingly trained to identify and deprioritise thin, repetitive content.

If you are asking yourself is AI generated content good for SEO, the answer is nuanced.

AI generated SEO content can work, but only when it is treated as a starting point that gets heavily edited, fact checked, and enriched with genuine expertise.

Purely machine generated output published without human oversight is a liability.

The brands that win long term are the ones producing content that AI systems genuinely trust as authoritative, and you cannot fake that at scale.

Detailed, Outcome Focused Content Wins

Forget your 1,000 word blog posts. That era is dead.

When it comes to AI search visibility, depth and accuracy win every time. Your content has to be extremely detailed, factual, and outcome based. Write with the mindset that it could be a standalone guide.

This is the foundation of any effective ai content strategy for the AI era.

AI models and users reward comprehensive, structured information that actually solves problems, not filler paragraphs written for word count.

To see what I mean, compare these two articles covering the same topic. First, read this: https://thruuu.com/topic-cluster-content-strategy/free-keyword-grouping-tools/

Now read this: https://www.keywordinsights.ai/blog/keyword-clustering-tools/

Can you see the difference?

Recency Matters More Than You Think

I cannot stress this enough. Fresh content wins.

I have tested this across multiple queries, and content that is newer almost always gets more visibility in AI search. That does not mean you should blindly change your publish date or stuff updates with fluff.

Instead, make meaningful monthly updates where possible. Refresh examples, tweak data, and add context. The key is to signal to both Google and AI systems that your content is alive and maintained.

Distribute the Hell Out of Your Content

You cannot just publish and pray anymore.

Break your content into bite sized, high value snippets and distribute it across YouTube Shorts, TikTok, LinkedIn, and Twitter. Go where your audience actually is.

Visibility is not just about ranking.

It is about presence.

The more your ideas and brand surface across platforms, the higher your chances of being cited or mentioned by AI systems.

This is core to how we think about Search Journey Optimisation at Snippet Digital.

Every platform your audience touches is a potential citation source for AI.

YouTube mentions and branded web mentions are the top factors correlating with AI brand visibility across ChatGPT, AI Mode, and AI Overviews.

If your content only lives on your website, you are leaving an enormous amount of AI visibility on the table.

The Reddit Challenge: Why Authentic Engagement Is the Only Way

Here is something we have been experimenting with heavily: Reddit marketing for AI visibility.

The relationship between Reddit and SEO has shifted dramatically. Reddit’s organic visibility on Google has exploded by roughly 1,300%+ over the last two years. Google signed a deal worth over $60 million to access Reddit’s full archive. And AI systems, particularly ChatGPT and Perplexity, pull from Reddit threads constantly when generating responses.

So getting your brand mentioned in relevant Reddit discussions is incredibly valuable. But here is the hard truth: Reddit is one of the most difficult platforms to do this on without getting absolutely destroyed.

Reddit communities have zero tolerance for self promotion. Drop a link to your product in a thread without context and you will be downvoted into oblivion, reported, and potentially banned.

The community can smell marketing from a mile away, and they are ruthless about calling it out.

The only approach that works is genuine engagement.

That means spending time in subreddits, answering questions with actual expertise, contributing to discussions without mentioning your brand, and building a reputation as someone who adds value. Only then, when someone asks a question your product genuinely answers, can you mention it naturally and have it land well.

We have learned this through trial and error. It is slow work. It is not scalable in the way most agencies would like.

But, the payoff is enormous because those organic, upvoted mentions in Reddit threads become the exact content that AI systems reference and cite.

A single well received Reddit comment recommending your product can end up in thousands of AI generated responses.

This is why we take a community first approach with our Reddit work.

No bots, no fake accounts, no astroturfing. Just real people having real conversations in communities they genuinely participate in.

Only Create Listicles When They Make Sense

Listicles still work, but only when the intent demands it.

Do not force “Top 10” articles just for the sake of it.

AI models seem to recognise when list formats make sense contextually. For example, reviews, comparisons, or curated recommendations perform better than generic “best of” lists.

If you want to get a product recommended by AI, then work on creating lots of product modifier based content around it and distribute it via different channels.

Build Proper Topic Clusters and SEO Topical Authority

This is still one of the most reliable long term strategies.

If you are targeting something like “keyword clustering tools,” create 8 to 10 related supporting articles around it such as “best,” “reviews,” “how to,” “comparison,” or “top tools.”

Interlink them naturally, not mechanically. The goal is to build a network of authority within your topic. And yes, this is literally what Keyword Insights helps you do better and faster.

Our core page:

https://www.keywordinsights.ai/features/keyword-clustering/

Supporting pages:

https://www.keywordinsights.ai/blog/keyword-clustering-tools/

https://www.keywordinsights.ai/blog/keyword-clustering-guide/

Let’s say you run a project management SaaS.

Writing about “10 ways to stay productive at work” might sound related, but it is too broad and generic. It does not strengthen your topical authority because anyone from a lifestyle blogger to an HR site could cover that.

Instead, write something like “How to use project management software to plan your team’s week more efficiently” or “The workflow templates high performing teams use to manage complex projects.”

Both stay tightly aligned to your niche, reinforce your product’s relevance, and tell search engines and AI systems exactly what space you own.

I wrote on how to build topical authority in SEO and how it’s your moat in against AI search.

Citation Building: The New Link Building

AI search heavily references brand mentions, even unlinked ones. That means any serious ai seo strategy needs to move beyond just link building.

Traditional link building focuses on backlinks for domain authority. Citation building for AI is fundamentally different. It is about creating a consistent, authoritative brand presence across the sources that AI systems trust and pull from.

Here is the stat that changed how we think about this: brands are 6.5x more likely to be cited in AI responses through third party sources than through their own domains.

Domains with profiles on platforms like Trustpilot, G2, and Capterra have roughly 3x higher chances of being chosen by ChatGPT as a source compared to those without.

What this means practically is that your brand needs to exist everywhere the conversation is happening.

Guest posts, industry publications, review platforms, podcast appearances, expert commentary. Not for the backlink (though that is a nice bonus) but for the citation.

Every authoritative mention of your brand paired with a relevant keyword (Think of entities) is a signal that AI systems pick up on when deciding who to recommend.

We work on contextual brand citations.

We target mentions that pair your brand name with relevant keywords, even if they do not link directly.

The end goal is simple: when someone asks an AI about your target keyword, your brand should already exist in the conversation across enough trusted sources that the model feels confident citing you.

Source of Truth: What Does AI Actually Know About Your Brand?

This is something most agencies overlook entirely, and it is one of the first things we do with every client.

Before we start building visibility, we need to understand what AI already knows (and gets wrong) about a brand. We run what we call a source of truth audit. We ask ChatGPT, Perplexity, Gemini, and other AI systems direct questions about the brand. Who are they? What do they do? What are their products? Who are their competitors?

The answers are often surprising. AI might be pulling outdated information from Crunchbase. It might be referencing a years old press release that no longer reflects the brand’s positioning. It might be confusing the brand with a competitor or missing key products entirely.

Once we have mapped these gaps and inaccuracies, we trace them back to their source. Where is the AI getting this information from? Is it the brand’s own website? A Wikipedia entry? A third party directory? An old news article?

Then we fix it at the source level. That might mean updating the brand’s own site content to be clearer and more structured for AI comprehension.

It might mean correcting a Crunchbase profile, updating industry directory listings, or creating new content that establishes the correct narrative across multiple authoritative sources.

This is foundational work.

There is no point building AI visibility if the information AI is sharing about you is wrong.

You have to get your house in order first.

The Real World Example: How We Got Keyword Insights Featured

Back in 2024, one of our competitors wrote an article that ranked number one for “keyword clustering tools” You can see it here: Thruuu’s article.

We were bouncing between positions 6 and 7. Not terrible, but not where we wanted to be. We also were not showing up prominently in AI search.

So I decided to run a full blown test. I created a comprehensive, highly detailed guide: Keyword Clustering Tools — Full Breakdown.

I expected Google to replace our product page with this article. That did not happen. But what did happen was more interesting. The article started getting heavily cited in AI search results, and since it linked back to our product page, that page started climbing.

We moved up to position 3 on Google.

Meanwhile, our competitor’s page disappeared from AI search entirely.

If you compare the two, you will immediately see why.

Ours is deeper, better structured, outcome based and genuinely useful. (Maybe a tad biased)

The Power of Recency (Again)

For months, we dominated AI search for that keyword. Then, a new competitor published their own version in September: AnswerSocrates’ article.

Now, they are being cited alongside us in AI results. Why? Their article is newer and uses a very similar approach and structure to ours.

That is it.

Also the AI SEO hacker/Expert Metehan found this in the ChatGPT configuration:

use_freshness_scoring_profile: true

It just proves that you cannot sleep on your content.

Even if you are ranking or being cited today, someone else can easily outdate and outrank you tomorrow.

They also started showing up on ChatGPT for the same target query.

My next move was obvious. Update the article, add new tools, fresh comparisons, and push it live again. Plus seed more articles on other websites.

So, I looked for all other tools that provided Keyword clustering solution, bought a subscription/credits and used the exact same approach to test, update the article with new results.

Guess what?

We’ve outranked the competitor on Google and our article is cited and ranked at the top.

To prove this point further, Our other competitor has copied our format and was able to outrank us on Google.

So, as you can see you cannot sleep on this and it’s non stop work.

When Competitors Mention You, You Still Win

Even when competitors mention you in not so positive light, they can accidentally help you.

Case in point: Thruuu’s Best Keyword Clustering Tools post.

They took a swipe at us but still mentioned Keyword Insights. That is a brand citation in context, and it is a win in my book.

How they portrayed Keyword insights

How we actually look.

Distribution Example

I create different versions of my main article and distribute them on different channels.

For example: https://www.linkedin.com/pulse/8-best-keyword-clustering-tools-2025-tested-compared-mohanadasan-trdff/

Yes, it is a little bit of parasite SEO but in my opinion, this serves as a reinforcer to our main article.

End of the day these articles obviously position our tool favourably. But, I’d argue by putting all of our competitors via real world testing with the same data set and doing a non biased assessment we have proven that our tool is superior for x reasons.

Lily Ray Wrote an article about Google cracking down on self promotional articles and we expected this article to take a hit, but it didn’t. So, we know our method is likely working and not seen as spammy or self promotional. (Touch wood)

How We Actually Measure All of This

Traditional ranking reports only tell part of the story in the AI era. A brand can be invisible in Google’s top ten but heavily cited in ChatGPT and Perplexity responses. Or vice versa.

We track AI visibility across multiple dimensions: citation monitoring across ChatGPT, Perplexity, and Google AI Overviews; brand mention frequency in AI generated responses; share of voice analysis against competitors in AI search; and tracking which sources AI is pulling from when it mentions (or does not mention) a brand.

This measurement layer is critical because without it you are flying blind. You might think your AI SEO efforts are not working when actually your brand is being cited in thousands of AI responses you cannot see in traditional analytics. Or you might think everything is fine while a competitor is quietly overtaking you in AI visibility.

We provide clients with monthly reporting that covers both traditional search performance and AI citation performance side by side, so the full picture is always clear.

You can read more about our approach on our AI SEO Services page.

The Honest Truth: Nobody Has All the Answers Yet

We want to be completely upfront about something.

The future of SEO with AI is changing faster than anyone can fully keep up with. What works today might shift in three months.

The algorithms behind ChatGPT, Perplexity, Gemini, and Google AI Overviews are constantly being updated, and the ranking factors for AI citations are not documented anywhere the way Google’s ranking signals have been studied over decades.

We do not claim to have a magic formula.

What we do have is a disciplined approach to experimentation.

We test hypotheses, measure results, document what we find, and iterate.

We share our findings openly (this article being a case in point) because we believe transparency builds more trust than pretending to have all the answers.

What we can say with confidence is that the fundamentals hold.

Quality content, genuine authority, consistent brand presence across trusted sources, and authentic community engagement are the patterns that correlate most strongly with AI visibility.

The brands that invest in building real value rather than gaming systems are the ones that keep showing up, regardless of how the algorithms change.

Final Thoughts

AI search optimisation is not just about SEO anymore. It is about maintaining an active presence both on your site and across the wider ecosystem.

Keep your best content detailed, fresh, distributed, and cited.

Build authority within your niche. And above all, do not sit back once you have “won” a keyword. The game resets every month.

This is the new reality of AI driven search. And it is a lot more fun if you stay ahead of it.

If any of this resonates and you want to explore what an AI SEO strategy could look like for your brand, we are always happy to chat. No hard sell, just an honest conversation about where you are, what the opportunities look like, and whether we are the right fit to help. Book a free strategy call and let’s figure it out together.