If you find value in my newsletter and want to support the work that goes into it consider —> [☕Buy Me a Coffee☕]💡 Want more from me? [SEO Strategy Course] | [Build Your Own SEO Tools (with Python & Agentic AI)] | [Premium SEO Mastermind]

Alternatively you can become a paid subscriber

Intro

We talk a lot about optimizing for better visibility in AI, and there’s tons of content being shared, but one of the questions I get asked in my community calls is how to understand where you stand today in AI?

Personally, every once in a while I have someone reach out to me, and they say they found me from an LLM platform.

I just don’t share those very often so not to jinx it 😄😄😄

Anyways, for today I decided to put together a simple process for you to understand where you stand today in your AI visibility in AI Overviews.

Note: this is not an audit to find fixes, it’s an audit to observe how and when do LLMs cite you, and recommend you.

I did that before

I recently created the data study “Who Does Google Trust in AI Overviews for SEO Advice?”

and it all started with a simple data export of a bunch of related keywords (thousands)

Then I did some cleanup, used an API to get AIO for each of the keywords, and analyzed those answers in bulk.

I really recommend you check out this study so you can imagine what you can do if you follow my process. Works wonders when you begin with the end in mind.

Let’s get to it

So there are two thing you want to do:

1. how often, and in what situations is your brand cited and/or mentioned

2. who does AIO cites and mentions in general (competitor analysis)

The steps are simple.

The keywords list

First, pull a list of keywords that you want to analyze your visibility for. You can get those keywords from GSC, or you can get them from any of the third-party SEO tools.

Once you have your list looking something like this:

The cleanup

If you pulled a large list of keywords, it’s always a good idea to sift through it to remove any noise. For example, you may want to remove competitor brand names (or not depending on what keywords are important to you to analyze), keywords with Non-Latin letters for example. API calls can be expensive if you’re doing them for a large number of keywords, so cleanup is important to reduce the cost, but also, bad or noise keywords will reduce the quality of your report.

The best way to do this cleanup is a mix of both manual checks and using claude or chatgpt for more large scale automated changes. But always ask them to show you examples of any keywords they removed. Double check, double check, double check.

The API calls

There are a lot of SEO APIs out there, and I have been using SERPapi and the good news is that you can create a free account and get 250 free search per month (not sponsored)!

250 searches are not a lot, but can be a good place if you’re working on a small audit for your website.

I created this free SEO python script for you, once you run it, it will ask you for your API key, which you can get from SERPapi as I mentioned above. Then it will ask you for a CSV that has your keywords. It needs to be called “sample_keywords” and the keywords are in the first column that’s called “keywords” all lowercase. here’s the sample input and output file that I used for the purpose of this blog.

For each of the keywords on your list, the output will look like this

You have the keyword, the AI Overviews, and all the URLs in serps as well. Looks good right?

Note: before running the API on thousands of urls, make sure you run the code on a small set of keywords to test it’s doing what you would like it to do.

The analysis

This is what separates men from boys, or great SEOs from just SEOs. Using chatgpt or claude (I personally used claude code) I would ask it to analyze this output data. For every analysis it should save the output, as we will need to create an HTML report in the end (similar to the report I created).

Note: If you think this is a quick and easy task, you’re probably doing it wrong. You need to double- and triple-check the output for every question before moving on to the next one.

I also recommend asking Claude or ChatGPT to write code to analyze the data, rather than having them analyze the dataset directly. This will give you more consistent results, save you money, and, perhaps most importantly, make it much easier to audit the analysis when you understand exactly how the results were generated in the first place.

Some of the analysis questions you can perform:

• How often was my brand cited compared to my competitors (provide the list of competitors and of course your brand name)

• How often does being cited or mentioned overlaps with ranking and in what positions.

• When your brand is cited, what was the sentiment? perform a sentiment analysis for each time your brand was cited or mentioned in AI Overviews to understand was is cited in positive, negative or neutral tone.

• What type of queries trigger my visibility (is it informational? is it when a specific feature is mentioned, etc…)

• What type of queries are we lagging in visibility (same question as previous one but looking to the other half of the glass)

the sky is really the limit… and this is where you shine!

Finally combine all this data into an hmtl report because it’s easier to format and you have a very cool report that you can use to drive optimization initiatives in your organization.

And That’s a Wrap (Almost 😄)

I may have made this task sound simpler than it actually is, I know. But that’s not necessarily a bad thing.

Well… I hope I made it simple enough for you to test out and have fun with!

That’s that for today folks and see you in the next newsletter!

Support the Riddler!

• Sign up for my newsletter if you’re not already. (Pssst, you can also become a paid subscriber)

• Share the newsletter and invite your friends to signup. Help me reach 2k signups by end of 2025 please 🙂

• Provide feedback on how I can make this newsletter better!!!

• Buy me coffee.

• If you’re an SEO tool or an SEO service provider, consider sponsoring my newsletter. I’m also open to other partnership ideas as well.

Disclaimer: LLMs were used to assist in wording and phrasing this blog.

Hello Riddlers!

📌 If you find value in my newsletter and want to support the work that goes into it consider —> [☕Buy Me a Coffee☕]💡 Want more from me? [SEO Strategy Course] | [Build Your Own SEO Tools (with Python & Agentic AI)] | [Premium SEO Mastermind]

Alternatively you can become a paid subscriber

Intro

I run monthly live SEO townhalls to chat about anything and everything SEO, you can also bring your own questions or tips that you’d like to share. You can watch recording of previous sessions here, or signup and join us for the next one!

These sessions always inspire me, and last time someone asked, “How do you learn SEO in 2026?” That really got me thinking...

We’ve come a long way. SEO has evolved into a vast ocean that requires continuous learning if you want to keep sailing (such a dramatic analogy, right? That's totally me, not the AI helping me write this post 😂).

AI is also a big part of this evolution, so I thought it was a great question to answer in this newsletter. So, hold tight!

What is SEO today?

First, I want to set the stage to what learning SEO includes today and the areas of knowledge you should pick up. I, by no means intend to overwhelm you, we are all still learning. But it’s important to begin with the end in mind.

SEO imo covers a lot more area than we used to. Auditing reddit and finding brand interaction opportunities for your social team, or auditing your YouTube Channel and optimizing the content and descriptions, not just to rank on YouTube but also to rank those videos better in search, and get your brand cited in AI answers using those videos (YouTube gets cited 25% of the time in AI answers).

You may be wondering at this point… OMG do I need to learn all of this? not right away… you’ll build your knowledge overtime, with every audit and every client and every new SEO article you read… but you gotta cover the basis.

1# Cover the basis

People in this industry would eat me alive if I said anything before saying this: the fundamentals are still the fundamentals. If you want to learn SEO in 2026, you still need to master many of the same concepts you had to learn years ago.

Now that I’ve got that out of the way, here’s what I recommend:

If you can build your own test website, please do. It costs little more than a domain name and about $4/month for GitHub, and you can build your own website from scratch using Claude Code. This is the best learning environment—better than any course I can recommend.

If you don't want to build a website, find a small website you'd like to audit instead.

Next I recommend you go through Google’s SEO Starter Guide. As you read and learn, keep going back to your website and apply what you've learned.

For example, the documentation talks about the site: search operator (e.g., site:wikipedia.org). Go try it in Google Search and see what happens.

Don’t understand something? The good news in 2026 is that you can ask ChatGPT, or join one of the many SEO communities and ask your questions there. I also run an SEO community, apply to join here.

In my opinion, Google's documentation is the best place to start. If you're looking for something more comprehensive that will set you up well, I'd also recommend the SEO specialization certificate on Coursera. By the end of it, you'll have the knowledge expected of a junior SEO.

2# Quality content

Google recommends creating “helpful content”... but what exactly is helpful content?

One of the best places to start is Google’s own “Search Quality Rater Guidelines: An Overview”

I highly recommend reading it and creating your own content audit checklist as you go. It’s a great way to turn what you’re learning into something practical that you can reuse.

You can also upload the document to NotebookLM. It can generate a podcast based on the file, and you can ask questions about the document and get answers grounded in its content.

3# Uncle Tom

What about doing SEO for platforms like ChatGPT and Claude?

Well, some people call this GEO...

And if you haven’t heard, using the term GEO is very inflammatory for some people in the SEO industry. Is SEO the same as GEO? Is that even the right question? The debate goes on and on...

I don’t really get into that debate anymore. Call it whatever you want—you can call it Uncle Tom for all I care. 😂

I highly recommend you devour this resources to get on top of this field:

• The iPullRank AI Search Manual

That’s it. That’s my advice!

4# Signup for the right resources

LinkedIn is great, but newsletters are even better. Here are a few newsletters I recommend. I’m not affiliated with any of them (except, of course, my own 😉).

1. SEORiddler.com: a newsletter by yours truly, it’s not really a beginner level newsletter, but it opens your eyes to new ideas, and shared actionable tips as well.

2. seroundtable.com: that’s where I go for news, you’ll find every single thing that ever happened any day in SEO there, that’s a given.

3. Mike King’s iPullRank newsletter: big topics, in-depth AI/SEO research, and so many gems in there.

4. Tech SEO Tips Newsletter: this one is by Nikki Halliwell, I had her on my podcast one time and she’s awesome and her newsletter is no less if you want to build a good technical SEO foundation.

5. SEO Notebook by Steve Toth: short actionable tips on SEO and GEO, definitely worth a spot in your inbox.

5# Wash, rinse, repeat

If you feel the resources I recommended above are not enough, you’re right—you need practice. That’s where you truly grow and learn.

Audit more websites. Audit big websites too: Amazon, Wikipedia, CNN, and others.

Learn to find patterns. Every time you use Google, ask yourself: Why is this URL here?

And That’s a Wrap (Almost 😄)

I hope I didn’t overwhelm you—please don’t be! We’re all learning, and anyone who says otherwise is simply not being honest.

Take baby steps, learn as you go, and try to find a mentor who can guide you if you can.

Good luck!

That’s that for today folks and see you in the next newsletter!

Support the Riddler!

• Sign up for my newsletter if you’re not already. (Pssst, you can also become a paid subscriber)

• Share the newsletter and invite your friends to signup. Help me reach 2k signups by end of 2025 please 🙂

• Provide feedback on how I can make this newsletter better!!!

• Buy me coffee.

• If you’re an SEO tool or an SEO service provider, consider sponsoring my newsletter. I’m also open to other partnership ideas as well.

Disclaimer: LLMs were used to assist in wording and phrasing this blog.

Hello Riddlers!

📌 If you find value in my newsletter and want to support the work that goes into it consider —> [☕Buy Me a Coffee☕]💡 Want more from me? [SEO Strategy Course] | [Build Your Own SEO Tools (with Python & Agentic AI)] | [Premium SEO Mastermind]

Alternatively you can become a paid subscriber

Intro

Google has been facing a lot of criticism and, in many cases, deservedly so.

First came AI Overviews. Then AI Mode.

Features that few people were asking for, but Google had to prove it wasn't falling behind in the AI race after OpenAI launched first using the Transformer architecture that originated from Google's own research.

And the data reflects the sentiment.

Since May 2024, searches from people looking for ways to turn off AI Overviews have been steadily increasing. Just facts. The trend peaked around April–May 2026.

Maybe the people actively searching for ways to remove AI Overviews are a minority. But I suspect many more are simply quietly dissatisfied.

You know who else is dissatisfied? Publishers.

I don't think I've ever seen this level of audacity toward publishers. AI platforms are using content they didn't create to train their models and perform live searches, then assembling answers that compete directly with the very sites that produced that content, taking away the clicks those publishers depend on.

Google says it’s putting users first. I’m not convinced.

To me, the goal isn’t just to help users find information really. It’s to keep users inside Google’s own ecosystem for as long as possible. That’s what this is really about.

And let’s not forget...

Google spent years lecturing all of us about E-E-A-T.

Publishers, SEOs, and content creators have been told to create “helpful content” that demonstrates Experience, Expertise, Authoritativeness, and Trustworthiness. We audited pages, rewrote articles, added author bios, cited sources, and jumped through every hoop because that’s what Google said good information should look like.

Then Google turned around and gave us AI Overviews.

A system that has repeatedly produced inaccurate or misleading information.

I could pause here and start talking about OpenAI and Anthropic. They aren’t exactly better when it comes to how they use other people’s content either.

But to keep this conversation focused, I’ll stick with Google today.

I think Google is up for a wakeup call.

Even tech giants can stumble, and history has a funny way of repeating itself in unexpected ways.

A challenging echo system

A lot of businesses have been impacted over the years with Google updates and a lot of websites lost traffic but none of it is equivalent to what we are seeing today.

Reddit is reportedly considering not renewing its $60 million deal with Google, which allowed Google to access Reddit content to train its AI models.

Reddit’s stated concern is that Google isn’t sending enough traffic back to the platform.

That argument is a little hard to take at face value, considering Reddit has become one of the most visible domains in Google Search results. Reddit threads appear everywhere now, often ranking prominently for product reviews, recommendations, and real user experiences.

And then we have publishers. Google said that it “sends billions of clicks to websites every week through AI search.” but also does not provide the data to verify this in GSC, and publishers are seeing declines in their traffic, the traffic they rely on to generate revenue through ads, subscriptions, and other business models.

Hence, a lot of publishers are considering blocking Google.

And just as Google is facing all of these challenges, SerpApi out of nowhere gets a Google lawsuit dismissed.

You see, Google had the audacity to sue SerpApi for copyright infringement because SerpApi was crawling Google.

Yes, you read that right… do not laugh, please. 😂

Google literally crawls every single website on the internet.

At least when SerpApi crawled Google, they weren’t taking clicks and revenue away from publishers.

Justice was served, and the court ruled that there was no copyrighted material to begin with. 😂😂😂

So some users are not happy, publishers are definitely not happy, Reddit is pushing back, and Google SERPs have been declared as non-copyrighted.

My 2 cents: as these incidents continue and more pressure builds on Google, something has to give. Google will eventually have to find ways to compensate publishers… right?

You may say, “Sara, you’re a small content creator. What do you know?”

Fair enough.

But I do know a thing or two from my startup days.

Hear me out.

Once upon a time

Do you remember when Facebook reduced the organic reach of pages from around 25% to somewhere between 1%–5%?

The goal was clear: push more businesses toward paid advertising and increase ad revenue.

But what happened over time?

Content creators slowed down. Pages became less active. The platform became far less engaging and, at times, almost felt like a digital desert.

I remember back in 2015 suggesting that Facebook should allow people to make money from creating great content on pages.

Without active publishers and creators, platforms risk becoming less engaging and less valuable because the content that keeps users coming back depends on those creators.

and turns out, that wasn’t such a crazy idea.

It took Facebook years to realize it, but eventually they started paying publishers and creators to keep producing content.

Facebook paid out nearly $3 billion to creators in 2025. Of those $3 billion in payouts, 60% went to Reels while the rest went to Stories, photos and text posts.

The lesson? Platforms need creators just as much as creators need platforms.

Maybe Google isn’t there yet, maybe they need to go through the same journey as Facebook to realize that. But they will eventually get there, if publishers and creators are not happy, the platform slowly starts to die.

And That’s a Wrap (Almost 😄)

If you’re a publisher, try to navigate this challenging period.

Because there will come a point when Google and other platforms realize that publishers are not just content suppliers, they are essential partners in their success.

And at some point, they will have to find a way to give back as much as they take.

That’s that for today folks and see you in the next newsletter!

Support the Riddler!

• Sign up for my newsletter if you’re not already.

• Share the newsletter and invite your friends to signup. Help me reach 2k signups by end of 2025 please 🙂

• Provide feedback on how I can make this newsletter better!!!

• Buy me coffee.

• If you’re an SEO tool or an SEO service provider, consider sponsoring my newsletter. I’m also open to other partnership ideas as well.

Disclaimer: LLMs were used to assist in wording and phrasing this blog.

Hello Riddlers!

📌 If you find value in my newsletter and want to support the work that goes into it consider —> [☕Buy Me a Coffee☕]💡 Want more from me? [SEO Strategy Course] | [Build Your Own SEO Tools (with Python & Agentic AI)] | [Premium SEO Mastermind]

Alternatively you can become a paid subscriber

Intro

Everyone seems to be angry at Google right now. Just yesterday, I came across the latest piece from The New York Times titled “Google Is Building an A.I. Fence Around the Internet It Once Championed.”

And, of course, even before this article was released, we had already heard statements from Google representatives emphasizing that Google continues to send significant amounts of traffic to the web. (yes Google we believe you 😂 and that’s exactly why you don’t want to show us the proof in GSC 😂)

Just last Friday, Google’s Head of Search, Nick Fox, wrote on LinkedIn that Google is “sending billions of clicks to websites every week through AI features in Search alone.” He added that these AI features were designed with this goal in mind: “We’ve designed our AI features in Search to connect people to websites.” Overall, he stated that Google “continues to send billions of clicks to the web every day through Search” and that people are using Google Search “more than ever.”

Similarly, last year, Google Search VP Liz Reid said that Search was still sending a “relatively stable” number of clicks—again, in the billions—and argued that reports showing declining search traffic relied on flawed methodologies.

The interesting part is that the conversation is no longer just about how many clicks Google sends. A billion clicks can be a very reassuring number until you start asking for the missing clicks data in GSC.

Well, in this sea of pessimism, I might actually have something potentially good news for ecommerce websites.

So buckle up!

First they came for the clicks, now they’re coming for the conversions

Publishers are upset because Google is taking away clicks from their websites, clicks they earned by creating great content and playing by the rules, clicks they need to generate ad revenue.

Ecommerce businesses, on the other hand, may have different concerns: how their products get recommended across AI surfaces and Google’s recent efforts to capture purchase clicks by offering users the ability to complete checkout directly within Search.

Just last year, ChatGPT announced that users could buy directly from U.S. Etsy sellers within chat. And in January, Google announced tools through the Universal Commerce Protocol that allow shoppers to complete purchases directly within AI Mode and the Gemini app.

I can imagine many concerns around this. One of them is that when people purchase directly from your website, they may discover other products they weren’t originally looking for and add them to their cart. Moving the purchase experience to a third-party platform — whether ChatGPT, Gemini, or AI Mode — gives merchants less control over the overall shopping experience.

For many retailers, this could be a significant challenge. The traditional ecommerce experience allows brands to cross-promote products, recommend complementary items, and encourage customers to explore more of their catalog. In a third-party checkout experience, products may be listed and purchased individually, without the same opportunities or control to guide customers toward other items or offers from the same seller.

This could also be seen as another example of what the New York Times article I shared earlier described: “Tech companies have built empires that locked users in and were focused on maximizing profit instead of enhancing public utility.”

So, as you can see, the concern has evolved. First, they came for the clicks. Now, they’re moving toward controlling the conversions by keeping users within their own platforms which raises an important question: how much control will merchants have over the customer journey in the future that Google and other platforms are building?

I can hear you saying… Sara, where’s the Good news you promised?

Quick historical analysis

I’ve been digging into the history of innovation in ecommerce trying to find patterns for an innovation strategy. Here’s one thing I noticed and I’m sure glad I did:

Does anyone remember Pinterest’s “Buyable Pins”?

Pinterest originally launched in-app purchasing through “Buyable Pins” in July 2015. However, the feature was officially retired globally in October 2018. Instead of keeping purchases within the platform, Pinterest shifted toward Product Pins, which redirect users to the retailer’s website to complete their purchase.

Then there was “Checkout on Instagram.”

Instagram launched its in-app checkout feature in March 2019, allowing users to complete purchases without leaving the app. However, Meta retired the feature globally in April 2024, moving back toward product tags that send users to the retailer’s external ecommerce store to complete their purchases.

So historically, we have two examples of major tech companies attempting to own the checkout experience and both eventually moved away from it.

Why?

Because users don’t just want to buy a product; they want to experience the brand they are buying from. They want to understand shipping times and costs, learn the brand’s story, decide whether they trust the company, explore other products, discover promotions, and so much more.

If there’s one thing this history teaches us, it’s that when users have an established way of doing things on a platform - like shopping on the web- changing that behavior is incredibly difficult.

The better opportunity may not be replacing existing habits, but building solutions around them: reducing friction, improving discovery, and making the existing customer journey easier rather than trying to completely reinvent it.

If you’re an ecommerce website, congratulations it seems you are safe for now. Your focus should be on optimizing your platform for conversions, removing any friction and simply making every click to your website count!

And That’s a Wrap (Almost 😄)

History is not boring! It’s actually one of the most fascinating places to look for insights, if you’re open to learning from it.

There’s a lot of negative news circulating as we navigate this AI boom: layoffs, declining clicks, concerns about the future of the web, and even broader conversations around how technology is affecting the way we think.

But we shouldn’t simply give in, passively consume, and accept everything we read as fact… right?

Speaking of being “open to learning”…. that’s a much bigger discussion for another day. There’s so much I want to say about what it takes to build a better SEO industry.

Hopefully. 🙏

That’s that for today folks and see you in the next newsletter!

Support the Riddler!

• Sign up for my newsletter if you’re not already.

• Share the newsletter and invite your friends to signup. Help me reach 2k signups by end of 2025 please 🙂

• Provide feedback on how I can make this newsletter better!!!

• Buy me coffee.

• If you’re an SEO tool or an SEO service provider, consider sponsoring my newsletter. I’m also open to other partnership ideas as well.

Disclaimer: LLMs were used to assist in wording and phrasing this blog.

📌 Join my in my next webinar on Thursday July 16 · 1 PM UTC / 6:30 PM IST where I will be discussing how to navigate the zero click era. Sign up here.

Intro

Google is getting billions of searches every month, but we’re also learning that only 32% of all searches end with any type of click and of those, 66.6% go to the open web (non-google non PPC ads).

We’ve been blaming Google’s AI experiences, and rightfully so. Google, on the other hand, has been trying to soften the blow by saying websites are only losing low-quality clicks from users who would’ve bounced anyway. Just last year, Google’s Elizabeth Reid said AI Overviews drive “higher-quality clicks.”

This year, there’s a different story.

Perhaps more data is now available (like Google needs more data 😂) but Liz said in a recent interview that “the decline [of traffic to publishers] isn’t solely caused by AI Overviews, but rather by broader shifts in user behavior”

So I decided to analyze this statement.

Is it true? because if so, we maybe missing out on so much opportunity, and holding on to optimizing for the wrong type of content.

So buckle up!

As always, I'm going to build the case step by step before getting to my final conclusion.

Platformisation

A recent Reuters study has some very interesting findings.

When it comes to news consumption, the study found that “social media and video networks are, on average across the markets covered, more popular than both TV and owned news websites and apps as sources of news,” and that “people increasingly like to watch rather than read the news, often drawing on a wider range of sources and voices.”

And video content isn’t synonymous with YouTube.

The study shows that:

• YouTube is used by 34% of people for news.

• Instagram follows at 26% and continues to grow.

• TikTok, while starting from a smaller base, is growing the fastest and is now used by 20% of people for news.

• Facebook remains the largest platform overall for news consumption, with 43% of respondents using it, reversing recent declines.

But here’s another interesting question...

Who’s creating all this content?

Not necessarily large, trusted news organizations.

The study found that:

• 27% of respondents globally get some of their news from news-focused creators or influencers.

• 46% get some news from creators of any type.

Why?

Respondents said creators are more entertaining, easier to understand, and more relatable than traditional news outlets.

Ironically, those same respondents also believe creators are less trustworthy and less impartial.

So despite recognizing that creators are generally less trustworthy, people still choose to consume their content because it’s more engaging, easier to digest (likely because of simpler language), and more relatable.

The following chart shows how trust varies across different news sources.

So... is traditional media dead?

Actually, no.

The study found that people are consuming these newer formats alongside traditional news rather than completely replacing them.

Another interesting finding is that more than half (52%) of respondents aged 18–24 now say that social media, video platforms, and AI chatbots are their primary way of getting news.

To me, this tells us three things.

First, user preferences are shifting toward consuming information on social media and video platforms rather than traditional text-based content that ranks in search.

Second, the age of your audience matters. Millennials—and especially Gen Z—are increasingly choosing these platforms as their preferred way to discover and consume information.

Third, people want to hear from people, not necessarily large brands.

Interesting Expertise Content

For so long, our focus has been on creating “helpful content.”

And naturally, helpful content is not always built to be entertaining.

But it seems that to be successful with your content strategy in 2026, and appeal to wider audiences, you need to think about the entertainment factor as well.

Now, Liz Reid didn’t say that exactly. What she said was:

“To the extent that you produce really interesting expertise content, we still see that people are interested in that.”

May I second that?

I’ve been seeing a lot of misinformation in our industry being amplified by the same voices over and over again. And somehow, those voices become very popular.

What’s interesting is that, almost every time I see this content being shared, because it’s entertaining. It’s funny, provocative, or creates a strong reaction.

And that’s the point: attention and trust are not always correlated.

So if your content is not getting the attention or user engagement it deserves, it may be missing that element.

I’m not suggesting you become a clown 🤡. I’m simply pointing out an observation, and it’s up to you to decide whether you want to adapt your content strategy.

But keep in mind: the more intellectually sophisticated your content and concepts are, the narrower your audience will naturally become. And you can be ok with that by the way.

This is not a new finding. It has always been the case.

However, it may be more visible than ever today because users have an endless number of sources competing for their attention.

Content Length

Liz is also arguing that:

"To the extent that you might just read an AI review and you wouldn’t click, you might have previously just read the headline and not clicked through… You were going to go spend 10 minutes reading the article, you’re probably not going to decide that an AI Overview is a substitute for the 10-minute article."

She attributes this to the fact that sometimes people just want a quick answer—a sports score, for example—and they were never going to read the full article anyway.

So, according to this argument, AI Overviews are not necessarily taking clicks away from publishers. People will still click when they want something beyond basic information: an in-depth analysis, a unique perspective, an opinion, or expert commentary.

Ok Liz, but here’s the thing...

AI Overviews can also summarize those unique viewpoints and opinionated analyses. So that argument isn’t necessarily a strong defense for Google either 😂

However, this does point us toward a bigger question.

At some point, we have to face reality.

And reality says: people are consuming less long-form content.

As dramatic as this title from The Atlantic sounds “The End of Reading Is Here”,it doesn’t feel entirely disconnected from what we’re seeing.

Research at the University of California, Irvine, highlights how our attention patterns have changed over time. By tracking digital activity, researchers found that the average time spent on a single screen before switching tasks dropped from around 150 seconds in 2004 to approximately 47 seconds today.

The reality is that people’s attention is becoming more fragmented. With constant notifications, infinite scrolling, and an endless supply of content competing for attention, users are increasingly looking for faster and easier ways to consume information.

That’s why short-form answers like AI Overviews, as well as alternative discovery platforms like social media and video networks, are becoming increasingly attractive for quick and passive information consumption.

AIO and Few More Things

Yes AIO is taking clicks away, but also we need to acknowledge that people are preferring video content, shorter content (a lot of the times), content from creators and social media, content that makes them smile or laugh 🤷‍♀️

That’s the reality of where we are today.

And while I will remain a strong supporter of long-form content, I don’t think the answer is to ignore these patterns.

My recommendation is to branch out.

Take the valuable insights, research, and expertise from your long-form content and repurpose it into different formats and distribute it across different platforms.

And That’s a Wrap (Almost 😄)

Next time someone asks where the clicks go (I asked Google ppl that in search central live 😄) I guess now you know the answer…. Google took a lot of it, users want different things, and we have not adjusted to this new era yet.

That’s that for today folks and see you in the next newsletter!

References

• Reuters: Overview and key findings of the 2026 Digital News Report

• In 2026, Less than One Third of Google Searches Still Send a Click

Support the Riddler!

• Sign up for my newsletter if you’re not already.

• Share the newsletter and invite your friends to signup. Help me reach 2k signups by end of 2025 please 🙂

• Provide feedback on how I can make this newsletter better!!!

• Buy me coffee.

• If you’re an SEO tool or an SEO service provider, consider sponsoring my newsletter. I’m also open to other partnership ideas as well.

Disclaimer: LLMs were used to assist in wording and phrasing this blog.

Hello Riddlers!

📌 If you find value in my newsletter and want to support the work that goes into it consider —> [☕Buy Me a Coffee☕]💡 Want more from me? [SEO Strategy Course] | [Build Your Own SEO Tools (with Python & Agentic AI)] | [Premium SEO Mastermind]

Alternatively you can become a paid subscriber

Intro

You’ve probably seen the term content chunking circulating across SEO social media, with some people recommending it as a tactic to improve AI visibility while others dismiss it as unnecessary.

And, of course, Google had to weigh in. On multiple occasions, they have made it clear that you don’t need to chunk your content for AI. They even added this in their official “Optimizing your website for generative AI features on Google Search” guide.

But… there are a couple of issues at play here.

First, a lot of SEOs are still relatively new to LLMs and AI—myself included—and I don’t think we always acknowledge that. If we did, we’d probably be a little more cautious about immediately rejecting new ideas.

Second, Google’s guidance is, to some extent, self-serving. Google doesn’t want site owners restructuring their content because of every new trend that popsup through the industry. From Google’s perspective, that’s a reasonable position to take. They said verbatim “We don’t want people to have to be crafting anything for Search specifically.” So their concern or objection is not the concept of chunking itself; rather, it’s trying to change your content specifically for search and visibility with disregard to users.

Chunking is also misunderstood in my opinion.

Of course it is, as I said we’re all new to this.

So when people try to interpret chunking into actionable approach, they may get it wrong, but then the nay-sayers would latch to those misinterpretations and label the entire concept as flawed.

So…

What is chunking, actually? And why was it never up for debate to begin with?

Buckle up!

What is chunking?

Chunking is the process of breaking a large text document into smaller, coherent sections called chunks. Each chunk represents a complete idea or segment of the text while preserving the original meaning and context.

Chunking is essential for large language models because they cannot process an unlimited amount of text all at once.

Makes sense right?

LLMs need to go through vast amounts of unstructured texts, and by dividing the content into smaller chunks in a size that LLMs can process (this size is called the context window) LLMs can process text more efficiently and therefore search for and retrieve information better.

Without chunking, LLMs are searching for a needle in a haystack.

If you ask an LLM, “What is an atom?”, it does not need to process every chemistry and physics resource ever created. Instead, a retrieval system can identify and provide the LLM with the specific sections of content that are most relevant to the question, such as passages explaining the definition and properties of atoms. This approach improves efficiency by reducing the amount of information the model needs to process, while also improving accuracy by allowing it to focus on the most relevant context.

This isn't just theoretical. Here's a simple example showing how splitting text into coherent paragraphs changes retrieval relevance.

Totally copying iPullRank here, I created this chunking simulator to show the relevance difference of keywords and text, before and after splitting the text into 2 paragraphs:

When all the text was one paragraph the relevance scores were 45.3% and 55.3%:

When the text was split into 2 paragraphs the relevance scores went up to 58.4% and 68.6% and that’s just by splitting the text into 2 proper paragraphs:

I’m still working on this tool and will probably launch it soon on my website for you to play around, stay tuned!

So….

We’ve established that chunking content is a fact of life used by RAG systems to feed relevant information for LLMs instead of giving LLMs the entire haystack…

But this raises an important question: Should you manually chunk your content, or is chunking already handled by the LLM’s retrieval system?

The answer is that you still should structure your content into clear, logical sections. While retrieval systems automatically chunk documents before passing them to an LLM, they can only work with the content they’re given.

So having well-structured content with clear headings, focused paragraphs, and distinct ideas, makes it easier for retrieval systems to identify accurate chunk boundaries and isolate the most relevant information.

And the result is, the chunks presented to the LLM are more likely to contain complete, self-contained answers, increasing the chances that your content is retrieved and used correctly.

But things like using good headers has always been part of what we do, right?

Absolutely, but that’s not the chunking process I’m proposing 😊

Introducing… the proper paragraph 🤷‍♀️

As I said in the title of this blog “Content Chunking Was Never Really Up for Debate” not only because that is actually what RAG systems already use when feeding information to LLMs, but because chunking happens to be how proper writing is!!!

Let me introduce you to….. 🥁🥁🥁

THE PROPER PARAGRAPH

According to the English language, there's such a thing as a 'proper paragraph if you’re writing formally, academically or professionally.

So unless your content is in conversational slang format like I’m writing right now - which we all know is not optimal for search - you should chunk your content using the proper paragraph method.

I can hear you in my mind saying “What do you mean Sara? what is that?”

A proper paragraph in English has the following structure:

--> Topic Sentence (The Opening): The first sentence that introduces the main point or controlling idea. It tells the reader exactly what to expect in this paragraph.

--> Supporting Sentences (The Middle): The body of the paragraph. These sentences provide explanations, facts, data, statistics, or concrete examples to back up your topic sentence

--> Transitions (The Connectors): Words or phrases (e.g., however, furthermore, for example, in contrast) used to link your sentences together smoothly.

--> Concluding Sentence (The Closing): The final sentence that summarizes the main idea, analyzes the evidence, or provides a logical transition into the next paragraph

writing your content in this format, makes each paragraph an individual entity that covers a specific point.

Here’s an example of this concept in action:

This has always been the proper way to write a paragraph. It’s not a new concept I’m introducing. And it’s very beneficial for users because just by reading the first sentence of a paragraph they can tell what the rest of the paragraph is about, making the content skimmable no matter how long it is!

Are we already using this format? I can argue that most of the content online is not written like that, nor do the average copywriters structure their content this way.

I tested the proper paragraph format using my simulator, and it did increase the relevance score.

Why? because it helps you group relevant information in one paragraph and have logically coherent content. So when RAG chunking comes in, it already has a solid foundation to work on.

Now I must be transparent, that I’m still testing more and more of this to provide solid numbers, but the concept still holds, this is how you should write your content. It is good writing which would naturally mean good chunking.

And That’s a Wrap (Almost 😄)

My argument is pretty straightforward, chunking is an established process that’s used by RAG systems to find and feed LLMs the most relevant information in a way an LLM can process.

But the more I read about chunking and what it’s trying to achieve, the more I found it similar to just proper English writing structure that has been established for a very long time.

I ran a few tests with my simulator tool, and early results showed improved relevance scores when using the proper paragraph format. So it’s a approach worth exploring.

Chunking is not just about the headers as some think and I hope by discussing the concept from both an LLM standpoint, and the English/user standpoint I showed you that, there’s really nothing to talk about… chunking your content is a fact of life 😄

That’s that for today folks and see you next newsletter!

Sources Worth Checking

• Moving from a Google-shaped Web to an Agent-shaped Web: A Refutation of Misinformation about Chunking

• Semchunk: a semantic chunking technique on github

Support the Riddler!

• Sign up for my newsletter if you’re not already.

• Share the newsletter and invite your friends to signup. Help me reach 2k signups by end of 2025 please 🙂

• Provide feedback on how I can make this newsletter better!!!

• Buy me coffee.

• If you’re an SEO tool or an SEO service provider, consider sponsoring my newsletter. I’m also open to other partnership ideas as well.

Disclaimer: LLMs were used to assist in wording and phrasing this blog.

Hello Riddlers!

📌 If you find value in my newsletter and want to support the work that goes into it consider —> [☕Buy Me a Coffee☕]💡 Want more from me? [SEO Strategy Course] | [Build Your Own SEO Tools (with Python & Agentic AI)] | [Premium SEO Mastermind]

Alternatively you can become a paid subscriber

Agency Life

“AI won’t replace project managers, because there’s nothing to replace” 😂

I saw this joke on twitter the other day and it inspired this post…!

Throughout my career, I’ve worked at several agencies and experienced different models of working with SEO project managers. They also go by other titles—SEO account managers, SEO coordinators, client success managers, and more.

In one setup, the project manager was the primary client contact. They managed timelines, assigned tasks, followed up on deliverables, removed blockers, and handled most client communication. The SEO specialists focused on strategy and execution.

Many of these project managers had little or no hands-on SEO experience. They were excellent project managers, but not necessarily SEO practitioners.

A large portion of the role involved coordination: chasing updates, writing meeting notes, updating project boards, preparing status reports, scheduling meetings, documenting action items, and making sure nothing slipped through the cracks.

In other words… SEO clerking.

But that was years ago… today a lot of things have changed, my perspective for one as well as AI tools becoming integral part of our work.

So buckle up, as in this blog I intend to share my 2 cents on the role of SPM in 2026!

SEO depth

I really think we need to reconsider how we select people for the SPM role. After being in this industry for over 12 years, I believe an SEO project manager should have some hands-on SEO experience.

Some of the they should have done before:

• Build or contribute to building a strategy

• performed technical audits, even simple ones

• collaborated with developers to get things done

• created content recommendations for SEO

• worked directly with content writers to update/create new content

• worked with external third party agencies on top of an internal SEO team

….. and more just to name a few!

I’m not undermining people with pure project management backgrounds. Traditional PM skills are still important.

But SEO is one of those fields where you can’t fully “coordinate” your way through complexity.

Without hands-on exposure, there’s a real risk of slowing things down, misinterpreting priorities, or becoming an unnecessary layer between execution and decision-making.

If you’re currently in an SEO project manager role without SEO experience, the fix is simple: start getting closer to the work.

Play around with the tools, learn, try things even minor things here and there….

You’re not trying to convert to a full stack SEO, you are trying to build enough fluency to not be a blocker, and ideally to be able to step in when needed.

AI leverage

Not all agencies even have a dedicated SPM role. In many cases, SEO managers inherit the coordination and “clerical” side of delivery. That works too.

So whether you have an SPM or not, the person handling delivery just got a massive unlock.

Because AI is already handling a big chunk of the administrative workload:

• Meeting summaries

• Turning conversations into structured tasks

• Drafting client updates and follow-ups

• Organizing project documentation

• Rewriting or refining status reports

• Converting notes into actionable briefs

And more….

A lot of this admin work was never the “value” part of the job to begin with, it was just necessary overhead.

If you’re an SPM or doing SPM as part of your role, here are two additional areas I recommend you explore:

• Optimize the project plan. Once you have a strategy in place, use AI tools to stress test it. AI can help you take it even to the next level, make it better, suggest changes here and there in priorities to drive more value to your clients.

• Agility management. Changes happen as you go in any project. SEO is far from being a static field. Instead of maintaining static documents that quickly become outdated, use AI to continuously reframe plans based on new inputs.

Not to mention how I think Claude code should be your best friend.

Familiarize yourself with the idea of “Claude skills” or reusable AI workflows. For example, I recently built a simple SEO Claude skill that turns a single issue name into a structured SEO user story.

For example, here’s the output using this skill for the issue “organization schema missing on the homepage”

Small input → structured output → faster execution. Right?

And That’s a Wrap (Almost 😄)

Basically what I’m trying to say is that, in 2026 the role/skills for SEO project management have changed.

and this blog was my attempt to change the joke “AI won’t replace project managers, because there’s nothing to replace” to a no-joke.

If you pickup some hands-on SEO experience, and upskill yourself with necessary AI tools for project management, AI cannot replace you because you are down to the bones… you’re down to the real value that AI cannot replace!

That’s that for today folks and see you in the next newsletter!

Sources Worth Checking

SEO User Story Claude Skill

Support the Riddler!

• Sign up for my newsletter if you’re not already.

• Share the newsletter and invite your friends to signup. Help me reach 2k signups by end of 2025 please 🙂

• Provide feedback on how I can make this newsletter better!!!

• Buy me coffee.

• If you’re an SEO tool or an SEO service provider, consider sponsoring my newsletter. I’m also open to other partnership ideas as well.

Disclaimer: LLMs were used to assist in wording and phrasing this blog.

Hello Riddlers!

📌 If you find value in my newsletter and want to support the work that goes into it consider —> [☕Buy Me a Coffee☕]💡 Want more from me? [SEO Strategy Course] | [Build Your Own SEO Tools (with Python & Agentic AI)] | [Premium SEO Mastermind]

Alternatively you can become a paid subscriber

SEO has changed/is changing…. ya ya ya

You’ve probably heard it a thousand times by now: “SEO is changing”, “SEO is evolving”, and every other variation of the same message. And we’ve all been bombarded with GEO advice on how to optimize for the new world of LLMs.

Here’s the thing: LLMs still aren’t sending much traffic, so for now, we’re still focused on figuring out how to get the most out of Google.

But Google is now eating up most of the clicks… we’re in the zero click ERA 🤷‍♀️

“In the first four months of 2026, a whopping 68.01% of Google searches ended without a click,” according to a new study by Similarweb and SparkToro.

So where do the clicks go, what happens after the user searches?

There are 3 possible scenarios:

• 32% of the time people click to an organic result, to another Google property (Youtube, AI Mode, Maps, Images, etc…)

• 39% they do nothing after the search.

• 29% they do another search.

The study found that for every 1000 us Google searches, only 232 convert to clicks to a non-Google property.

That’s not good…

And so far every solution I see proposed to this dilemma misses the biggest opportunity out there…

We forgot that Google has different surfaces

I was listening to a webinar recently about “Google Discover” and it was during this webinar that I got my Aha moment.

Google Discover is a Google surface that shows users content based on their interests. Google also said they’re rolling the feature out on desktop last year—not sure where that went, but they said it’s coming.

Google discover is a huge traffic source, for a lot of website owners, it makes the biggest source of traffic, even more than traditional search. and that’s why we should consider optimizing for discover.

But here’s the thing…

the content that works in Google discover is slightly different than the content that works in traditional SERPs, although there’s an overlap of course.

So what type of content works well in Google Discover?

Content for Google Discover

Your best ideas are going to come from browsing your discover feed and seeing what made it there, however here are some pointers:

• Sensational titles. But you need to avoid click bait, lean more on people’s natural curiosity vs been purely click-baity. An example is “New Zealand reaction to Mo Salah’s goal”.

• Quoting people in titles. This is something that would not work in traditional SERPs, but for Google discover, having a title like “Mbappe on PSG’s season: “for me, a team that wins will always be an example of football”.

• Questions in titles. Some have reported that this type of titles perform really well in discover. Worth testing out. An example is “why men keep dropping out of the workforce: it starts in childhood”

• Timely fresh content. Yes you can still get visibility in discover with your evergreen content, but timely content has an edge. One thing you can do is to keep an eye on Google trends for keywords related to your niche, and once there’s something relevant to your audience, you can blog about it.

• Images are very important for Google discover. Having the right featured image can improve your CTR there, this is something that is not relevant for traditional search results since you rarely see the featured image in search.

• Localized content. Google discover surfaces content that is very relevant to the user and one of the factors that determine relevancy is location. If your customers are in a specific geographical area e.g Ontario, content like “Spring in Ontario. Uncover colors, rhythms and flavors that make this province a true cultural canvas” may work well.

Cheesy: understand your audience

Yes I know saying “understand your audience” is as lame as the Google advice “create helpful content” but it’s a step we rarely do in SEO.

Sometimes when I meet with business owners, I’m pleasantly surprised when they share things like:

“Our target audience are SEO agencies managing multiple clients who need to standardise workflows, speed up repetitive tasks, and maintain consistency without increasing headcount.”

Because then you can tailor interest-based content that would perform well in discover and on socials for your audience.

Topics you may write about for example:

• Sensational: What actually breaks first when an SEO agency starts scaling

• Quotes: “SEO manager at a 30-client agency: ‘Reporting is where we lose most of our time”

• “Why do SEO agencies still do so much work manually in 2026?”

• “Inside Canada’s SEO agencies: why reporting is still the biggest time drain”

You are not a ship anchored to the past

Our main focus has always been the 10 blue links, only today there’s rarely 10 blue links anymore… they’re usually less, with a SERPs designed to send less clicks to your website with Google’s AI experiences.

I’m not suggesting you abandon the 10 blue links, I just think you should widen your horizons a bit, and explore other surfaces available to you.

Creating content for Google Discover, can be the answer to your traffic challenges. And you probably have everything already in place:

• Google technical foundations for discover highly are practically almost the same as the requirements for traditional serps.

• User experience and bounce rate matters a lot for how your content would perform in discover, but these are things we should’ve always taken into account when creating content for SEO, right?

• You probably have a social team in place, they can work with SEO to brainstorm content ideas that can work better for both social and discover!

The name of the game for SEO in 2026 is testing every thing, and this is one thing I think you should experiment with.

And That’s a Wrap (Almost 😄)

It’s time we tackle the zero-click reality with a different mindset and play the hand we’ve been dealt. The landscape has changed but there are still real opportunities for those who adapt to how distribution actually works today.

At the same time, we should keep an honest conversation going about the relationship between platforms and publishers.

Google continues to say “create helpful content,” and publishers have done exactly that, investing significant time, money, and effort. Yet the return in the form of clicks and owned audience is becoming harder to measure and less predictable.

As the web shifts toward more zero-click experiences, the question of fairness, attribution, and sustainability for publishers becomes harder to ignore.

We should continue pushing for a web where value flows both ways, not just one where content is consumed but not always returned to its source.

That’s that for today folks and see you in the next newsletter!

Sources Worth Checking

Google Discover Webinar with Barry Adams

Support the Riddler!

• Sign up for my newsletter if you’re not already.

• Share the newsletter and invite your friends to signup. Help me reach 2k signups by end of 2025 please 🙂

• Provide feedback on how I can make this newsletter better!!!

• Buy me coffee.

• If you’re an SEO tool or an SEO service provider, consider sponsoring my newsletter. I’m also open to other partnership ideas as well.

Disclaimer: LLMs were used to assist in wording and phrasing this blog.

Hello Riddlers!

📌 📌 Set me as a preferred source on Google! Click here.

Warm Up

Around this same time last year I talked about diagnosing SEO traffic drops, I had a simple framework:

Since then, my SEO learning has continued — and today I want to share a technique that can diagnose any SEO issue.

It’s called the Ishikawa diagram (aka the Fishbone diagram): a visual root-cause analysis tool that connects cause and effect to uncover why an SEO problem is happening, and what you can actually test to fix it.

What I love about this technique is that it structures your thinking into a diagram you can share with your team and stakeholders.

So buckle up!

1# Start with the effect

Just draw a simple box (or whatever shape really) and write the problem or the symptom you’re seeing that you wish to address.

2# Buckets of causes

The next step would be to draw a diagonal line, and list all category of potential causes. We’re not listing exact causes yet, just categories of potential causes.

In SEO we have a handful of established categories, so our work is pretty clear:

• Technical

• Content

• Authority

• User experience

You may want to add more categories like market changes or Google updates and SERPs changes… totally up to you how you tackle this.

It’s fascinating how we can all work from similar-ish checklists yet arrive at completely different SEO results and performance in search.

I really think this is very helpful in breaking down a complex problem, and help to focus on it from various perspectives.

Reminds me of the 6 thinking hats technique, where you wear a different hat for a different mode of thinking all in an attempt to solve a problem.

This is pretty much similar, only here, instead of hats, you’re switching between a technical lens, a content lens, and so on.

3# Potential Causes

Now it’s time to fill in potential causes under each of the above buckets (and yes I changed the diagram color 😄)

A quick disclaimer: this is not meant to be an SEO checklist. It's simply an example of how one person might approach the problem. Your own experience, knowledge of the website, and understanding of the industry may lead you to a completely different diagram.

Here’s how I thought about this from each lens:

• Technical lens: from my experience, sometimes things happen on the website itself that can cause a decline in traffic. Did your tech team remove the sitemap and not tell you, is there a UX change that included a lot of JS, is server returning 5XX errors or your internal links for one reason or the other have changed?

• Content lens: if your content is low quality (AI and spammy for example) it will stop working at some point, that if it worked at all. So that maybe the issue, or is your content old and have not been updated in a long while? your competitors are working btw, they don’t stop, and so shouldn’t you, SEO is not a one and done thing so it maybe your content is up for a refresh. Finally, is your content a “commodity” type of content that is just lame, expected, and has no unique angle?

• Authority lens: for so long in SEO pure brand mentions meant nothing, but that has changed, did your strategy for building authority adapt? Also let’s say you did a domain migration, and all your backlinks are pointing to your old domain (ya ya I know you created redirects and all), but wouldn’t it be nice to get a fresh pack of backlinks pointing to your new domain?

• User Experience: a lot of SEOs would not bucket this alone, but I would 😄 mainly because it requires extensive type of work and analysis on it’s own. How’s the bounce rate on your page? while this specific metric is NOT a ranking factor, it can also indicate that there’s a problem with your content. How is your CTR? well I know that CTR is dead in search according to some ppl 😄 but it’s always worth a look to understand if there’s anything you can do to improve this (test different title formats perhaps?)

So basically keep asking why, and filling in the diagram until you’ve reached a useful level of detail. That is when the cause is specific enough to be able to test a change and measure it’s effect.

and you’re done! You now have a clear view of potential causes, that you can prioritize and start testing out.

And That’s a Wrap (Almost 😄)

It’s not uncommon for the most powerful ideas to be surprisingly simple.

There’s a quote often attributed to Albert Einstein: “If you can’t explain it simply, you don’t understand it well enough.” Whether or not he actually said it, the principle holds true.

What I appreciate most about the Ishikawa diagram is its simplicity. It helps organize messy problems into something visual, collaborative, and actionable.

And if you struggle to populate the diagram at all, that can be useful information too, it may simply highlight areas where you need to deepen your SEO knowledge and experience.

That’s that for today folks and see you in the next newsletter!

Sources Worth Checking

Support the Riddler!

• Sign up for my newsletter if you’re not already.

• Share the newsletter and invite your friends to signup. Help me reach 2k signups by end of 2025 please 🙂

• Provide feedback on how I can make this newsletter better!!!

• Buy me coffee.

• If you’re an SEO tool or an SEO service provider, consider sponsoring my newsletter. I’m also open to other partnership ideas as well.

Disclaimer: LLMs were used to assist in wording and phrasing this blog.

Hello Riddlers!

📌 📌 Set me as a preferred source on Google! Click here.

Warm Up

So we’ve heard…

“Google search is AI search”, search is changing, and then cloudflare comes in and drops this data “Bot web traffic has overtaken human web traffic, data shows, for the first time” [1]

Google also added “agentic browsing audit” documentation to its lighthouse docs [2] that include reference to things like LLMs.txt after - also Google - repetitively telling us that LLMs.txt is not useful/important on various occasions 😂😂😂

It seems like we are trying to establish certainty in an environment where things are very dynamic and even the people building these systems don’t have all the answers yet.

Few topics capture this confusion better than LLMs.txt!

Over the course of several months, we heard:

• Jun 18, 2025: “FWIW no AI system currently uses llms.txt”

• Jul 22, 2025: noindex your LLMs.txt file

• Jul 24, 2025: Google doesn’t support LLMs.txt and isn’t planning to

• Aug 1, 2025: Why should AI systems trust a file that website owners can fill with whatever they want?

• Dec 3, 2025: Google itself uploaded an LLMs.txt file for the Google Search Central portal (which is now gone btw 404-ing https://developers.google.com/search/docs/llms.txt but it still remains on many of Google’s other sites)

• Jan 6, 2026: Google explains, they added LLMs.txt to their websites for other purposes

• Jan 20, 2026: Google Search Team Does Not Endorse LLMs.txt Files

And on the other hand, we have reports that "Log file analysis shows that OpenAI crawls LLMs.txt file”

At this point, I think the entire industry deserves a group therapy session 😂

But all jokes aside, there are a few things we need to keep in mind:

• When Google representatives speak publicly, they’re often speaking about specific products and teams. What applies to Google Search may not apply to other Google initiatives or to other companies entirely.

• It was widely believed that Google doesn’t use metrics like CTR or bounce rate for rankings. But it turns out they do use other user behavior signals that are in the same general category🤷‍♀️. It just shows that there usually isn’t a simple yes or no answer, there are often a lot of details, and those details really matter.

• We should stay open-minded about everything. A lot of things are still new to everyone. It helps to pause, think things through, test ideas, and then form your own conclusions. Also this isn’t something you do once and forget, it’s an ongoing process as more information keeps unfolding and technology continues to evolve..

In this new light💡here’s everything I know about getting your website ready for AI agents!

What agents do?

AI agents are software that performs specific tasks on your behalf autonomously. Unlike chatbots and LLMs, AI agents don’t just provide “answers”; they perform actual tasks, they can plan a trip for you, and make bookings for example.

“At its core, an agent is a system that receives input, interprets it, then plans and executes actions on behalf of the user” [3]

To do this, they need to browse the web, and be able to use your website.

In the AI-powered search era, we have three barriers we need to cross:

1. Discoverability: we need to be findable by different AI systems.

2. Citation and/or selection: being cited and selected as a source. And while AI agents may not provide outputs like AI mode and AI overviews for example, there has to be some type of mechanism where they narrow down the choices to start making decisions and taking actions.

3. Actions: can AI agents use your website? and that’s what we will focus on today!

Is your website screen reader friendly?

AI agents and screen readers use the accessibility tree as their primary roadmap to navigate websites and applications. This means that you can use chrome plugins like Text Mode to see how both screen readers and AI agents would see your website. Here’s a screenshot from my LinkedIn feed using this plugin:

What to tell your developers?

• Use real HTML elements like <button>, <nav>, <main>, <header>, and <footer>, and avoid replacing them with generic <div> containers just for styling. Make sure elements clearly describe what they do.

• Use <button> for clickable actions, and avoid clickable <div> or <span> elements.

• Every input must have a <label> that clearly explains what the field is for. For example, use “Email address” instead of relying only on placeholder text.

• Add appropriate autocomplete values to forms, such as name, email, tel, street-address, and organization. This helps browsers and AI agents complete forms correctly.

• Use headings in order (<h1> → <h2> → <h3>) and avoid skipping levels (for example, jumping from <h1> to <h4>). This helps agents understand the structure of the page and its sections.

• When building complex, custom, or dynamic user interfaces where native HTML elements do not provide the required functionality, use ARIA (Accessible Rich Internet Applications) attributes to fill those gaps.

• Make sure important content is already present in the HTML when the page loads rather than being added later through JavaScript. Use Server-Side Rendering (SSR) so pages are fully built before they reach the browser. Avoid depending on JavaScript to display critical content, because AI agents may not run or fully process scripts. Anything important should not rely on user actions or client-side scripts to become available.

• Use clear, descriptive link text that explains where a link goes. Avoid vague phrases such as “click here” or “read more.” Both users and AI agents rely on link text to understand the purpose of each link.

Google Lighthouse Agentic Browsing audit

If you download chrome canary (Chrome Canary is Google’s most experimental, cutting-edge version of the Chrome browser, designed primarily for developers, testers, and browser enthusiasts.), open your webpage, right click inspect, go to the lighthouse report, you’ll see that Google now has an Agentic browsing audit… ta-da!

You can use this audit to help you assess your webpage for agentic browsing (clear from the name daah 😂)

If you don’t want to do all of this, and want just to know what to tell your developer, here you go:

What to tell your developers?

• CLS (Cumulative Layout Shift) just got another importance boost outside of the core web vitals score. Your CLS score is a measure of UI stability for interaction precision.

• LLMs.txt, (please don’t laugh, mute giggles are ok though) but Google’s own documentation recommends “Create an llms.txt file and place it in the root directory of your website (for example, https://example.com/llms.txt). The file should follow the llms.txt specification and provide a concise Markdown summary of your site’s purpose and key links.” [4]

• Use WebMCP [5]. WebMCP is a proposed protocol that lets websites explicitly define and surface their “tools” (like forms, actions, and workflows) to AI agents in a structured way, instead of relying on agents to infer behavior from HTML, JavaScript, or UI interactions. In practice, it lets a site declare “this is a search tool,” “this is a checkout action,” or “this is a booking flow,” along with the required inputs and expected outputs, so agents can interact with it reliably and consistently.

Markdowns

Another highly controversial topic is adding markdowns to your webpages. Markdown is a lightweight markup language used to format plain text. It is widely used online for platforms like Reddit for example to format text in posts, comments, and community sidebars.

Google has added markdown files, .md.txt files, to the Google Search help documents [6]. Here’s an example.

While John Muller explicitly said that “There were discussions around this on Linkedin a few weeks back. This is not being done for Search or generative AI responses in Search.” This does not mean that Markdowns are useless, they maybe used by AI agents.

One tip though, do not create a markdown version of each webpage, because this may cause duplication. At the moment I’m testing adding markdown in the html of the page. You can use markdown between html tags as long as you add to the tags the markdown attribute with value 1. markdown=”1”

Here’s how this looks like on my website right now:

And That’s a Wrap (Almost 😄)

While a lot of the above recommendations are classics and have existed long before AI agents, some are very new and come with a lot of skepticism.

Keep an open mind, test things out, and keep learning.

That’s that for today folks and see you next newsletter!

Support the Riddler!

• Sign up for my newsletter if you’re not already.

• Share the newsletter and invite your friends to signup. Help me reach 2k signups by end of 2025 please 🙂

• Provide feedback on how I can make this newsletter better!!!

• Buy me coffee.

• If you’re an SEO tool or an SEO service provider, consider sponsoring my newsletter. I’m also open to other partnership ideas as well.

Disclaimer: LLMs were used to assist in wording and phrasing this blog.

Sources:

[1] Bot web traffic has overtaken human web traffic, data shows

[2] Lighthouse agentic browsing scoring

[3] Introduction to agents

[4] llms.txt

[5] WebMCP

[6] Google Adds Markdown Files To Help Docs But Not Used For Search

Hello Riddlers!

📌 📌 Your support keeps this newsletter FREE —> [☕Buy Me a Coffee☕]💡 Want more from me? [SEO Strategy Course] | [Build Your Own SEO Tools (with Python & Agentic AI)] | [Premium SEO Mastermind]

Warm Up

Since the Google I/O event a few weeks ago, my feed has been full of hot takes declaring “SEO is dead.”

Here’s one from TechCrunch:

It opens with:

“The era of the “ten blue links” is officially over.”

But if you read past that line (and most people don’t), the same article clarifies later:

“The links, to clarify, have not entirely disappeared; they are just no longer the priority for many types of searches.”

There’s plenty of speculation about what Google’s I/O announcements mean for search and with even more AI being woven in, the obvious question is: are we headed for another traffic drop?

AI search has become the synonymous to “less traffic to publishers”, so when Google’s VP of search, Liz Reid declares that ‘Google search is AI search, through and through,’ it’s not exactly great news 😆

So what are we going to do?

As of now, everything is still in the air, a lot of the AI features Google announced will be pushed to search later this summer, and as I will discuss below, they may not cause the apocalypse everyone is expecting. This much I know. Of course I can be wrong, but hear me out.

I also know that the web echosystem relies on publishers creating good content, if publishers cannot properly measure, let alone see the ROI of their work, the system will collapse, so whatever is happening in search, Google will have no option but to find ways to support publishers and compensate them.

Enter features like Preferred Sources, which just rolled out to all publishers after being limited to news outlets only. It's the shortcut no one expected! A way to get more visibility in search and across Google's AI surfaces.

If you're not familiar with it, it's a feature that lets people "follow" specific websites, so those sites appear more in their search results. [learn more here]

So what’s happening to search?

The Search Box

Google just launched their biggest upgrade to their search box ever. It anticipates your intent and helps you formulate your questions better that go beyond autocomplete.

What this means for SEO?

We will be seeing more and more long tail queries in GSC. Our traditional keyword research processes and optimizations will need to adapt accordingly.

It’s not going to be just simple keywords like “best SEO newsletters”, there will be more details attached like “best SEO newsletters for someone starting in SEO with no technical background” for example.

With more specific searches like this, your content will need to be more specific as well. But in a way, this has always been the case, over 70% of traffic on the web already comes from long tail keywords [source]. The queries are just going to get even more specific.

Additionally being more detailed and specific in your content has always been a thing, after all 94.74% of keywords have monthly search volumes of 10 or less [source]

Search Agents 🧐

Did you ever use Google alerts?

Well one of the features Google announced was search agents that keeps you up-to-date on whatever you need.

For example, if you’re apartment hunting, the new search agents feature can keep scanning the web for you and notifies you once there’s a new listing that fits your specific needs.

Ya… google alerts with more fine tuning features… one you might actually use 😆

What this means for SEO?

Agents will be searching on behalf of humans, LLMs do that at the moment in a way. Is your website agents ready?

Turns out adding an LLM.txt, markdown and schema may come in handy now right?

If your website has tools that agents maybe using, things like WebMCP protocol that Google quietly announced that didn't get nearly the attention it deserved maybe core to your web strategy. It now all makes perfect sense. It’s another piece of the agentic web puzzle.

The question is are we ready AI agents using your website on behalf of users?

Agentic coding in Search

You know when you want to teach a child something and you start by drawing it for them?

Search is about to do that.

Google announced that search results will be able to generate interactive, visual experiences on the fly. Not static diagrams, but actual tools you can play with.

For example,

ask how mixing red and yellow works, and instead of a text explanation of how they create the color orange, you get sliders to adjust the composition yourself and watch the color change in real time.

What this means for SEO?

I really don’t know. But I can make some guesses:

• People will have higher expectations from educational content. A lame block of text may not cut it anymore. If you're teaching something, you'll need to go deeper, or offer something the demo can't.

• A lot of learning will happen in search. I don’t think this is great news given we know the limitations of LLMs and how they hallucinate, a side of effect of their design.

• Another drop in traffic to educational websites. Sorry, but not great news.

The Mini Apps & New Content Mindset

One thing the I/O blog mentioned that I find super interesting, is “But often, you aren’t asking one-off questions — you have an ongoing task you find yourself searching for over and over”

With the agentic capabilities coming to search, you will be able to create dashboards to track your progress on specific tasks. Like building a fitness tracker for your daily workout plans and meals.

“You can think of these like mini apps for your own specific tasks.”

But this feature will be only available at first to Google AI Pro and Ultra subscribers in the U.S.

What this means for SEO?

I know this may come off surprising, but this is the part I liked the most about the I/O announcements. It just gave us a major hint how we should be creating content.

Think of the task the user is trying to achieve that this one search is one part of, look for the bigger picture not just the exact searches and their intent.

Old thinking:

You sell evening dresses, you optimize your content as follows:

• evening dresses product category page

• individual evening dresses page

• blogs about evening dresses (e.g what dresses are most slimming, and how much should you spend on an evening dress, etc..)

New thinking:

You sell evening dresses, you optimize your content as follows:

• You ask “why is a customer looking to buy an evening dress”

  • They have a date

  • They are attending a wedding

  • They just got invited to a black tie event and have no idea what to wear

• From there, you build content around those bigger goals, the date, the wedding, the event, not just the dress. Some of the information will naturally overlap with what you’re already creating, but the structure shifts from “what are people searching for” to “what are people trying to accomplish.” Think of it as zooming out from the search to the task behind it.

Psst… his overlaps nicely with the commodity vs. non-commodity content framework from the Google search central live event. The content that survives is the content that serves a purpose no widget or AI snippet can replicate.

And That’s a Wrap (Almost 😄)

I’ll be honest, I’m excited about what’s coming, even if it’s a challenge. SEO has survived every major evolution so far, and I don’t think this one will be any different.

And did you notice how everything connects? Preferred Sources, search agents, WebMCP, agentic coding, mini apps, etc.. it’s all pointing in the same direction. The web is getting more agentic, and the SEOs who adapt their thinking early will be just fine.

That’s that for today folks and see you next newsletter 👋

Support the Riddler!

• Sign up for my newsletter if you’re not already.

• Share the newsletter and invite your friends to signup. Help me reach 2k signups by end of 2025 please 🙂

• Provide feedback on how I can make this newsletter better!!!

• Buy me coffee.

• If you’re an SEO tool or an SEO service provider, consider sponsoring my newsletter. I’m also open to other partnership ideas as well.

Disclaimer: LLMs were used to assist in wording and phrasing this blog.

Hello Riddlers!

📌 Your support keeps this newsletter FREE —> [☕Buy Me a Coffee☕]💡 Want more from me? [SEO Strategy Course] | [Build Your Own SEO Tools (with Python & Agentic AI)] | [Premium SEO Mastermind]

Reddit is Organic

I was planning on sharing today how I got my Python course cited in ChatGPT without listicles or spamming, but I found a more interesting idea to write about!

Yesterday, I was running my monthly SEO town-hall-style meetup and Reddit came up, and I found myself discussing a cool idea, that I decided to share today instead!

Well, we all know how important Reddit is for visibility in LLMs. Reddit is a leading source across all AI search tools. It’s the top-cited domain on Perplexity, and among the top three on both SearchGPT and Google AI Mode [source].

And in case you didn’t know that, OpenAI officially uses Reddit as part of its training data [source].

Then, of course, we know that Google loves citing Reddit way more than we SEOs would like to see. It constantly raises eyebrows, really. Did you know that a Reddit thread can rank on Google within minutes 🤷? [source]

It’s the stuff fairy tales are made of for SEO people…

But the problem with Reddit is that it’s organic. If you try to hijack a thread to insert your brand, you will be easily spotted by Redditors and moderators. It’s not going to work. It can actually backfire for your brand.

The best engagements on Reddit about your brand are the ones that come naturally and organically, without you paying someone to promote your product or service around there. The strongest Reddit mentions are the ones you don’t manufacture.

That’s probably why Google and LLMs love Reddit…

But what can we as SEOs do then? How can we leverage that platform?

Let me tell you how!

Your New Customer Service Q&A Database

I wrote recently how Starbucks is now hiring more baristas as relying on automations backfired [source]. People want to engage with other people, it’s also more efficient sometimes (contrary to the popular belief that automation is always better)

There are moments when people would rather speak and engage with other people.

What if you use reddit as your customer Q&A forum? what if you direct users to your own brand subreddit where they can post questions about your brand and products, and get human-written informative answers.

What if your social media team uses reddit to engage with your customers on your brand subreddit.

I did this analysis over a year ago [source] and found many people are searching for brand subreddits.

Most of the time, these subreddits are not official. What if there’s an official one, where people can still post freely and ask questions, the only difference is that you are directing your customers to post their questions there.

You know how many brands have an FAQ page, that’s a great practice, but now your subreddit can supplement this page, and be a resource for every possible question your customers have.

If you’ve ever been on Facebook groups recently, you’ll see how many people are still engaging and asking questions there and some of those posts are also getting visibility in search, because that’s what people want.

And That’s a Wrap (Almost 😄)

SEO tactics are no longer limited to changes you make on the website in my opinion.

I personally audit Youtube, I audit socials, and I try to understand what factors and platforms impact a brand’s visibility in search and LLMS, then build my strategy accordingly.

And as simple as this reddit tactic is, I really think it would be useful for brands that have multiple lines of products or complex products that users can come back with questions about.

That’s that for today folks and see you next newsletter.

Support the Riddler!

• Sign up for my newsletter if you’re not already.

• Share the newsletter and invite your friends to signup. Help me reach 2k signups by end of 2025 please 🙂

• Provide feedback on how I can make this newsletter better!!!

• Buy me coffee.

• If you’re an SEO tool or an SEO service provider, consider sponsoring my newsletter. I’m also open to other partnership ideas as well.

Disclaimer: LLMs were used to assist in wording and phrasing this blog.

Hello Riddlers!

📌 Your support keeps this newsletter FREE —> [☕Buy Me a Coffee☕]💡 Want more from me? [SEO Strategy Course] | [Build Your Own SEO Tools (with Python & Agentic AI)] | [Premium SEO Mastermind]

The Mindset

As a LinkedIn’er myself 😂, I see tons of SEO tests and experiments shared. Some are really good and some are… just broken, and I’m sure you’ve seen your fair share too.

The problem I realized exists is, we need a better mindset to create SEO experiments and to read and assess their results.

Unless we want to build our strategies on broken assumptions, or even worse, do the right SEO tactics, but assume they don’t work because… we’re approaching the tests with a mindset that’s lacking!

Let me explain what I mean… buckle up, this is super FUN!

Google Search Console is a broken tool

There… I said it… again…

The first time I said GSC was buggy, it raised a lot of eyebrows… to my surprise.

Well, a few quick examples to establish an agreement on that, include the URL Inspection Tool showing a page as “not indexed” while that same page is literally appearing in the Performance Report collecting impressions… or impressions being inflated for almost a year 😂😂😂

There’s this unwritten rule, that if your SEO strategy is working, the first early signs would be an increase in impressions. I still believe that’s true. But as of today… I don’t think this is enough.

You maybe thinking rankings is a better measurement…. well yes and no (I’ll explain in the next section), but my conclusion is:

if you rely solely on GSC to see if your test/experiment is working, you may not be able to spot that accurately. There’s data lag, there’s seasonality, there’s inflated metrics, and more…

The best approach is imo:

• Combine data from multiple sources (e.g: GA4)

• Check user behavior on the page because that’s all that matters (use MS clarity for example)

• Have a baseline of your website performance, and understand potential impact of seasonality (decide on % lift or decline)

Google plays games

I mentioned above using rankings to measure the success of an SEO strategy, right?

Well, imagine this…

You try an SEO tactic, and the next day your ranking jumps from position 50 to position 3.

Then you repeat the same tactic 2–3 more times… and the same thing happens again.

Wouldn’t that reveal a LOT about how Google works?

And wouldn’t that open the door to even more search manipulation? (As if backlinks spam, listicles, and everything else weren’t enough already 😂)

Google has two patents (Ranking documents & Changing a rank of a document by applying a rank transition function) describing how it intentionally slow down ranking changes instead of updating rankings instantly 😂

Google is using social engineering to fight spam.

For example, if you build backlinks to your website, you may notice:

• nothing happens at all

• a decline in rankings

• rankings fluctuations

for a period of time (a transition period), before you get rewarded, that is if Google sees you deserve to be rewarded.

This on it’s own is enough

to mess up with a lot of SEO tests.

You can be doing the right thing, but seeing no rewards at all. I experienced that in my own Python for SEO page. I did everything right imo, and it was not until recently that it finally made it to the top of the SERPs.

The core goal of Google is spam detection and dampening manipulative SEO, such as aggressive link schemes or constant micro‑tuning based on daily SERP feedback.

By introducing some type of a ranking transition period with seemingly random or counter‑intuitive ranking changes, Google makes it harder for spammers to map “I did X yesterday, rankings went up today, so X works.”

The patent discusses observing how site owners react to these fluctuations; if someone rapidly reverses or overreacts to every movement, that behavior can itself be a spam signal

For link building specifically, the patent says:

“it might take approximately 70 days for a change in a document’s link-based information to change the rank of the document to its steady state”

The problem when you have such a transition period, a lot of other changes have already occurred on your website, so it can become a challenge to isolate the exact tactic that brought the positive impact.

Also, anyone saying SEO does not need a minimum of three months to work, I hope they read this…. things can be fast, but also can be slow, by design.

Best approach for analysis imo

Well if data from GSC is… inflated sometimes, and rankings are tricking you, what can we do?

The best analysis imo would be existing SERPs and citations, and finding patterns. That is if you’re looking for a quick analysis. Otherwise, long term SEO studies expanding over at least 3 months (I’d say 6 months is even better since we saw how mount AI takes some time before it goes down) are your second best alternative.

And That’s a Wrap (Almost 😄)

My goals in this edition was to shed the light on why so many SEO tests are broken.

GSC inflated impressions and Google’s social engineering tricks are not the only reason though.

More often than not, the experiment itself has design flows. But that’s probably a topic for another day.

That’s that for today folks and see you next newsletter.

Support the Riddler!

• Sign up for my newsletter if you’re not already.

• Share the newsletter and invite your friends to signup. Help me reach 2k signups by end of 2025 please 🙂

• Provide feedback on how I can make this newsletter better!!!

• Buy me coffee.

• If you’re an SEO tool or an SEO service provider, consider sponsoring my newsletter. I’m also open to other partnership ideas as well.

Disclaimer: LLMs were used to assist in wording and phrasing this blog.

Hello Riddlers!

📌 Your support keeps this newsletter FREE —> [☕Buy Me a Coffee☕]💡 Want more from me? [SEO Strategy Course] | [Build Your Own SEO Tools (with Python & Agentic AI)] | [Premium SEO Mastermind]

Truth Be Told

I’m about to once again step into the debate of GEO vs SEO 😄

Google has said on multiple occasions that they’re essentially the same thing. That there’s nothing particularly special or different you need to do for “GEO”.

But Google has also said a lot of things before…

…and ahem, we all know how some of those turned out 😄

So it was honestly refreshing to see Microsoft Bing publish a new blog discussing the difference between traditional search systems and grounding systems.

While much of the industry has been busy arguing whether GEO is “real” or not, Bing has quietly been one of the more transparent players during this AI-powered search wave.

They introduced AI Answers reporting inside Bing Webmaster Tools, publicly discussed the role of schema and structured data for LLM understanding, and now they’re sharing more details about how indexing systems and grounding systems actually work behind the scenes.

So buckle up, because I’m about to dissect what all of this actually means for SEO 🙏

Two Systems, Two Questions

I really think it’s important to start from the top and acknowledge that traditional search, and LLMs grounding are two separate systems.

As the new Microsoft Bing blog explains:

“Traditional search and grounding systems share the same foundation – crawling, understanding, and ranking the web – but they are optimized for fundamentally different outcomes. “

Here’s a simple analogy to explain the difference.

You walk into a restaurant and the waiter hands you the menu. That’s traditional search: a curated list of options they think may satisfy what you’re looking for.

But then you ask the waiter, “What’s the best dish here?”

Now the waiter shifts from simply presenting options to giving you a direct recommendation based on context, interpretation, and experience.

And that’s essentially the difference between traditional search and grounding.

Traditional search presents you with possible sources and options.

Grounding attempts to synthesize those sources into a direct answer.

It also fits well with the classic “librarian” analogy we’ve used for years in SEO.

A librarian can point you toward the books or sections where the information exists.

But if the librarian directly answers your question based on their own reading and interpretation of those books… that’s a very different role.

One system retrieves information sources and serves you the most relevant.

The other synthesizes and delivers answers.

Traditional search asks: which pages should a user visit? (the menu)

Grounding asks: what information can an AI system responsibly use to construct a response? (the dish)

How They Work Differently

The two systems clearly have two different goals/outcomes. And therefore it’s reasonable to assume they work differently, but the good news we don’t have to assume anymore!

Traditional search is about serving the user a list of options, they believe are the best to answer the user query. When you look at SERPs, you don’t expect every single URL to be great for you but, you expect the results to be “right enough” so you find what you need.

If you’re searching for a black shirt, you’ll get a lot of options in SERPs, not every option necessarily fits your taste, but overall the results are relevant to your search and you can eventually find what you need.

AI answers has an additional constraint, the goal is not to point the user to information sources, it’s goal is to use those information sources to answer the user query (well that explains why the clicks are less, the system by design is about providing the answer directly to the user, citations or not).

AI answers use the index. Let’s make that clear, however, it’s not looking for entire pages, it’s looking for “groundable information – discrete, supportable facts with clear provenance”

This means the grounding system needs to decide:

• Can I answer this question/user query

• Do I have enough information to do so while preserving the meaning, making sure users can verify that if needed, and detecting and representing conflicting views when relevant?

This is where the two systems clearly are optimizing for different things.

Zooming In

To be more clear, here are processes and things Grounding needs to account for, that traditional search does not:

• AI systems often break content into smaller chunks (yes they chunk content) before retrieving it. The challenge is making sure the original meaning and context are still preserved after that process.

• Source quality matters differently in AI answers. A grounding system cannot treat every indexed page as equally trustworthy if it’s going to generate a direct response from it.

• Freshness becomes far more critical. In traditional search, outdated content may simply rank lower. In grounding systems, outdated information can directly become part of the answer itself.

• Contradicting sources also become a bigger issue. A search engine can simply rank one page above another and let the user decide. But a grounding system has to recognize when sources disagree, otherwise the AI may confidently present the wrong information as fact.

• Another important difference is that errors in grounding systems can snowball very quickly. In traditional search, if a result is irrelevant or inaccurate, users can usually recognize it, skip it, and adjust their search accordingly. But grounding systems don’t really have that safety net. If an AI retrieves slightly wrong, incomplete, or misleading information early in the process, that error can carry through the entire reasoning chain and influence the final answer without the user even realizing it. That means grounding systems need to optimize not just for retrieving information once, but for consistently retrieving accurate, reliable information across repeated reasoning steps and interactions.

So What?

At this point you’re looking for actionable steps, here’s some thoughts, learnings and future research ideas that I gathered at this stage:

• Understanding and optimizing for chunking seems to be valuable based on the information in Bing’s blog. I highly recommend you read “Moving from a Google-shaped Web to an Agent-shaped Web: A Refutation of Misinformation about Chunking” to learn more (I will 😄).

• We’ve seen over and over AI answers citing some URLs NOT in the SERPs. This requires an in-depth research to understand what did AI answers find in this source to cite, while this URL did not qualify for the top 10 results in SERPs (different systems, right?)

• Freshness matters more than we think. That takes updating your content to a whole new level of importance (strategy update alert: if AI answers matter to you, prioritize updating content)

And That’s a Wrap (Almost 😄)

I think the confusion of the debate of SEO vs GEO all comes down to the fact that both search indexing and grounding indexing processes start at the same foundations.

That’s true, but that does not mean they’re identical systems. They have different goals and outcomes, so that cannot be.

As the blog perfectly puts it:

“Search indexing was built to help humans decide what to read.” while “Grounding indexing is being built to help AI systems decide what to say”

I wanna end today’s newsletter by saying that, every time there’s something new in SEO, there’s always those SEO naysayers ready to dismiss it immediately… that’s the actual root cause of the SEO vs GEO debate imo. Some people are just not open to new ideas and innovation🤷

You don’t have to follow this pattern, you can do your own thinking!

That’s that for today folks and see you next newsletter.

Bing’s post: Evolving role of the index: From ranking pages to supporting answers

Support the Riddler!

• Sign up for my newsletter if you’re not already.

• Share the newsletter and invite your friends to signup. Help me reach 2k signups by end of 2025 please 🙂

• Provide feedback on how I can make this newsletter better!!!

• Buy me coffee.

• If you’re an SEO tool or an SEO service provider, consider sponsoring my newsletter. I’m also open to other partnership ideas as well.

Disclaimer: LLMs were used to assist in wording and phrasing this blog.

Hello Riddlers!

📌 Your support keeps this newsletter FREE —> [☕Buy Me a Coffee☕]💡 Want more from me? [SEO Strategy Course] | [Build Your Own SEO Tools (with Python & Agentic AI)] | [Premium SEO Mastermind]

“Here’s how AI replaced”

I get it, everyone is excited about using AI to automate their tasks, I am too. But we also need to understand what AI cannot fully replace. One thing we can agree on, is it cannot replace SEOs!

I saw this post recently on LinkedIn and I just cannot stop laughing 😂

I also didn’t believe AI should be heavily involved in quality content writing. We’ve seen one study after another showing the impact of scaled content abuse, or as Google puts it in its spam policies, “Using generative AI tools or other similar tools to generate many pages without adding value for users.”…..

But I also came across a very interesting example!

I was super surprised to learn that Ahrefs are using Claude Code to write and update some of their content. They’ve been doing it for 8 months now, and the process makes read-to-publish drafts starting from keyword in just 6–12 minutes !!!

I had to pause and learn how are they doing it and not getting hit with some kind of spam penalty.

Which brings me to today’s topic.

AI is a great tool. But like any tool, its value is defined by how you use it, and more importantly, where you use it.

Not all automations are created equal.

Nor everything that can be automated should be handed to an LLM.

So let’s break this down properly.

Using AI to generate quality content

Any good use of AI will not involve a “quick” setup, and the Ahrefs team seem to have invested a lot of time into building and automating their editorial process.

Here’s how they did it:

1. Turned every editorial SOP into a claude skill file.

   1. If you don’t know what a skill file is, it’s a a structured, markdown-based text file that teaches an AI agent how to perform a specific, specialized task (often named SKILL.md)

   2. SOP for how to write a brief became it’s own skill file

   3. SOP for how to write an outline became it’s own skill file, and so on…

2. Add your inputs, like focus keyword, working title, your POV and points you want to include, other things you want to reference (e.g specific products, etc…)

3. Build one master skill that runs all the other skills files in order.

   1. When the steps are executed sequentially, this gives you a chance to provide feedback at every stage.

4. Use Ahrefs MCP to pull SEO data like SERPs results, and competitor coverage.

5. Refine the output by providing 5-10 great articles of your own to reference, and the system surfaces moments in the draft that you can insert your own real life experience.

6. Refine the system, using a skill that tests every other skill in isolation and suggest improvements. This way your system gets better over time.

7. Read every article from start to finish before you publish it

Note: they’re not using this system to pump out hunderds of blogs every month, they actually only created 15 so far [source to post]

I see what they did here, they removed all the noise and stripped the process down to its core: the value isn’t the content itself anymore, it’s the meaning/knowledge they are trying to communicate.

I think this is a very good approach, and it works for them.

But I don’t think this can work for me.

As an indie newsletter writer, what I put out isn’t just SEO insights. It’s the tone, the random comments, the little jokes (don’t worry, I’m holding back… mostly 😂).

That’s part of the newsletter… me.

And I don’t think that’s something you can fully systematize.

Also by the by, if you have not heard, Starbucks are hiring more baristas to win back their customers.

“Over the last couple of years, we’ve actually been removing labour from the stores. I think with the hope that equipment could offset the removal of the labour,” Mr Niccol said during a call with investors.

“What we’re finding is... that wasn’t an accurate assumption with what played out.”

Customer experienced seemed to suffer, so they’re rehiring people.

Don’t use AI for these

There are things that AI simply cannot do very well. Here’s what I don’t recommend you fully automate:

• Data tasks: Despite the hype, AI tools like ChatGPT and Claude are unreliable for data work.

  • They can hallucinate, miss critical data points, and quietly omit information without warning.

  • Did you know that LLMs struggle data in tables (tabular data). According to recent research, even the smartest AI models see a big drop in their scores when they have to read data from a grid.

  • So if you’re uploading your data csv to chatgpt and asking it questions about the data, chances are the output is inaccurate, which is risky if you’re doing client reporting for example.

• Summarizing important documents: this is probably one of those no-brainers we see circulating around. I do it too, but only when I want a rough idea on something. If I want a summary that’s comprehensive and does not miss out any important points, AI is not gonna do that because it can simply skip important information…. I wouldn’t trust the output.

• Write long code in one go: I teach vibe coding, and one thing I always say break tasks down into smaller tasks and test each one. The bigger the task, the more likely the mess in the code and therefore the output, and the more challenging it is to fix, if at all 😂😂😂 so if you’re vibe coding, you need to have a mental plan of the steps involved. Start small to grow your code.

And That’s a Wrap (Almost 😄)

I really believe that the future is human, more human, and deeply human. All things machines cannot create.

Think of Artesian bread vs. store bought bread with tons of preservatives and additives.

That’s how I see the difference between AI output to human work.

And because this difference exits, not everything can be fully automate.

That’s that for today folks, and see you next newsletter 🙏

Support the Riddler!

• Sign up for my newsletter if you’re not already.

• Share the newsletter and invite your friends to signup. Help me reach 2k signups by end of 2025 please 🙂

• Provide feedback on how I can make this newsletter better!!!

• Buy me coffee.

• If you’re an SEO tool or an SEO service provider, consider sponsoring my newsletter. I’m also open to other partnership ideas as well.

Disclaimer: LLMs were used to assist in wording and phrasing this blog.

You know the drill!

The Schema Tool Built For The Agentic Web

Writing valid JSON-LD is no longer the bottleneck. Keeping it consistent across a portfolio is — different stacks, tools, outputs... no central view of what’s deployed where.

NxisAI brings it all together. AI scans your live pages, generates valid schema markup, and deploys it in one click — as a JS tag, native Shopify integration, or SSR/SSG SDK — across every site you run, from a single dashboard.

Plus native MCP, so your schema becomes queryable by AI agents directly.

Live today: the Founder’s Package. 25 seats, $16/mo locked for life, 30-day risk-free trial. Claim yours at nxisai.com.

Check it out

What a great event!

I had the pleasure be attending last week’s Google search central live event in Toronto, I have been looking forward to this, we don’t have a lot of SEO events in Canada so I was super happy that Google finally decided to bestow an event upon us!

The event covered a lot of topics, from AI in search, to Google trends, schema, SEO myths, and of course how search works.

And yes, I had my notebook in hand, so enough chitchat… let’s get to the good part!

Key takeaways

1# Search is evolving beyond information to intelligence.

The ultimate goal is for search to understand exactly what you mean and give you exactly what you’re looking for. But then, there’s the trade-off between the cost to compute vs intelligence level of a model. This is where the The Pareto frontier concept comes in. This is the set of results that are optimal for at least one combination of tradeoffs. I really think this is a very great hint, to understanding how Google and LLMs may potentially be selecting sources to rank/cite. I found this AMAZING resource on the topic.

2# The life of a URL

A URL goes through multiple phases before it finally becomes eligible to appear in search. Note how I said “eligible” because ranking is not just about technical SEO, quality signals of course matter and sometimes, your URL is not getting indexed or fell off search results because users did not find it useful and Google picked up on that.

A lot of cool nuggets and random notes from this session:

• If there are issues on your sitemap, Google can access it less often. So if Google finds broken URLs, redirected URLs, non-canonical URLs in the sitemap, that can be an issue if you’re a large website, or a news website for example.

• Factors that can impact your rankings include the type of search, is it coming from desktop or mobile, is it geo-sensitive search, is it a voice search (yes that matters), is it a photo search?

• We operate in an echo system where change is the only constant, user behavior changes, web changes, expectations changes and more. Search is a never solved problem.

3# Google Trends

First, there’s a Google trends API from Google that is in Alpha right now, and being closed tested by a select group of companies. Great news right?

My main takeaway is that, we are underutilizing this tool in SEO. So I’m bringing it to my day to day as much as possible. Do we ever check Google trends when we do keyword research? We should!

Narratives beat keywords (we’re better off focusing on topics/problems vs specific keywords).

Also and I’m quoting jean-christophe-chouinard here who was also present in the event:

“Trends vs. Keyword Planner: They are distinct tools with different ways of calculation. Trends is superior for cross-platform interest (YouTube + Search) and identifying “Breakout” queries. The data is lagged by 48 hours to prevent spammers.”

4# Good SEO is Good GEO

I really am not getting into the debate of terminology, but Danny Sullivan’s session was all about AI in search and Myths busting.

An important note from the session is “Make use of structured data”.

Schema has been under scrutiny and constant attack in the SEO industry, with many people calling it useless… it’s not.

And of course the popular slide from Danny that has been making rounds. Screenshot from jean-christophe-chouinard:

Commodity content is basic, simple, and very generic. People may not relate too, you are talking AT people. Non-commodity content is talking about a problem, sharing personal experiences and real-life scenarios.

5# Structured data, quality and AI

If you’re wondering what is the relation between structured data, quality and AI, well that was the title of the talk by Ryan Levering, a Google search engineer.

Here are my notes:

• Schema is used as context served to models when doing fanouts.

• Be more precise with schema, spamming won’t help.

• Something that’s being considered is publishing Google’s validation rules in standards and client-friendly formats, so SEOs can build their own schema validation tools instead of relying solely on the structured data and rich snippets tools (that go down sometimes because they get overwhelmed 😁)

• Google is also considered providing data on which schemas are more popular!

• Additionally Google is reinvigorating their investment in schema.org this year. After all how do you think the two newly Google agentic standards the UCP and WebMCP are going to communicate? (personal note: schema is a good candidate for this)

• Personal note: with so many voices in the industry saying schema is useless because they cannot measure it’s impact… well we have solid proof today that it is useful somehow, we just do not understand how.

6# Some good news to news😁

The highlight of the event for me is I got to ask Daniel Waisberg, Google search advocate the one question that was very important for me given that I work for a major news house! Will AIO come to top stories, and I got a clear “no”… yaaaay!

So for now… all is good for news publishers.

And That’s a Wrap (Almost 😄)

I loved every bit of this event. I will definitely do my best to attend ANY upcoming Google events like this.

We can disagree with Google reps all the time, but there’s no denial that they do an awesome work, go above and beyond and deliver great value.

My biggest regret coming out of this event is…. I only had one falfel wrap, should’ve grabbed two 😄

That’s that for today folks and see you next newsletter!

Support the Riddler!

• Sign up for my newsletter if you’re not already.

• Share the newsletter and invite your friends to signup. Help me reach 2k signups by end of 2025 please 🙂

• Provide feedback on how I can make this newsletter better!!!

• Buy me coffee.

• If you’re an SEO tool or an SEO service provider, consider sponsoring my newsletter. I’m also open to other partnership ideas as well.

Disclaimer: LLMs were used to assist in wording and phrasing this blog.

Hello Riddlers!

📌 Your support keeps this newsletter FREE —> [☕Buy Me a Coffee☕]💡 Want more from me? [SEO Strategy Course] | [Build Your Own SEO Tools (with Python & Agentic AI)] | [Premium SEO Mastermind]

My new Free Log Files Tool

Not sure if you’ve heard but I recently launched a Log File Analyzer Tool and it’s free! Also it’s super cool, give it a test drive.

Talking about server log files feels especially relevant right now. While everyone’s focused on “AI this” and “AI that,” log files are sitting there quietly holding some of the most valuable data you can get.

Honestly, they’re a goldmine.

If you want to see what I mean, check out my example report—it’ll give you a clear picture of the kind of insights you can uncover.

Anyways I decided to make today’s newsletter about Log files analysis, plus I’m giving you a raw python script so you can build your own workflows on top of this code!

Also if you don’t know what log files are, don’t worry, I’ve got you:

What are server log files for SEO?

Server log files for SEO record every request made to a website’s server, including pages crawled, response codes, and bot activity. You can use server log files to analyze how search engine and AI bots crawlers access your site, identify crawl errors, and optimize crawl budget and indexing efficiency.

We don’t have the data we need

As annoying as this sounds, it’s the truth. We are missing a lot of the data we need in SEO. Google search console, our main source of data, has a lot of issues. Last year when I called it buggy, that ruffled some feathers, I still stand by that… it’s a buggy tool in general.

Google search console data is:

• incomplete

• inaccurate (e.g. impressions have been inflated for at least the last 12 months)

• and depending on your website structured, maybe hard to segment in a clean way.

and that’s just the data part, let’s not get into the technical issues.

And that leaves us as SEO hanging, and looking for the best third party tool to get some more information. But again, third party tools come with their own limitations, and data assumptions, I would treat them as directional.

I guess this is a great motivation to build your own tool, and building your own log file analysis tool can give you answers you may not find elsewhere.

So… build your own data advantage

In a time were all we talk about is AI bots, log files cannot be any more important. From your log files you can find more concise answers to questions like:

• How much referral traffic is sent to our website via chatgpt/gemini/perplexity/ect…

• How many times does AI bots access the content on our websites.

• Which pages on our websites are accessed more often by AI bots (this is a major optimization opportunity)

and many more…

But the log files analysis does not stop there, you can also understand the behavior of Google bot on your website:

• How often does Google bot visit your website

• What pages are visited regularly and what pages are rarely visited (important optimization opportunity right here!)

• Are there any redundant page requests that make no sense (maybe we should noindex those pages?)

etc…

You can find pages to optimize, and opportunities to reduce your server costs as well. It’s a gold mine of insights.

Build your own log file workflow (Python script included)

So… as part of my Build Your Own SEO Tools (with Python & Agentic AI) course, I added this simple Colab script that generates this dashboard for you:

You can use this script as a starting point, and build your own workflow!

And That’s a Wrap (Almost 😄)

As someone who’s been working with data in SEO for a while, analyzing, learning, and trying to finding meaning and connections between the numbers we have and the things we do, I find log files very valuable.

If you’re looking for something new to try out this week, let this be at the top of your list. Ping your dev team today and ask them for few rows of data (1000+) from your log files and run the script (or my free tool) so you can understand how different bots interact with your website.

That’s that for today folks and see you next newsletter 🙏

Support the Riddler!

• Sign up for my newsletter if you’re not already.

• Share the newsletter and invite your friends to signup. Help me reach 2k signups by end of 2025 please 🙂

• Provide feedback on how I can make this newsletter better!!!

• Buy me coffee.

• If you’re an SEO tool or an SEO service provider, consider sponsoring my newsletter. I’m also open to other partnership ideas as well.

Disclaimer: LLMs were used to assist in wording and phrasing this blog.

Hello Riddlers!

📌 Your support keeps this newsletter FREE —> [☕Buy Me a Coffee☕]💡 Want more from me? [SEO Strategy Course] | [Build Your Own SEO Tools (with Python & Agentic AI)] | [Premium SEO Mastermind]

Tracking visibility in AI

Google does not show us AI visibility in GSC, and other AI tools have followed suit. Although Barry Schwarz reported yesterday that Google Search Console maybe testing an AI contribution report, so we’ll have to wait and see.

In the meantime, SEOs are experimenting with all kinds of AI visibility tracking tool or even building their own. And honestly, we kind of have to. Without some form of data, even if it’s directional, it’s hard to generate insights that actually inform what we do next.

In today’s newsletter, I want to unpack both sides of this using my own courses as an example: What are we actually measuring? and How do we turn that into action?

Let’s dig in!

What are we actually measuring

The way I think about visibility tracking is this: it’s a measure of share of voice.

How likely is my brand to be mentioned compared to competitors?

Wil Reynolds recently shared this on LinkedIn: “We just asked a room of 200 marketers to enter the same prompt into ChatGPT incognito and I’d say 60% got the same 3 brands. I was shocked to see that level of repetition of brand names.”

That level of repetition is the signal. How often is your brand mentioned?

Because here’s the thing with LLMs:
They’re not deterministic. The output can change.

So the real question isn’t:
“Am I showing up?”

It’s:
“How likely am I to be mentioned?”

But here’s where it gets tricky…

How likely… for what?

We use prompts to check visibility—but prompts are just a proxy.

What you’re actually measuring is visibility for a topic.

The specific wording of a single prompt doesn’t matter nearly as much as the topic space it represents.

For example:

I asked ChatGPT, Gemini, Claude, and Google for:
→ “top python for seo resources”
→ “top python for seo courses”

For “resources”? No mention.
For “courses”? I showed up on almost every platform (except Gemini 🤷‍♀️).

Here’s an example of a mention on Claude:

What does that actually tell me?

It tells me my visibility is stronger around the “courses” topic than “resources.”

So if I want broader visibility, the opportunity isn’t to tweak prompts endlessly…

It’s to expand my presence in the “resources” topic space.

The takeaway

Individual prompts don’t matter.

Topics do.

So when you’re measuring AI visibility, ask:

• What topic am I trying to win?

• How often do I show up across prompts within that topic?

• Where are the gaps?

Because that’s what actually turns visibility tracking into something actionable.

First party data, is the best data

One of the most useful things I did recently was mine my own GSC data differently.

I used this regex:

([^” “]*\s){4,}

to get keywords that are 5 words or more because that’s how I expect a prompt to look like and I found this search that I assume to be a prompt (there’s more):

• “has anyone actually taken sara taher seo riddler course worth 299 dollars honest review of content quality”

I ran this by ChatGPT, Claude, Gemini and Google and I kid you not, none of them corrected the pricing for the course is not 299, but 100 😂😂😂 but that’s not the issue.

With the exception of Gemini, both chagtp and claude mentioned a big yellow flag for me to work on: there are no independent third party reviews of my course. Well, in actuality there is, but only on LinkedIn in some posts, but there’s non in the places/websites LLMs look for to validate a product e.g. reddit.

Here’s what chatgpt said:

Here’s what claude said:

So this is another workflow for you:

• Check your GSC for prompt like keywords

• Run them by LLMs

• See how often you’re mentioned or not and if not, why.

• Come up with a plan.

Note: I’m not entirely sure how to reliably get LLMs to correct incorrect pricing when it’s embedded in user input but I think now I have an idea for testing and research!

And That’s a Wrap (Almost 😄)

Tracking your AI visibility is great, but understanding it and knowing how to use those insights is what actually matters. And you may not need a lot of prompts to do that btw!

Also, always start your data journey with GSC. First party data is your best data (keeping in mind that GSC is very bugy 😄😄😄)

Support the Riddler!

• Sign up for my newsletter if you’re not already.

• Share the newsletter and invite your friends to signup. Help me reach 2k signups by end of 2025 please 🙂

• Provide feedback on how I can make this newsletter better!!!

• Buy me coffee.

• If you’re an SEO tool or an SEO service provider, consider sponsoring my newsletter. I’m also open to other partnership ideas as well.

Disclaimer: LLMs were used to assist in wording and phrasing this blog.

Hello Riddlers!

📌 Your support keeps this newsletter FREE —> [☕Buy Me a Coffee☕]💡 Want more from me? [SEO Strategy Course] | [Build Your Own SEO Tools (with Python & Agentic AI)] | [Premium SEO Mastermind]

The search for meaning

Measuring performance is what gives our work meaning.

And in SEO, meaning has always been… complicated.

Showing ROI has never been easy—but in the past few years, it’s become even harder.

Not because SEO isn’t driving value.

But because of the ambiguity baked into the data we rely on.

You know the drill.

Google Search Console doesn’t give you the full picture.
Third-party tools estimate search volume—sometimes over, sometimes under.
There’s a massive gap in the funnel, where keyword-level attribution breaks down.

You’re left asking:

Was this conversion driven by branded search?
Or non-branded discovery—the thing we actually want to prove?

And just when you think you’ve made peace with the chaos…

We find out that impressions in Google Search Console have been inflated for over a year.

Impressions—arguably one of the few metrics that could hint at visibility, demand, even brand growth—turn out to be unreliable.

So you start wondering:

What exactly are we measuring?
And why?

The SEO is dead narrative

I’m tired of hearing it. You probably are too.

SEO is not dead.

But repetition is powerful.
The more something is said, the more people believe it—regardless of whether it’s true.

And here’s the real issue:

It’s not SEOs who believe this narrative.

It’s the people further from the work—executives, business owners, CMOs.

The moment SEO becomes hard to measure, it becomes easy to dismiss.

“If we can’t measure it, we cannot see it, and if we cannot see it, it must not be working.”

And honestly?
The ambiguity doesn’t make it easy to push back.

Time series

So… bring it on.
What do you have up your sleeves, Sara… right? 😄

Fair question.

The answer I have for you today is Time series. You know the performance graphs we use all the time, x-axis is date, and y-axis is whatever metric?

Exactly that, but now we are going to use that in a smarter way. Here’s how:

Get your graph ready… just stay away from impressions for the time being.

Then,

For the same period, plot 2 different metrics, clicks and sessions for the same time period for example or clicks and trends from Google trends. I have this graph from my Build Your Own SEO Tools (with Python & Agentic AI) course, where I compare impressions of my website (make that clicks starting today) with the search interest from Google trends for the keyword “Python”.

From the graph you can see that while the interest remained steady, I had a surge in performance at some point. That gap tells a story. Demand didn’t change.
My performance did. We are not looking for exact numbers, we are looking for patterns. Whatever I was doing in December 2024, it was working and I should probably do that again!

Here’s another example of how insights can be pulled by comparison:

In the screenshot, you can see that there's an increase in organic traffic, that's aligned with an increase in the number of organic keywords, which is NOT due to an increase in the number of pages, but rather due to an increase in branded searches!!!! [I wrote about this here]

Last but not least my favorite example, direct traffic vs organic clicks. You can show the direct impact and relationship between your direct traffic which often goes unattributed to specific marketing efforts, to your SEO work, if your graph looks like this (do you see how they go hand in hand with absolute harmony?)

That was actually a real-life case I experienced in the past for one of the websites I worked on. Putting different metrics side-by-side does magic.

Before and after

If you’re not using GSC Guardian or Advanced GSC Analyzer chrome exteions you should change that right now imo!

Both allows you to plot a vertical line that can be used to correlate traffic changes with Google updates or better development releases and SEO implementations!

Here’s an example of how they can highlight on a graph the duration of a Google update for you so you can see your traffic pattern during the update, and also visually compare before and after!

I had this discussion recently with the rollout of a new SEO feature, and having a vertical line on the clicks graph, maybe one of the easiest remedies to show performance changes.

Seasonality

Don’t forget about seasonality.

Compare your performance to the same time last year, and look at it both numerically and visually. This makes it easier to tell whether growth is coming from your SEO efforts—or just seasonal demand.

Look for patterns, 2 lines in the same graph…

And That’s a Wrap (Almost 😄)

Ya time series are your new best friend in attempting to make sense of all the chaos, I’m not saying they solve everything, but definitely having those tips in the back of your pocket will help!

Thanks for reading this far and see you next newsletter!

Support the Riddler!

• Sign up for my newsletter if you’re not already.

• Share the newsletter and invite your friends to signup. Help me reach 2k signups by end of 2025 please 🙂

• Provide feedback on how I can make this newsletter better!!!

• Buy me coffee.

• If you’re an SEO tool or an SEO service provider, consider sponsoring my newsletter. I’m also open to other partnership ideas as well.

Disclaimer: LLMs were used to assist in wording and phrasing this blog.

Hello Riddlers!

Before we dive into today’s topic, a quick word from today’s sponsor:

You Don’t Have a Marketing Strategy Problem. You Have an Execution Problem.

Most marketers know what needs to happen. The bottleneck is always doing it!

Writing the content, fixing the tech issues, running the ads, building the links, you know the drill...

Search Atlas changes that. It’s the agentic marketing platform that saves you time by helping execute your vision and not just giving you suggestions that waste your time.

A team of AI agents at your disposal that autonomously execute across your entire marketing operation:

• SEO & technical fixes ✅

• Content created and published ✅

• PPC managed and optimised ✅

• Press Release Writing and Distribution ✅

• LLM Optimization ✅

• Marketing Execution ✅

Your job becomes deciding what to grow. Search Atlas handles the rest.

73 Marketing Tools. 1 Platform. 1 Payment. 0 Manual Execution.

Start your free trial today

SEO can be overwhelming

Every day there’s a new tactic, another “must-do” strategy, constant shifts in search behavior, and never-ending updates from Google. Just when you think you’ve figured things out, something changes again. It’s a lot for one person to keep up with.

If there’s one thing I learned that works like magic, it’s consistency.

Remember when John Muller said this:

He was absolutely right, but this is not just for technical SEO, it’s for everything in SEO. Your best way to winning, is to stay on top of things.

And when I say “stay on top of things,” here’s what I actually mean:

• Search trends

• New tactics

• Changes happening on your website (and the bigger the site, the messier this gets)

and more!!!

That’s already a lot to juggle—and that’s exactly what I want to chit-chat with you about today.

Well… that, and how one simple system helped me catch something worth fixing.

The headspace

I had a recent meeting with a co-worker that inspired me to build a simple automation on Google sheets. I created a simple script that pulls latest URLs added to a website through the sitemap, their title tags, status, title length, etc….

I then started to create pivot tables to analyze the data

And that’s when something clicked 💡

It wasn’t anything groundbreaking, but it was a small, easy-to-miss fix that was definitely worth addressing.

I can’t go into the specifics, but it was one of those moments where you realize the issue wasn’t complexity… it was the mental load that prevents you from noticing opportunities. [paid newsletter subscribers can access this sheet with instructions to use it at the end of this article]

I came across this post recently on LinkedIn from Jonathan Boshoff, and he had a similar experience!

Long story short, Jonathan automated the repetitive work, and once he automated enough, he had free headspace, to look in-depth in more SEO issues, and guess what? He found a major opportunity that grew organic traffic from 160k to 1.7 million.

Can you imagine?

So we should just automate everything?

“So… is that what you’re saying here, Sara? Just automate stuff?”

Naaaah.

What I’m trying to say is, we need to build systems that work for us!

Automation is just a piece of that, not the goal.

Build systems (and yes, some automation within them) that:

• Free up your headspace for deeper, more important thinking

• Allow you to stay consistently on top of things, without constantly juggling sources or manually digging through data.

A framework to finding automation opportunities

We talk a lot about automation in SEO, and very less about what to automate. So here you go!

If you’re looking to start automating today to reap the benefits, here’s how you should do it:

Step 1: Start with Your Business Goal
☐ Write down your main business goal (e.g., grow website traffic).

Step 2: List High-Level Tasks
☐ Break the goal into key tasks that drive it (e.g., content, track performance, competitor monitoring, etc…).

Our goal here is visibility, i.e. having a simple way to quickly check the status of the tasks that drive your business goal, like how many pieces of content you publish each month and how well those new pages are performing.

Step 3: Break It Down Further
☐ Break the high-level key tasks, into subtasks. (e.g. for content: writing content, promoting content, etc…)

Step 4: Spot Opportunities
Identify tasks that are:

☐ Repetitive.

☐ Time Consuming.

☐ Bonus: follow clear IF/THEN logic. Rule-based tasks sound like IF we create a new blog, THEN we need to share it on social media or if a competitor creates a new blog, I need to be notified.

☐ Bonus: frequently cause errors when done manually

Example

If you’re wondering how this framework would look like in action, here’s a simple example just to demonstrate the process:

1. My business goal: get more newsletter signups

2. Tasks to support that goal (many, but for simplicity I’m focusing on content)

3. Zooming in, under the content category there are

   1. Creating great content

   2. Analyzing content performance

   3. Keeping up with industry trends and news to be able to create great content

   4. Promote the content on socials once created

4. Now which of those tasks are repetitive, time consuming and possibly prone to errors when done manually or follow a clear structure? I’d say everything except creating great content.

   —> therefore I should be automating everything EXCEPT the content creation!

And That’s a Wrap (Almost 😄)

Automations in SEO some how became synonyms with content creation and programmatic SEO, that’s definitely not the use case I’m promoting. Nor I am promoting the “I replaced my entire marketing team with [place an automation tool]…” narrative.

Automation is the key to staying consistent and delivering solid results, and the framework above shows you exactly how to make it happen!

That’s that for today folks and see you next newsletter!

Support the Riddler!

• Sign up for my newsletter if you’re not already.

• Share the newsletter and invite your friends to signup. Help me reach 2k signups by end of 2025 please 🙂

• Provide feedback on how I can make this newsletter better!!!

• Buy me coffee.

• If you’re an SEO tool or an SEO service provider, consider sponsoring my newsletter. I’m also open to other partnership ideas as well.

Disclaimer: LLMs were used to assist in wording and phrasing this blog.

Paywalled content below this point that includes the Google sheet template mentioned above.

Read more