SEO Archives SEO

Apr 17 2025

SEOFOMO Survey Shows How Ecommerce SEOs Use AI In 2025 via @sejournal, @martinibuster

Aleyda Solis’ SEOFOMO published a survey of ecommerce owners and SEOs that indicates a wide range of uses of AI, reflecting popular SEO tactics and novel ways to increase productivity, but also reveals that a significant number of the respondents have yet to fully adopt the technology because they are still figuring out how it best fits into their workflow. Very few of the survey respondents said they were not considering AI.

The survey responses showed that there are five popular category uses for AI:

Content
Analysis & Research
Technical SEO
User Experience & Conversion Rate Optimization
Generate Client Documentation, Education & Learning

Content Creation

The survey respondents used AI for important reasons like product listing and descriptions, as well as for scaling meta descriptions, titles, and alt text. Other uses include creating content outlines, grammar checks and other assistive uses of AI.

But some also used it for blog content, landing pages, and for generating FAQ content. There’s no details of how extensively AI was used for blog content but a case could be made against using it for fully generating main content with AI (if that’s how some people are using it) because of Google’s recent cautionary guidance about extensive use of AI for main content.
Google’s Danny Sullivan at the recent Search Central NYC event cautioned about low effort content lacking in originality.

The other reported uses of AI was for grammar checking and clarity which are excellent ways to use AI. Care should be used even for these purposes because AI has a style that can get injected into the content even for something as simple as checking for grammar.

Another interesting use of AI is for revising content so that it matches a company’s “brand voice” which is checking for word choices, tone, and even sentence structure.

Lastly, the ecommerce survey respondents reported using AI for brainstorming content ideas which is another excellent way to use AI.

Analysis & Research

The part about keyword analysis is interesting because the report lists keyword research and clustering as one of the uses. Clustering keywords according to similarity is a good practice because it’s somewhat repetitive and spammy to write pages of content about related things, one page for each keyword phrase when one strong page that represents the entire topic is enough.

Focusing on keywords for SEO has been around longer than Google, and even Google itself has evolved from using keywords as a way to understand content to also incorporating an understanding of queries and content as topics.This is seen in the fact that Google uses core topicality systems as part of its ranking algorithm. So it’s somewhat curious that topicality research wasn’t mentioned as one of the uses, unless keyword clustering is considered part of that. Nevertheless, data analysis is a great use of AI.

Technical SEO

Technical SEO is a fantastic application of AI because that’s all about automating repetitive SEO tasks but also for assisting on making decisions about what to do. There’s lots of ways to do this, including by uploading a set of guidelines and/or charts and asking AI to analyze for specific things. Apps like Screaming Frog allow integration with OpenAI, so it’s leaving money and time on the table to not be investigating all the ways AI can integrate with tools as well as just asking it to analyze data.https://www.screamingfrog.co.uk/seo-spider/tutorials/how-to-crawl-with-chatgpt/

For example, one of the uses reported in the survey was for generating an internal linking strategy.

User Experience (UX) & Conversion Rate Optimization (CRO)

Another way ecommerce store owners are using AI is for improving the user experience and CRO.

The survey reports:

“AI-powered product recommendations

Chatbots for product discovery or customer support

CRO/UX audits based on user behavior”

Training & Education

Lastly, an increasing number of the ecommerce respondents reported using AI for generating training documentation for internal use and for creating customer documentation.

The survey reports:

“Less common but growing:

Learning how AI tools function

Using AI to create training material or SEO learning resources”

Not Using AI Or Limited Use

What was surprising is the amount of SEOs that are not using AI in a meaningful way. 31% of respondents said they are not using AI but are planning to, 3% of the survey respondents were digging their heels into the ground and flatly refusing to use AI in any way, while an additional 4% answered that they weren’t sure.

That makes a full 37% that aren’t using AI in any meaningful way. Looked at another way, 31% of respondents were getting ready to adopt AI into their workflow. Many managed WordPress hosting companies are integrating AI into their WordPress builder workflow as are some WordPress builders. AI can be integrated via WordPress SEO plugins as well. Wix has already integrated AI into their customer workflow through their proprietary Astro chatbot and companies like Shopify are also planning meaningful and useful ways to integrate AI.

The SEOFOMO survey makes it clear that AI is a significant part of the SEO and ecommerce workflow. Those who don’t use AI shouldn’t feel like they have to. But if you’re unsure how to integrate it, one way to think about it is to ask: what kinds of tasks would you hand off to an intern? Those are the kinds of tasks that AI excels at, enabling one worker to produce at a level five times greater than they could without using AI.

Read the SEOFOMO in ecommerce survey results:

The SEOFOMO Ecommerce SEO in 2025 Survey Results

Featured Image by Shutterstock/tete_escape

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Apr 17 2025

Google Says LLMs.Txt Comparable To Keywords Meta Tag via @sejournal, @martinibuster

Google’s John Mueller answered a question about LLMs.txt, a proposed standard for showing website content to AI agents and crawlers, downplaying its usefulness and comparing it to the useless keywords meta tag, confirming the experience of others who have used it.

LLMS.txt

LLMS.txt has been compared to as a Robots.txt for large language models but that’s 100% incorrect. The main purpose of a robots.txt is to control how bots crawl a website. The proposal for LLMs.txt is not about controlling bots. That would be superfluous because a standard for that already exists with robots.txt.

The proposal for LLMs.txt is generally about showing content to LLMs with a text file that uses the markdown format so that they can consume just the main content of a web page, completely devoid of advertising and site navigation. Markdown language is a human and machine readable format that indicates headings with the pound sign (#) and lists with the minus sign (-). LLMs.txt does a few other things similar to that functionality and that’s all it’s about.

What LLMs.txt is:

LLMs.txt is not a way to control AI bots.
LLMs.txt is a way to show the main content to AI bots.
LLMs.txt is just a proposal and not a widely used and accepted standard.

That last part is important because it relates to what Google’s John Mueller said:

LLMs.txt Is Comparable To Keywords Meta Tag

Someone started a discussion on Reddit about LLMs.txt to ask if anyone else shared their experience that the AI bots were not checking their LLMs.txt files.

They wrote:

“I’ve submitted to my blog’s root an LLM.txt file earlier this month, but I can’t see any impact yet on my crawl logs. Just curious to know if anyone had a tracking system in place,e or just if you picked up on anything going on following the implementation.

If you haven’t implemented it yet, I am curious to hear your thoughts on that.”

One person in that discussion shared that they host over 20,000 domains and that no AI agents or bots are downloading the LLMs.txt files, only niche bots like one from BuiltWith is grabbing those files.

The commenter wrote:

“Currently host about 20k domains. Can confirm that no bots are really grabbing these apart from some niche user agents…”

John Mueller answered:

“AFAIK none of the AI services have said they’re using LLMs.TXT (and you can tell when you look at your server logs that they don’t even check for it). To me, it’s comparable to the keywords meta tag – this is what a site-owner claims their site is about … (Is the site really like that? well, you can check it. At that point, why not just check the site directly?)”

He’s right, none of the major AI services, Anthropic, OpenAI, and Google, have announced support for the proposed LLMs.txt standard. So if none of them are actually using it then what’s the point?

Mueller also raises the point that an LLMs.txt file is redundant because why use that markdown file if the original content (and structured data) have already been downloaded? A bot that uses the LLMs.txt will have to check the other content to make sure it’s not spam so why bother?

Lastly, what’s to stop a publisher or SEO from showing one set of content in LLMs.txt to spam AI agents and another set of content for users and search engines? It’s too easy to generate spam this way, essentially cloaking for LLMs.

In that regard it is very similar to the keywords meta tag that no search engine uses because it would be too sketchy to trust a site that it’s really about those keywords and search engines are better and more sophisticated nowadays about parsing the content to understand what it’s about.

Read the LinkedIn discussion here:

LLM.txt – where are we at?

Featured Image by Shutterstock/Jemastock

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Apr 16 2025

AI Overviews: We Reverse-Engineered Them So You Don’t Have To [+ What You Need To Do Next]

This post was sponsored by DAC. The opinions expressed in this article are the sponsor’s own. Authors: Dan Lauer & Michael Goodman

Is the classic funnel model (TOFU-MOFU-BOFU) still relevant in an AI-driven SERP?

What kinds of queries trigger Google’s AI Overviews?

How can you structure content so that AI pulls your site into the response?

Do you really need to change your SEO strategy?

For years, SEO teams followed a familiar SEO playbook:

Optimize upper-funnel content to capture awareness,
mid-funnel content to drive consideration,
lower-funnel content to convert.

One page, one keyword, one intent.

But with the rise of ChatGPT, Perplexity, Copilot, Gemini, and now Google’s AI Mode, that linear model is increasingly outdated.

So, how do you move forward and keep your visibility high in modern search engine results pages (SERPs)?

We’ve reverse-engineered AI Overviews, so you don’t have to. Let’s dive in.

What We’ve Discovered Through Reverse Engineering Google’s AI Overviews (AIO)

From what we’re seeing across client industries and in how AI-driven results behave, the traditional funnel model – the idea of users moving cleanly from awareness to consideration to conversion – feels increasingly out of step with how people actually search.

How Today’s Search Users Actually Search

Today’s users jump between channels, devices, and questions.

They skim, abandon, revisit, and decide faster than ever.

AI Overviews don’t follow a tidy funnel because most people don’t either.

They surface multiple types of information at once, not because it’s smarter SEO, but because it’s closer to how real decisions get made.

AIOs & AI Mode Aren’t Just Answering Queries – They’re Expanding Them

Traditionally, SEO strategy followed a structured framework. Take a travel-related topic, for example:

Informational (Upper-Funnel) – “How to plan a cruise?”
Commercial (Mid-Funnel) – “Best cruise lines for families”
Transactional (lower-Funnel) – “Find Best Alaska Cruise Deals”

However, AI Overviews don’t stick to that structure.

Instead, they blend multiple layers of intent into a single, comprehensive response.

How AI Overviews Answer & Expand Search Queries

Let’s stay with the travel theme. A search for “Mediterranean cruise” might return an AI Overview that includes:

Best Time to go (Informational).
Booking Your Cruise (Commercial).
Cruise Lines (Navigational).

AI Mode Example for ‘Mediterranean Cruise’

What’s Happening Here?

In this case, Google isn’t just answering the query.

It anticipates what the user will want to know next, acting more like a digital concierge than a traditional search engine.

The AI Overview Test & Parameters

Source: Semrush & Google
Tested Data: 200 cruise-related informational queries

We started noticing this behavior showing up more often, so we wanted to see how common it actually is.

To get a clearer picture, we pulled 200 cruise-related informational queries from SEMrush and ran them through our custom-built AI SERP scraper. The goal was to see how often these queries triggered AI Overviews, and what kind of intent those Overviews covered.

The patterns were hard to miss:

88% of those queries triggered an AI Overview
More than half didn’t just answer the initial question.
52% mixed in other layers of intent, like brand suggestions, booking options, or comparisons, right alongside the basic information someone might’ve been looking for.

Using a different query related to Mediterranean Cruises, the AIO response acts as a travel agent, guiding the user on topics like:

How to fly,
Destinations with region,
Cruise prices,
Cruise lines that sail to that destination.

While it’s an Information non-brand search query, the AIO response is lower-funnel as well.

Again, less than half of the queries were matched intent.

Here are some examples of queries that were identified as Informational and provided only the top-of-funnel response without driving the user further down the funnel.

The Verdict

Even when someone asks a simple, top-of-funnel question, AI is already steering them toward what to do next, whether that’s comparing prices, picking a provider, or booking a trip.

What Does This Mean for SEO Strategies Moving Forward?

If AI Overviews and AI Mode are blending intent types, content, and SEO strategies need to catch up:

It’s no longer enough to rank for high-volume informational keywords. If your content doesn’t address multiple layers of intent, AI will fill the gaps with someone else’s content.
SEO teams need to analyze how AI handles their most important queries. What related questions is it pulling in? Are those answers coming from your site or your competitors?
Think beyond keyword volume. Long-tail queries may have lower search traffic, but they often align better with AI-cited content. Structure your pages with clear headings, bullets, and concise, helpful language—that’s what AI models prefer to surface.

The Future of SEO in an AI World: Hybrid Intent Optimization

The fundamentals of technical and on-page SEO still matter. But if your content is still built around single keywords and single intent types, you’re likely to lose visibility as AI continues to reshape the SERP.

The brands that adapt to this shift by creating content that mirrors the blended, fast-moving behavior of actual users are the ones that will continue to own key moments across the funnel, even as the funnel itself evolves.

As AI transforms search behavior, it‘s crucial to adapt your SEO strategies accordingly. At DAC, we specialize in aligning your content with the latest search trends to enhance visibility and engagement. Reach out to us today to future-proof your strategy with our award-winning TotalSERP approach and stay ahead in the evolving digital landscape.

https://www.dacgroup.com/” class=”btn-learn-more button-green medium-size”>Optimize Your SEO For AI Search, Now

Image Credits

Featured Image: Image by DAC. Used with permission.

In-Post Image: Images by DAC. Used with permission.

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Apr 15 2025

Google Confirms That Structured Data Won’t Make A Site Rank Better via @sejournal, @martinibuster

Google’s John Mueller answered a question on Bluesky about whether structured data helps with SEO, which may change how some people think about it.

Schema.org Structured Data

When SEOs talk about structured data they’re talking about Schema.org structured data. There are many kinds of structured data but for SEO purposes only Schema.org structured data matters.

Does Google Use Structured Data For Ranking Purposes?

The person starting the discussion first posted that they were adding structured data to see if it helps with SEO.

Mueller’s first post was a comment about the value of preparation:

“Yes, and also no. I love seeing folks stumble into the world of online marketing, search engines, and all that, but reading up on how things technically work will save you time & help you focus.”

The original poster responded with a question:

“In your experience, how has it helped?”

That’s when Mueller gave his answer:

“(All of the following isn’t new, hence the meme.) Structured data won’t make your site rank better. It’s used for displaying the search features listed in developers.google.com/search/docs/… . Use it if your pages map to & are appropriate for any of those features.”

Google Only Uses Structured Data For Rich Results

It might seem confusing that structured data doesn’t help a site rank better but it makes more sense to think about it as something that makes a site eligible for rich results. In the context of AI Search results, Google uses regularly indexed data from websites and because AI search results are a search feature, it may rely on the documented structured data for search related features (read more about that here: Google Confirms: Structured Data Still Essential In AI Search Era.)

The main points about structured data in the context of AI search is that according to what was shared at a recent Search Central Live (hat tip to Aleyda Solis):

“Structured data is critical for modern search features

Check the documentation for supported types

Structured data is efficient,
…for computers easy to read,
… and very precise”

In a nutshell, for the context of AI Search:
Structured data supports search features and AI Search is an AI feature. AI search also relies on the regular search index apart from the Schema.org structured data.

How Google Uses Structured Data In Search Features

Google uses only a fraction of the available Schema.org structured data. There are currently over 800 Schema.org structured data types and Google only uses around 30 types for which it publishes structured data documentation for required properties for each structured data type and other guidelines and requirements.

The only use Google has for structured data is to collect information in a machine readable format so that it can then use the information for displaying rich results, which can be seen for recipes, reviews, displaying website information in carousel format, and even to enable users to buy books directly from the search results.

Adding Schema.org structured data doesn’t guarantee that Google will display the site with a rich results feature in search. It only makes a site eligible to be displayed in rich results. Adding non-documented forms of Schema.org structured data won’t affect search optimization for a site because Google ignores all but the roughly thirty structured data types.

Read the original discussion on Bluesky:

Adding structured data to see if it helps with SEO

Featured Image by Shutterstock/ViDI Studio

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Apr 15 2025

AI & SEO-Driven Content Marketing: How To Calculate True ROI for B2B Companies in 2025

This post was sponsored by Heeet. The opinions expressed in this article are the sponsor’s own.

How do you calculate the true cost of SEO content production?

Are you overspending or underspending on SEO compared to performance?

Can you connect SEO-driven awareness to pipeline and revenue?

How do you make SEO efforts more visible to your C-suite?

If you aren’t sure, that’s okay.

You may simply lack the tools to measure the actual impact of SEO on revenue.

So, let’s dive in and:

Break down the true steps to B2B conversion.
Highlight the tools to calculate the true ROI of your SEO-driven content in 2025.
Look past the simplified first and last-touch approach to attribution.
Leverage the need for multitouch solutions that track engagement with SEO content throughout the buyer’s journey.

Can I Connect SEO To Revenue?

Yes, you can connect SEO to revenue.

Why Should I Connect SEO To Revenue?

SEO plays a large role in future conversions.

In fact, SEO helps prospects discover your brand, tool, or company.

SEO also helps provide easy-to-discover content with informational intent, which helps to nurture a prospective lead into a sale.

Your prospect’s journey:

Starts at the first time they find your optimized webpage on the search engine results page (SERP).
Moves into nurture, where your B2B prospects typically perform months of extensive product research via traditional searches and AI results before a sale is closed.

The fact that informative content is found on SERPs is due to SEO.

But how is this tracked? How do you know which non-conversion pages are:

Part of the user journey?
Part of the overall ROI?

How Do I Tie SEO To Company Revenue?

Luckily, your C-suite likely recognizes the need for SEO content.

They are prepared to invest in a strategy incorporating AI search.

However, you need tools that validate the investment and clearly showcase it for your higher-ups.

How To Keep Revenue High When SERPs Are Changing

Gartner predicts that traditional search engine volume will drop 25% by 2026 and flow directly to AI chatbots and agents.

As AI continues to accelerate the evolution of SEO, it’s critical to ensure that high-performing pages:

Continue to rank in traditional SERPs.
Appear in Google’s AI overviews.
Get referenced by the Gen AI tools your audience relies on.
They are tracked, so these visits are attributed to a sale.

That’s why you need to understand why certain content is picked up by AI tools and the cost of generating the content to calculate the true ROI of your SEO.

Step 1. How To Create Content That Gets Seen In Traditional Search & AI Overviews

With the shift in consumer search behavior, your first step is to create, optimize, and measure the ROI of content sourced by leading AI tools.

That means appearing in AI Overviews and AI Answers that contain list-based content and product comparisons.

Search Your Brand & See What Each AI Tool Recommends

That’s the first step to determining whether your content or your competitor’s stands out.

Give these prompts a try:

What is the best solution for…
Give me the top tools for…
Best alternative to…
Is [competitor] solution better than…

Optimize Your Existing Content & Strategy To Feed AI’s Answer Base

The next step is optimizing existing content and adjusting your strategy so that you write copy that gives AI the answers it’s looking for.

With that said, following traditional SEO strategies and best practices championed by Google should help.

Just like traditional search, AI tools also favor:

Proper site and article structure with explicit metadata and semantic markup.
Content with lists and bullet points that are easier to scan.
Websites optimized for speed.
Updated content, keeping things fresh with context.
Content with backlinks from high-quality publications.
FAQ sections.
Mobile-responsive websites with indexable content when pulling sources to provide an answer.

These factors give your content more authority in your industry, just like the content outside your website that Google and LLMs look for to find answers from, such as videos on YouTube, reviews on G2, and conversations on Reddit forums.

Publishing enough quality content for all those channels to optimize for AI and be visible in traditional search is no small task. It requires substantial human resources, SEO tools, and time.

Step 2. Understand All Aspects Of The Real Cost Of SEO Content In 2025

SEO is a long game, especially in B2B, where the path from first click to purchase can span weeks or months and involve multiple touchpoints.

And now, with AI influencing how content is discovered, the cost of doing SEO well has increased.

To accurately assess the cost of SEO-driven content in 2025, you need to go beyond production budgets and organic traffic. Here’s how:

Break Down Your True SEO Investment

Start by identifying all the resources that go into content creation and maintenance:

People: Writers, designers, SEOs, developers, and editors.
Tools: SEO platforms, content optimization tools, keyword research databases, analytics software.
Distribution: Paid support for SEO content, social promotion, and email newsletters.
Maintenance: Refreshing old content, updating links, and improving page experience.

Monitor Content Performance Over Time

Track the performance of each piece of content using more than just rankings:

Organic traffic (from both traditional search and AI surfaces).
Time on page and engagement metrics.
Cost per lead and pipeline contribution (if possible).
Assisted conversions across all touchpoints.

Map Content to Buyer Journey Stages

Content doesn’t just convert, it nurtures. Tie content assets to specific stages:

Top-of-funnel (education, discovery).
Mid-funnel (comparison, product evaluation).
Bottom-of-funnel (case studies, demos).

Even if content isn’t the final touchpoint, it plays a role. Traditional tools miss this.

Adjust, Monitor & Pivot

No single metric will tell the full story. Instead:

Adjust: Re-optimize content based on AI overview visibility, CTR, and engagement.
Monitor: Watch how users arrive from search vs. AI sources.
Pivot: Invest more in formats and topics that show traction across both human and AI audiences.

Without full-funnel attribution, even the most engaged content may look like a cost center instead of a revenue driver.

That’s why accurate measurement, aligned with total investment and the full buyer journey, is critical to understanding the real ROI of your SEO content in 2025.

However, we know that:

AI Overviews and similar answer engines also play a big role in education and nurturing.
Attributing a sale to content read on an untrackable AI Overview is impossible, but it’s happening.

This is where the calculation gets difficult.

Step 3. Incorporate Multi-Touch Attribution To Your Revenue Calculations

Now that we’re here, you’re beginning to understand how tricky it is to tie ROI to AI Overview responses that nurture your prospects.

How do you accurately determine the cost?

Some people are creating their own attribution models to calculate ROI.

Most people are using tools that are built specifically for this new calculation.

The only way to accurately calculate cost in B2B SEO is to capture the engagement with content throughout the buyer journey, which conventional attribution models don’t credit.

Incorporate These Blindspots: Pre-Acquisition & The Post-Lead Journey

Another substantial blind spot in SEO measurement occurs when companies focus exclusively on pre-acquisition activities, meaning everything that happens before a lead is added to your CRM.

Consider the typical journey enterprise clients take in an account-based marketing approach:

After multiple organic searches, a prospect converts into a lead from direct traffic.
After being qualified as an SQL, they’re included in an email sequence that they never respond to, but return through a Google Ads campaign promoting a white paper.
They download it from an organic search visit and continue reading more blog articles to understand your product and the outcomes they hope to achieve.

Can your marketing team track how each channel (direct, paid search, and organic) influenced the deal throughout the sales process?

Multitouch attribution tools allow marketers to finally link SEO content to tangible business outcomes by tracking what SEO-driven content leads interacted with before a sale.

Heeet Makes SEO ROI Calculations Easy

After years of wrestling with these challenges, we built Heeet to fill the void: an end-to-end attribution solution that connects SEO efforts and interactions generated from content marketing to revenue by highlighting their impact throughout the sales cycle within Salesforce.

Our proprietary cookieless tracking solution collects more data, ensuring your decisions are based on complete, unbiased insights rather than partial or skewed information.

Traditional SEO measurement often relies on first-click or last-click attribution, which fails to capture SEO’s entire influence on revenue. Heeet places SEO on a level playing field by providing full-funnel attribution that tracks SEO’s impact at every customer journey stage.

We help marketers determine whether SEO-driven content is the first touchpoint, one of the many intermediary interactions along the lengthy B2B sales cycle, or the final conversion leading to a sale to pinpoint SEO’s cumulative influence on your pipeline.

Screenshot from Google, April 2025

Heeet actively tracks every touchpoint, ensuring that the actual impact of SEO is neither underestimated nor misrepresented.

Rather than neglecting SEO’s role when a prospect converts through another channel, Heeet delivers a complete view of how different personas in the buying committee interact with each piece of content and where they’re converting. This empowers businesses to make informed, data-driven SEO strategies and investment decisions.