Yoast SEO announced a new feature that enables SEO and readability analysis within Google Docs, allowing publishers and teams to integrate search marketing best practices at the moment content is created instead of as an editing activity that comes after the fact.

Two Functionalities Carry Over To Google Docs

Yoast SEO is providing SEO optimization and readability feedback within the Google Docs editing environment.

SEO feedback consists of the familiar traffic light system that offers visual confirmation that the content is search optimized according to Yoast SEO’s content metrics on keywords, structure and optimization.

The readability analysis offers feedback on paragraph structure, sentence length, and headings to help the writer create engaging content, which is increasingly important in today’s content-first search engines that prioritize high quality content.

According to Yoast SEO:

“The Google Docs add-on tool is available to all Yoast SEO Premium subscribers, offering them a range of advanced optimization tools. For those not yet subscribed to Yoast Premium, the add-on is also available as a single purchase, making it accessible to a broader audience.

For those managing multiple team members, additional Google accounts can be linked for just $5 a month per account or annually for a 10% discount ($54). This flexibility ensures that anyone who writes content and in-house marketing teams managing multiple projects can benefit from high-quality SEO guidance.”

This new offering is an interesting step for Yoast SEO. Previously known as the developer of the Yoast SEO WordPress plugin, it’s expanded to Shopify and now it’s breaking out of the CMS paradigm to encompass the optimization process that happens before the content gets into the CMS.

Read more at the Yoast SEO:

Optimize your content directly in Google Docs with Yoast SEO

https://www.searchenginejournal.com/yoast-seo-functionality-is-now-available-within-google-docs/550782/

Internet Marketing Ninjas has been acquired by SEO consultancy Previsible, an industry leader co-founded by a former head of SEO at eBay. The acquisition brings link building and digital PR expertise to Previsible. While both companies are now under shared ownership, they will continue to operate as separate brands.

Internet Marketing Ninjas

Founded in 1999 by Jim Boykin as We Build Pages, the Internet Marketing Ninjas consultancy story is one of steady innovation and pivoting in response to changes brought by Google. In my opinion, Jim’s talent was his ability to scale the latest tactics in order to offer the services to a large number of clients, and his ability to nimbly ramp up new strategies at scale in response to changes at Google. The names of the people he employed are a who’s who of legendary marketers.

In the early days of SEO, when reciprocal linking was the rage, it was Jim Boykin who became known as a bulk provider of that service, and when directories became a hot service, he was able to scale that tactic and make it easy for business owners to pick up links fast. Over time, the ability to provide links became increasingly harder, and yet Jim Boykin kept on innovating with strategies that made it easy for customers to attain links. I’ve long been an admirer of Boykin because he is the rare individual who can be both a brilliant SEO strategizer and a savvy business person.

Jordan Koene, CEO and co-founder at Previsible, commented:

“Previsible believes that the future of discovery and search lies at the intersection of trust and visibility. Our acquisition of Internet Marketing Ninjas brings one of the most experienced trusted-link and digital PR teams into our ecosystem. As search continues to evolve beyond keywords into authority, reputation, and real-world relevance, link strategies are essential for brands to stand out.”

Previsible and Internet Marketing Ninjas will continue to operate as separate brands, leveraging Boykin’s existing team for their expertise.

Jim Boykin explained:

“Combining forces with Previsible kicks off an incredibly exciting new chapter for Internet Marketing Ninjas. We’re not just an SEO company anymore, we’re at the forefront of the future of digital visibility. Together with Previsible, we’re leading the charge in both search and AI-driven discovery.

By merging decades of deep SEO expertise with bold, forward-thinking innovation, we’re meeting the future of online marketing head-on. From Google’s AI Overviews to ChatGPT and whatever comes next, our newly united team is perfectly positioned to help brands get found, build trust, and be talked about across the entire digital landscape. I’m absolutely stoked about what we’re building together and how we’re going to shape the next era of internet marketing.”

Previsible’s acquisition of Internet Marketing Ninjas merges long-standing experience in link building while retaining the distinct brands and teams that make each consultancy a search marketing leader. The partnership will enable clients to increase visibility by bringing the expertise of both companies together.

Read more at Internet Marketing Ninjas:
Internet Marketing Ninjas Has Been Acquired by and Is Merging With Previsible

https://www.searchenginejournal.com/internet-marketing-ninjas-acquired-by-previsible/550742/

There’s no one-size-fits-all answer when it comes to deciding how much of your marketing budget should go toward SEO versus PPC.

But that doesn’t mean the decision should be based on gut instinct or what your competitors are doing.

Marketing leaders are under more pressure than ever to show a return on every dollar spent.

So, it’s not about choosing one over the other. It’s about finding the right balance based on your goals, your timelines, and what kind of results the business expects to see.

This article walks through how to think about budget allocation between SEO and PPC with a focus on what kind of output you can reasonably expect for your spend.

What You’re Actually Paying For

When you spend money on PPC, you’re buying immediate visibility.

Whether it’s Google Ads, Microsoft Ads, or paid social, you’re paying for clicks, impressions, and leads right now.

That cost is largely predictable and better to forecast. For example, if your cost-per-click (CPC) is $3 and your budget is $10,000, you can expect about 3,300 clicks.

PPC spend can be directly tied to pipeline, which is why it’s often favored by performance-driven teams.

With SEO, you’re investing in long-term growth. You’re paying for content, technical fixes, site structure improvements, and link acquisition.

But you don’t pay for clicks or impressions. Once rankings improve, those clicks come organically.

The upside is compounding growth and reduced cost per lead over time.

The downside? It can take months to see meaningful impact, and the cost-to-output ratio is harder to predict.

It’s also worth noting that PPC costs often increase with competition, while SEO costs tend to remain relatively stable over time. That can make SEO more scalable in the long term, especially for brands in high-CPC industries.

How Urgency And Goals Influence Budget Splits

If you need leads or traffic now, PPC should probably get the bulk of your short-term budget.

Launching a new product? Trying to meet quarterly goals? Paid search and social can give you the volume you need pretty quickly.

But if you’re trying to reduce customer acquisition cost (CAC) in the long run or improve visibility in organic search to support brand awareness, SEO deserves more attention. It builds value over time and often pays dividends past the life of your campaign.

Many brands start with a 70/30 or 60/40 split favoring PPC, then shift the mix as organic efforts gain traction.

Just make sure you set clear expectations: SEO is not a quick fix, and over-promising short-term gains can backfire when the board wants results next quarter.

If you’re rebranding, expanding into new markets, or supporting a product launch, a heavier upfront PPC investment makes sense. But brands that already rank well organically or have strong content foundations can afford to rebalance the mix in favor of SEO.

Why Organic Traffic Is Getting Harder To Defend

One emerging challenge for organic marketing is the rise of AI Overviews in Google Search. More brands are seeing a dip in organic traffic even when they maintain strong rankings.

Why?

Because the search experience is shifting. AI-generated summaries are now answering questions directly on the results page, often pushing traditional organic listings further down.

That means your SEO strategy can’t just be about rankings anymore. You need to invest in content that earns visibility in AI Overviews, featured snippets, and other enhanced search features.

This may involve rethinking how content is structured, focusing more on schema markup, FAQs, and direct-answer formats that AI models tend to surface.

In practical terms, your SEO budget should now include:

• Structured content planning built around entity-based search.
• Technical SEO improvements like schema and page speed.
• Multimedia content like images and videos, which AI often pulls into results.
• Continual refresh of older content to maintain relevance in evolving search formats.

This shift doesn’t mean SEO is no longer worth it. It means you need to be more strategic in how you spend.

Ask your SEO partner or in-house team how they’re adapting to AI search changes, and make sure your budget reflects that evolution.

Budget Planning Based On Realistic Outputs

Let’s put this into numbers. Say you have a $100,000 annual digital marketing budget.

Putting $80,000 toward PPC might get you 25,000 paid clicks and 500 conversions (based on a fictional $3.20 CPC and 2% conversion rate).

The remaining $20,000 on SEO might buy you four high-quality articles a month, technical clean-up work, and backlink outreach.

If done well, this might start showing traction in three to six months and bring in sustained traffic over time.

The key is to model your budget around what’s actually possible for each channel, not just what you hope will happen. SEO efforts often have a longer lag time, but PPC campaigns can run out of gas as soon as you turn off the spend.

You should also budget for maintenance and reinvestment. Even strong SEO performance requires fresh content and updates to keep rankings.

Similarly, PPC campaigns need regular optimization, creative testing, and bid adjustments to stay efficient.

You should also plan for budget allocation across different campaign types: brand vs. non-brand, search vs. display, and prospecting vs. retargeting.

Each serves a different purpose, and over-investing on one without supporting the others can limit growth.

For example, allocating part of your PPC budget to retargeting warm audiences can drastically improve efficiency compared to cold prospecting alone.

While branded search often delivers low-cost conversions, it shouldn’t be your only area of investment if you’re trying to scale.

What To Communicate To Leadership

Leadership wants to know two things: how much are we spending, and what are we getting in return?

A mixed SEO and PPC strategy gives you the ability to answer both.

PPC provides short-term wins you can report on monthly.

SEO builds long-term momentum that pays off in quarters and years.

Explain that PPC is more like a faucet you control. SEO is more like building your own well. Both are valuable.

But if you only have one or the other, you’re either stuck renting traffic or waiting too long to see the impact.

Board members and non-marketing executives often prefer hard numbers. So, when proposing a budget mix, include projected costs per acquisition, estimated traffic volumes, and timelines for ramp-up.

Make it clear where each dollar is going and what kind of return is expected.

If possible, create a model that shows various scenarios. For example, what a 50/50 vs. 70/30 SEO/PPC split might look like in terms of conversions, traffic, and cost per lead over time.

Visuals help ground the conversation in data rather than preference.

Choosing The Right Metrics For Each Channel

One challenge with mixed-channel budget planning is deciding which key performance indicator (KPI) to prioritize.

PPC is easier to measure in terms of direct return on investment (ROI), but SEO plays a broader role in business success.

For PPC metrics, you may want to focus on KPIs like:

• Impression share.
• Conversion rate.
• Cost per acquisition (CPA).
• Return on ad spend (ROAS).

For SEO metrics, you may want to focus on:

• Organic traffic growth over time.
• Ranking improvements.
• Page engagement.
• Assisted conversions.

When reporting to leadership, show how the two channels complement each other.

For example, paid search might drive immediate clicks, but your top-converting landing page could rank organically and reduce spend over time.

When To Adjust Your Budget Mix

Your initial budget allocation isn’t set in stone. It should evolve based on performance data, market shifts, and internal needs.

If PPC costs rise but conversion rates drop, that could be a cue to pull back and invest more in organic.

If you’re seeing strong rankings but low engagement, it may be time to shift some SEO funds into conversion rate optimization (CRO) or paid retargeting.

Seasonality and campaign cycles also matter. Retailers may lean heavily on PPC during Q4, while B2B companies might invest more in SEO during longer sales cycles.

Set quarterly review points where you re-evaluate performance and make adjustments. That level of agility shows leadership you’re making informed decisions, not just sticking to arbitrary ratios.

Avoiding Common Budget Mistakes

Some companies go all-in on SEO, expecting miracles. Others burn through paid budgets with nothing left to sustain organic efforts. Both approaches are risky.

A healthy mix means budgeting for:

• Immediate lead gen (PPC).
• Long-term traffic growth (SEO).
• Regular testing and performance analysis.

Don’t forget to budget for what happens after the click: landing page development, CRO, and reporting tools that tie it all together.

Another mistake is treating SEO as a one-time project instead of an ongoing investment. If you only fund it during a site migration or a content sprint, you’ll lose momentum.

Same goes for PPC: Without a proper landing page experience or conversion tracking, even high-performing ads won’t deliver meaningful results.

Balancing Short-Term Wins With Long-Term Growth

There is no universal perfect split between SEO and PPC. But there is a perfect mix for your goals, stage of growth, and available resources.

Take the time to assess what you actually need from each channel and what you can realistically afford. Make sure your projections align with internal timelines and expectations.

And most importantly, keep reviewing your mix as performance data rolls in. The right budget allocation today might look very different six months from now.

Smart marketing leaders don’t choose sides. They choose what makes sense for the business today, and build flexibility into their strategy for tomorrow.

More Resources:

Featured Image: Jirapong Manustrong/Shutterstock

https://www.searchenginejournal.com/how-to-get-the-perfect-budget-mix-for-seo-and-ppc/548300/

SEO died a thousand times only this year, and the buzzword that resonates across every boardroom (and let’s be honest, everywhere else) is “AI.”

With Google releasing several AI-powered views over the past year and a half, along with the latest take on its own SearchGPT rival AI Mode, we are witnessing a traffic erosion that is very hard to counteract if we stay stuck in our traditional view of our role as search professionals.

And it is only natural that the debate we keep hearing is the same: Is AI eventually going to take our jobs? In a stricter sense, it probably will.

SEO, as we know it, has transformed drastically. It will keep evolving, forcing people to take on new skills and have a broader, multichannel strategy, along with clear and prompt communication to stakeholders who might still be confused about why clicks keep dropping while impressions stay the same.

The next year is expected to bring changes and probably some answers to this debate.

But in the meantime, I was able to draw some predictions, based on my own study investigating humans’ ability to discern AI, to see if the “human touch” really has an advantage over it.

Why This Matters For Us Now

Knowing if people can recognize AI matters for us because people’s behavior changes when they know they’re interacting with it, as compared to when they don’t.

A 2023 study by Yunhao Zhang and Renée Richardson Gosline compared content created by humans, AI, and hybrid approaches for marketing copy and persuasive campaigns.

What they noticed is that when the source was undisclosed, participants preferred AI-generated content, a result that was reversed when they knew how the content was created.

It’s like the transparency on using AI added a layer of diffidence to the interaction, rooted in the common mistrust that is reserved for any new and relatively unknown experience.

At the end of the day, we have consumed human-written content for centuries, but generative AI has been scaled only in the past few years, so this wasn’t even a challenge we were exposed to before.

Similarly, Gabriele Pizzi from the University of Bologna showed that when people interact with an AI chatbot in a simulated shopping environment, they are more likely to consider the agent as competent (and, in turn, trust it with their personal information) when the latter looks more human as compared to “robotic.”

And as marketers, we know that trust is the ultimate seal not only to get a visit and a transaction, but also to form a lasting relationship with the user behind the screen.

So, if recognizing AI content changes the way we interact with it and make decisions, do we still retain the human advantage when AI material gets so close to reality that it is virtually undistinguishable?

Your Brain Can Discriminate AI, But It Doesn’t Mean We Are Infallible Detectors

Previous studies have shown that humans display a feeling of discomfort, known as the uncanny valley, when they see or interact with an artificial entity with semi-realistic features.

How this negative feeling is manifested physiologically with higher activity of our sympathetic nervous system (the division responsible for our “fight or flight” response) before participants can verbally report on or even be aware of it.

It’s a measure of their “gut feeling” towards a stimulus that mimics human features, but does not succeed in doing so entirely.

The uncanny valley phenomenon arises from the fact that our brain, being used to predicting patterns and filling in the blanks based on our own experience, sees these stimuli as “glitches” and spots them as outliers in our known library of faces, bodies, and expressions.

The deviation from the norm and the uncertainty in labeling these “uncanny” stimuli can be triggering from a cognitive perspective, which manifests in higher electrodermal activity (shortened as EDA), a measure of psychological arousal that can be measured with electrodes on the skin.

Based on this evidence, it is realistic to hypothesize that our brain can spot AI before making any active discrimination, and that we can see higher EDA in relation to faces generated with AI, especially when there is something “off” about them.

It is unclear, though, at what level of realism we stop displaying a distinctive response, so I wanted to find that out with my own research.

Here are the questions I set up to answer with my study:

1. Do we have an in-built pre-conscious “detector” system for AI, and at what point of realistic imitation does it stop responding?
2. If we do, does it guide our active discrimination between AI and human content?
3. Is our ability to discriminate influenced by our overall exposure to AI stimuli in real life?

And most of all, can any of the answers to these questions predict what are the next challenges we’ll face in search and marketing?

To answer these questions, I measured the electrodermal activity of 24 participants between 25 and 65 years old as they were presented with neutral, AI-generated, and human-generated images, and checked for any significant differences in responses to each category.

My study ran in three phases, one for each question I had:

1. A first task where participants visualized neutral, AI, and human static stimuli on a screen without any actions required, while their electrodermal activity was recorded. This was intended to measure the automatic, pre-conscious response to the stimuli presented.
2. A second behavioral task, where participants had to press a button to categorize the faces that they had seen into AI- vs. human-generated, as fast and accurately as they could, to measure their conscious discrimination skills.
3. A final phase where participants declared their demographic range and their familiarity with AI on a self-reported scale across five questions. This gave me a self-reported “AI-literacy” score for each participant that I could correlate with any of the other measures obtained from the physiological and behavioral tasks.

And here is what I found:

• Participants showed a significant difference in pre-conscious activation between conditions, and in particular, the EDA was significantly higher for human faces rather than AI faces (both hyper-realistic and CGI faces). This would support the hypothesis that our brain can tell the difference between AI and human faces before we even initiate a discrimination task.
• The higher activation for human faces contrasts with the older literature showing higher activation for uncanny valley stimuli, and this could be related to either our own habituation to CGI visuals (meaning they are not triggering outliers anymore), or the automatic cognitive effort involved in trying to extrapolate the emotion of human neutral faces. As a matter of fact, the limitation of EDA is that it tells us something is happening in our nervous system, but it doesn’t tell us what: higher activity could be related to familiarity and preference, negative emotional states, or even cognitive effort, so more research on this is needed.
• Exposure and familiarity with AI material correlated with higher accuracy when participants had to actively categorize faces into AI-generated and human, supporting the hypothesis that the more we are exposed to AI, the better we become at spotting subtle differences.
• People were much faster and accurate in categorizing stimuli of the “uncanny valley” nature into the AI-generated bucket, but struggled with hyper-realistic faces, miscategorizing them as human faces in 22% of cases.
• Active discrimination was not guided by pre-conscious activation. Although a difference in autonomous activity can be seen for AI and human faces, this did not correlate with how fast or accurate participants were. In fact, it can be argued that participants “second-guessed” their own instincts when they knew they had to make a choice.

And yet, the biggest result of all was something I noticed on the pilot I ran before the real study: When the participant is familiar with the brand or the product presented, it’s how they feel about it that guides what we see at the neural level, rather than the automatic response to the image presented.

So, while our brain can technically “tell the difference,” our emotions, familiarity with the brand, the message, and expectations are all factors that can heavily skew our own attitude and behavior, essentially making our discrimination (automatic or not) almost irrelevant in the cascade of evaluations we make.

This has massive implications not only in the way we retain our existing audience, but also in how we approach new ones.

We are now at a stage where understanding what our user wants beyond the immediate query is even more vital, and we have a competitive advantage if we can identify all of this before they explicitly express their needs.

The Road To Survival Isn’t Getting Out Of The Game. It’s Learning The New Rules To Play By

So, does marketing still need real people?

It definitely does, although it’s hard to see that now that every business is ignited by the fear of missing out on the big AI opportunity and distracted by new shiny objects populating the web every day.

Humans thrive on change – that’s how we learn and grow new connections and associations that help us adapt to new environments and processes.

Ever heard of the word neuroplasticity? While it might just sound like a fancy term for learning, it is quite literally the ability of your brain to reshape as a result of experience.

That’s why I think AI won’t take our jobs. We are focusing on AI’s fast progress in the ability to ingest content and recreate outputs that are virtually indistinguishable from our own, but we are not paying attention to our own power of evolving to this new level field.

AI will keep on moving, but so will the needle of our discernment and our behavior towards it, based on the experiences that we build with new processes and material.

My results already indicate how familiarity with AI plays a role in how good we are at recognizing it, and in a year’s time, even the EDA results might change as a function of progressive exposure.

Our skepticism and diffidence towards AI is rooted in the unknown sides of it, paired with a lot of the misuse that we’ve seen as a by-product of a fast, virtually unregulated growth.

The nature of our next interactions with AI will shape our behavior.

I think this is our opportunity as an industry to create valuable AI-powered experiences without sacrificing the quality of our work, our ethical responsibilities toward the user, and our relationship with them. It’s a slower process, but one worth undertaking.

So, even if, at the beginning, I approached this study as a man vs. the machine showdown, I believe we are heading toward the man and the machine era.

Far from the “use AI for everything” approach we tend to see around, below is a breakdown of where I see a (supervised) integration of AI to our job unproblematic, and where I think it still has no space in its current state.

Use: Anything That Provides Information, Facilitates Navigation, And Streamlines User Journeys

• For example, testing product descriptions based on the features that already reside in the catalog, or providing summaries of real users’ reviews that highlight pros and cons straight away.
• Virtual try-ons and enabling recommended products based on similarity.
• Automating processes like identifying internal link opportunities, categorizing intent, and combining multiple data sources for better insights.

Avoid: Anything That’s Based On Establishing A Connection Or Persuading The User

• This includes any content that fakes expertise and authority in the field. The current technology (and the lack of regulation) even allows for AI influencers, but bear in mind that your brand authenticity is still your biggest asset to preserve when the user is looking to convert. The pitfalls of deceiving them when they expect organic content are greater than just losing a click. This is the work you can’t automate.
• Similarly, generating reviews or user-generated content at scale to convey legitimacy or value. If you know this is what your users want to get more information on, then you cannot meet their doubts with fake arguments. Gaming tactics are short-lived in marketing because people learn to discern and actively avoid them once they realize they are being deceived. Humans crave authenticity and real peer validation of their decisions because it makes them feel safe. If we ever reach a point where, as a collective, we feel we can trust AI, then it might be different, but that’s not going to happen when most of its current use is dedicated to tricking users into a transaction at all cost, rather than providing the necessary information they need to make an informed decision.
• Replacing experts and quality control. If it backfired for customer-favorite Duolingo, it will likely backfire for you, too.

The New Goals We Should Be Setting

Here’s where a new journey starts for us.

The collective search behavior has already changed not only as a consequence of any AI-powered view on the SERP that makes our consumption of information and decision-making faster and easier, but also as a function of the introduction of new channels and forms of content (the “Search Everywhere” revolution we hear all about now).

This brings us to new goals as search professionals:

• Be omnipresent: It’s now the time to work with other channels to improve organic brand awareness and be in the mind of the user at every stage of the journey.
• Remove friction: Now that we can get answers right off the search engine results page without even clicking to explore more, speed is the new normal, and anything that makes the journey slower is an abandonment risk. Getting your customers what they want straight off the bat (being transparent with your offer, removing unnecessary steps to find information, and improving user experience to complete an action) prevents them from going to seek better results from competitors.
• Preserve your authenticity: Users want to trust you and feel safe in their choices, so don’t fall into the hype of scalability that could harm your brand.
• Get to know your customers deeper: Keyword data is no longer enough. We need to know their emotional states when they search, what their frustrations are, and what problems they are trying to solve. And most of all, how they feel about our brand, our product, and what they expect from us, so that we can really meet them where they are before a thousand other options come into play.

We’ve been there before. We’ll adapt again. And I think we’ll come out okay (maybe even more skilled) on the other side of the AI hype.

More Resources:

Featured Image: Stock-Asso/Shutterstock

https://www.searchenginejournal.com/this-is-why-ai-wont-take-your-job-yet/548765/

The Movement For An Open Web and other organizations filed a legal challenge against Google, alleging harm to UK news publishers. The crux of the legal filing is the allegation that Google’s AI Overviews product is using news content as part of its summaries and for grounding AI answers, but not allowing publishers to opt out of that use without also opting out of appearing in search results.

The Movement For An Open Web (MOW) in the UK published details of a complaint to the UK’s Competition and Markets Authority (CMA):

“Last week, the CMA announced plans to consult on how to make Google search fairer, including providing “more control and transparency for publishers over how their content collected for search is used, including in AI-generated responses.” However, the complaint from Foxglove, the Alliance and MOW warns that news organisations are already being harmed in the UK and action is needed immediately.

In particular, publishers urgently need the ability to opt out of Google’s AI summaries without being removed from search altogether. This is a measure that has already been proposed by other leading regulators, including the US Department of Justice and the South African Competition Commission. Foxglove is warning that without immediate action, the UK – and its news industry – risks being left behind, while other states take steps to protect independent news from Google.

Foxglove is therefore seeking interim measures to prevent Google misusing publisher content pending the outcome of the CMA’s more detailed review.”

Reuters is reporting on an EU antitrust complaint filed in Brussels seeking relief for the same thing:

“Google’s core search engine service is misusing web content for Google’s AI Overviews in Google Search, which have caused, and continue to cause, significant harm to publishers, including news publishers in the form of traffic, readership and revenue loss.”

Publishers And SEOs Critical Of AI Overviews

Google is under increasing criticism from the publisher and the SEO community for sending fewer clicks to users, although Google itself insists it is sending more traffic than ever. This may be one of those occasions where the phrase “let the judge decide” describes where this is all going, because there are no signs that Google is backing down from its decade-long trend of showing fewer links and more answers.

Featured Image by Shutterstock/nitpicker

https://www.searchenginejournal.com/google-ai-overviews-target-of-legal-complaints-in-the-uk-and-eu/550540/

An SEO shared on social media that his SEO tests proved that not using a meta description resulted in a lift in traffic. Coincidentally, another well-known SEO published an article that claims that SEO tests misunderstand how Google and the internet actually work and lead to the deprioritization of meaningful changes. Who is right?

SEO Says Pages Without Meta Descriptions Received Ranking Improvement

Mark Williams-Cook posted the results of his SEO test on LinkedIn about using and omitting meta descriptions, concluding that pages lacking a meta description received an average traffic lift of approximately 3%.

Here’s some of what he wrote:

“This will get some people’s backs up, but we don’t recommend writing meta descriptions anymore, and that’s based on data and testing.

We have consistently found a small, usually around 3%, but statistically significant uplift to organic traffic on groups of pages with no meta descriptions vs test groups of pages with meta descriptions via SEOTesting.

I’ve come to the conclusion if you’re writing meta descriptions manually, you’re wasting time. If you’re using AI to do it, you’re probably wasting a small amount of time.”

Williams-Cook asserted that Google rewrites around 80% of meta descriptions and insisted that the best meta descriptions are query dependent, meaning that the ideal meta description would be one that’s custom written for the specific queries the page is ranking for, which is what Google does when the meta description is missing.

He expressed the opinion that omitting the meta description increases the likelihood that Google will step in and inject a query-relevant meta description into the search results which will “outperform” the normal meta description that’s optimized for whatever the page is about.

Although I have reservations about SEO tests in general, his suggestion is intriguing and has the ring of plausibility.

Are SEO Tests Performative Theater?

Coincidentally, Jono Alderson, a technical SEO consultant, published an article last week titled, “Stop testing. Start shipping.” where he discusses his view on SEO tests, calling it “performative theater.”

Alderson writes:

“The idea of SEO testing appeals because it feels scientific. Controlled. Safe…

You tweak one thing, you measure the outcome, you learn, you scale. It works for paid media, so why not here?

Because SEO isn’t a closed system. …It’s architecture, semantics, signals, and systems. And trying to test it like you would test a paid campaign misunderstands how the web – and Google – actually work.

Your site doesn’t exist in a vacuum. Search results are volatile. …Even the weather can influence click-through rates.

Trying to isolate the impact of a single change in that chaos isn’t scientific. It’s theatre.

…A/B testing, as it’s traditionally understood, doesn’t even cleanly work in SEO.

…most SEO A/B testing isn’t remotely scientific. It’s just a best-effort simulation, riddled with assumptions and susceptible to confounding variables. Even the cleanest tests can only hint at causality – and only in narrowly defined environments.”

Jono makes a valid point about the unreliability of tests where the inputs and the outputs are not fully controlled.

Statistical tests are generally done within a closed system where all the data being compared follow the same rules and patterns. But if you compare multiple sets of pages, where some pages target long-tail phrases and others target high-volume queries, then the pages will differ in their potential outcomes. External changes (daily traffic fluctuation, users clicking on the search results) aren’t controllable. As Jono suggested, even the weather can influence click rates.

Although Williams-Cook asserted that he had a control group for testing purposes, it’s extremely difficult to isolate a single variable on live websites due to the uncontrollable external factors as Jono points out.

So, even though Williams-Cook asserts that the 3% change he noted is consistent and statistically relevant, the unobservable factors within Google’s black box algorithm that determines the outcome makes it difficult to treat that result as a reliable causal finding in the way one could with a truly controlled and observable statistical testing method.

If it’s not possible to isolate one change then it’s very difficult to make reliable claims about the resulting SEO test results.

Focus On Meaningful SEO Improvements

Jono’s article calls out the shortcomings of SEO tests but the point of his essay is to call attention to how focusing on what can be tested and measured can become prioritized over the “meaningful” changes that should be made but aren’t because they cannot be measured. He argues that it’s important to focus on the things that matter in today’s search environment that are related to content and a better user experience.

And that’s where we circle back to Williams-Cook because although statistically valid A/B SEO tests may be “theatre” as Jono suggests, it doesn’t mean that Williams-Cook’s suggestion is wrong. He may actually may be correct that it’s better to omit the meta description and let Google rewrite them.

SEO is subjective which means what’s good for one might not be a priority for someone else. So the question remains, is removing all meta descriptions a meaningful change?

Featured Image by Shutterstock/baranq

https://www.searchenginejournal.com/seo-rockstar-proves-you-dont-need-meta-descriptions/550490/

No ranking data. No impression data. 

So, how do you measure success when AI-generated answers appear and disappear, prompt by prompt?

With these significant changes to how we optimize for search, many brands are seeking to understand how to achieve SEO success.

Some Brands Are Winning in Search. Others? Invisible.

If your content isn’t appearing in AI-generated responses, like AI Overviews, ChatGPT, or Perplexity, you’re already losing ground to competitors.

👉 RSVP: Learn from the brands still dominating SERPs through AI search

In This Free Webinar, You’ll Learn:

• Data-backed insights on what drives visibility and performance in AI search
• A proven framework to drive results in AI search, and why this approach works
• Purpose-built content strategies for driving success in Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO).

This webinar helps enterprise SEOs and executives move from “I don’t know what’s happening in AI search” to “I have a data-driven strategy to compete and win.”

This session is designed for:

• Marketing managers and SEO strategists looking to stay ahead.
• Brand leaders managing performance visibility across platforms.
• Content teams building for modern search behaviors.

You’ll walk away with a usable playbook and a better understanding of how to optimize for the answer, not the query.

Learn from what today’s winning brands are doing right.

Secure your spot, plus get the recording sent straight to your inbox if you can’t make it live.

https://www.searchenginejournal.com/are-you-still-optimizing-for-rankings/550093/

Is your SEO strategy ready for Google’s new AI Mode?

Is your 2025 SERP strategy in danger?

What’s changed between traditional search mode and AI mode? 

Will Google’s New AI Mode Hurt Your Traffic?

Watch our webinar on-demand as we explored early implications for click-through rates, organic visibility, and content performance so you can:

• Spot AIO SERP triggers: Identify search types most likely to spark AI Overviews.
• Analyze impact: Find out which industries are being hit hardest.
• Audit AIO brand mentions: See which domains are dominating AI-generated answers.
• Optimize visibility: Update your SEO strategy to stay competitive.
• Accurately track AI traffic: Measure shifts in click-through rates, visibility, and content performance.

In this actionable session, Nick Gallagher, SEO Lead at Conductor, gave actionable SEO guidance in this new era of search engine results page (SERPs). 

Get recommendations for optimizing content to stay competitive as AI-generated answers grow in prominence.

Google’s New AI Mode: Learn To Analyze, Adapt & Optimize

Don’t wait for the SERPs to leave you behind.

Watch on-demand to uncover if AI Mode will hurt your traffic, and what to do about it.

View the slides below or check out the full webinar for all the details

https://www.searchenginejournal.com/is-google-about-to-bury-your-website-recap/548146/

A discussion on LinkedIn about LLM visibility and the tools for tracking it explored how SEOs are approaching optimization for LLM-based search. The answers provided suggest that tools for LLM-focused SEO are gaining maturity, though there is some disagreement about what exactly should be tracked.

Joe Hall (LinkedIn profile) raised a series of questions on LinkedIn about the usefulness of tools that track LLM visibility. He didn’t explicitly say that the tools lacked utility, but his questions appeared intended to open a conversation

He wrote:

“I don’t understand how these systems that claim to track LLM visibility work. LLM responses are highly subjective to context. They are not static like traditional SERPs are. Even if you could track them, how can you reasonably connect performance to business objectives? How can you do forecasting, or even build a strategy with that data? I understand the value of it from a superficial level, but it doesn’t really seem good for anything other than selling a service to consultants that don’t really know what they are doing.”

Joshua Levenson (LinkedIn profile) else answered saying that today’s SEO tools are out of date, remarking:

“People are using the old paradigm to measure a new tech.”

Joe Hall responded with “Bingo!”

LLM SEO: “Not As Easy As Add This Keyword”

Lily Ray (LinkedIn profile) responded to say that the entities that LLMs fall back on are a key element to focus on.

She explained:

“If you ask an LLM the same question thousands of times per day, you’ll be able to average the entities it mentions in its responses. And then repeat that every day. It’s not perfect but it’s something.”

Hall asked her how that’s helpful to clients and Lily answered:

“Well, there are plenty of actionable recommendations that can be gleaned from the data. But that’s obviously the hard part. It’s not as easy as “add this keyword to your title tag.”

Tools For LLM SEO

Dixon Jones (LinkedIn profile) responded with a brief comment to introduce Waikay, which stands for What AI Knows About You. He said that his tool uses entity and topic extraction, and bases its recommendations and actions on gap analysis.

Ryan Jones (LinkedIn profile) responded to discuss how his product SERPRecon works:

“There’s 2 ways to do it. one – the way I’m doing it on SERPrecon is to use the APIs to monitor responses to the queries and then like LIly said, extract the entities, topics, etc from it. this is the cheaper/easier way but is easiest to focus on what you care about. The focus isn’t on the exact wording but the topics and themes it keeps mentioning – so you can go optimize for those.

The other way is to monitor ISP data and see how many real user queries you actually showed up for. This is super expensive.

Any other method doesn’t make much sense.”

And in another post followed up with more information:

“AI doesn’t tell you how it fanned out or what other queries it did. people keep finding clever ways in the network tab of chrome to see it, but they keep changing it just as fast.

The AI Overview tool in my tool tries to reverse engineer them using the same logic/math as their patents, but it can never be 100%.”

Then he explained how it helps clients:

“It helps us in the context of, if I enter 25 queries I want to see who IS showing up there, and what topics they’re mentioning so that I can try to make sure I’m showing up there if I’m not. That’s about it. The people measuring sentiment of the AI responses annoy the hell out of me.”

Ten Blue Links Were Never Static

Although Hall stated that the “traditional” search results were static, in contrast to LLM-based search results, it must be pointed out that the old search results were in a constant state of change, especially after the Hummingbird update which enabled Google to add fresh search results when the query required it or when new or updated web pages were introduced to the web. Also, the traditional search results tended to have more than one intent, often as many as three, resulting in fluctuations in what’s ranking.

LLMs also show diversity in their search results but, in the case of AI Overviews, Google shows a few results that for the query and then does the “fan-out” thing to anticipate follow-up questions that naturally follow as part of discovering a topic.

Billy Peery (LinkedIn profile) offered an interesting insight into LLM search results, suggesting that the output exhibits a degree of stability and isn’t as volatile as commonly believed.

He offered this truly interesting insight:

“I guess I disagree with the idea that the SERPs were ever static.

With LLMs, we’re able to better understand which sources they’re pulling from to answer questions. So, even if the specific words change, the model’s likelihood of pulling from sources and mentioning brands is significantly more static.

I think the people who are saying that LLMs are too volatile for optimization are too focused on the exact wording, as opposed to the sources and brand mentions.”

Peery makes an excellent point by noting that some SEOs may be getting hung up on the exact keyword matching (“exact wording”) and that perhaps the more important thing to focus on is whether the LLM is linking to and mentioning specific websites and brands.

Takeaway

Awareness of LLM tools for tracking visibility is growing. Marketers are reaching some agreement on what should be tracked and how it benefits clients. While some question the strategic value of these tools, others use them to identify which brands and themes are mentioned, adding that data to their SEO mix.

Featured Image by Shutterstock/TierneyMJ

https://www.searchenginejournal.com/llm-visibility-tools-do-seos-agree-on-how-to-use-them/550267/

Google Search Advocate John Mueller says core updates rely on longer-term patterns rather than recent site changes or link spam attacks.

The comment was made during a public discussion on Bluesky, where SEO professionals debated whether a recent wave of spammy backlinks could impact rankings during a core update.

Mueller’s comment offers timely clarification as Google rolls out its June core update.

Core Updates Aren’t Influenced By Recent Links

Asked directly whether recent link spam would be factored into core update evaluations, Mueller said:

“Off-hand, I can’t think of how these links would play a role with the core updates. It’s possible there’s some interaction that I’m not aware of, but it seems really unlikely to me.

Also, core updates generally build on longer-term data, so something really recent wouldn’t play a role.”

For those concerned about negative SEO tactics, Mueller’s statement suggests recent spam links are unlikely to affect how Google evaluates a site during a core update.

Link Spam & Visibility Concerns

The conversation began with SEO consultant Martin McGarry, who shared traffic data suggesting spam attacks were impacting sites targeting high-value keywords.

In a post linking to a recent SEJ article, McGarry wrote:

“This is traffic up in a high value keyword and the blue line is spammers attacking it… as you can see traffic disappears as clear as day.”

Mark Williams-Cook responded by referencing earlier commentary from a Google representative at the SEOFOMO event, where it was suggested that in most cases, links were not the root cause of visibility loss, even when the timing seemed suspicious.

This aligns with a broader theme in recent SEO discussions: it’s often difficult to prove that link-based attacks are directly responsible for ranking drops, especially during major algorithm updates.

Google’s Position On The Disavow Tool

As the discussion turned to mitigation strategies, Mueller reminded the community that Google’s disavow tool remains available, though it’s not always necessary.

Mueller said:

“You can also use the domain: directive in the disavow file to cover a whole TLD, if you’re +/- certain that there are no good links for your site there.”

He added that the tool is often misunderstood or overused:

“It’s a tool that does what it says; almost nobody needs it, but if you think your case is exceptional, feel free.

Pushing it as a service to everyone says a bit about the SEO though.”

That final remark drew pushback from McGarry, who clarified that he doesn’t sell cleanup services and only uses the disavow tool in carefully reviewed edge cases.

Community Calls For More Transparency

Alan Bleiweiss joined the conversation by calling for Google to share more data about how many domains are already ignored algorithmically:

“That would be the best way to put site owners at ease, I think. There’s a psychology to all this cat & mouse wording without backing it up with data.”

His comment reflects a broader sentiment. Many professionals still feel in the dark about how Google handles potentially manipulative or low-quality links at scale.

What This Means

Mueller’s comments offer guidance for anyone evaluating ranking changes during a core update:

• Recent link spam is unlikely to influence a core update.
• Core updates are based on long-term patterns, not short-term changes.
• The disavow tool is still available but rarely needed in most cases.
• Google’s systems may already discount low-quality links automatically.

If your site has seen changes in visibility since the start of the June core update, these insights suggest looking beyond recent link activity. Instead, focus on broader, long-term signals, such as content quality, site structure, and overall trust.

https://www.searchenginejournal.com/googles-john-mueller-core-updates-build-on-long-term-data/550241/