Nov 13 2025
Data Shows How AI Overviews Is Ranking Shopping Keywords via @sejournal, @martinibuster

BrightEdge’s latest research shows that Google’s AI Overviews are now appearing in ways that reflect what BrightEdge describes as “deliberate, aggressive choices” about where AI shows up and where it does not. These trends show marketers where AI search is showing up within the buyer’s journey and what businesses should expect.

The data indicates that Google is concentrating AI in parts of the shopping process where it gives clear informational value, particularly during research and evaluation. This aligns AI Overviews with the points in the shopping journey where users need help comparing options or understanding product details.

BrightEdge reports that Google retained only about 30 percent of the AI Overview keywords that appeared at the peak of its September 1 through October 15, 2025 research window. The retained queries also tended to have higher search volume than the removed ones, which BrightEdge notes is the opposite pattern observed in 2024. This fits with the higher retention in categories where shoppers look for explanations, comparisons, and instructional information.

BrightEdge explains:

“The numbers paint an interesting story: Google retained only 30% of its peak AI Overview keywords. But here’s what makes 2025 fundamentally different: those retained keywords have HIGHER search volume than removed ones—the complete opposite of 2024. Google isn’t just pulling back; it’s being strategic about which searches deserve AI guidance.”

The shifting behavior of AI Overviews shows how actively Google is tuning its system. BrightEdge observed a spike from 9 percent to 26 percent coverage on September 18 before returning to 9 percent soon after. This change signals ongoing testing. The year-over-year overlap of AI Overview keywords is only 18 percent, which BrightEdge calls a “massive reshuffling” that shows “active experimentation” and requires marketers to plan for change rather than stability. The volatility shows Google may be experimenting or responding to user trends and that the queries shown in AI Overviews can change over time.
My opinion is that Google is likely responding to user trends, testing how they respond to AI Overviews, then using the data to show more if user reactions are positive.

AI Is A Comparison And Evaluation Layer

BrightEdge’s research indicates that AI Overviews aligns with shopper intent. Google places AI in research queries such as “best TV for gaming,” continues support for evaluation queries like “Samsung vs LG,” and then withdraws when users show purchase intent with searches like “Samsung S95C price.”

These examples show that AI serves as an educational and comparison layer, not a transactional one. When a shopper reaches a buying decision, Google steps back and lets traditional results handle the final step. This apparent alignment with comparison and evaluation means Google is confident in using AI Overviews as a part of the shopping journey.

Usefulness Varies Across Categories

The data shows that AI’s usefulness varies across categories, and Google adjusts AIO keywords retention based on these needs. Categories that retained AI Overviews such as Grocery, TV and Home Theater, and Small Appliances share a pattern.

Users rely on comparison, explanation, and instruction during their decisions. In contrast, categories with low retention, like Furniture and Home, rely on visual browsing rather than text-based evaluation. This limits the value of AI. Google’s category patterns show that AI appears more often in categories where text-based information (such as comparison, explanation, and instruction) guides decisions.

Google’s keyword filtering clarifies how AI fits into the shopping journey. Among retained queries, a little more than a quarter are evaluation or comparison searches, including “best [product]” and “X vs Y” terms. These are queries where users need background and guidance. In contrast, Google removes bottom-funnel keywords. Price, buy, deals, and specific product names are removed. This shows Google’s focus is on how useful AI serves for each intent. AI educates and guides but does not handle the final purchase step.

Shopping Trends Influence AI Appearance

The shopping calendar shapes how AI appears in search results. BrightEdge describes the typical shopping journey as consisting of research in November, evaluation and comparison in early December, and buying in late December. AI helps shoppers understand options in November, assists with comparisons in early December, and by late December, AI tends to be less influential and traditional search results tend to complete the sale.

This makes November the key moment for making evaluation and comparison content easier for AI to cite. Once December arrives, the chance for AI-driven discovery shrinks because consumers have moved on to the final leg of their shopping journey, purchase.

These findings mean that brands should align their content strategies with the points in the journey where AI Overviews are active. BrightEdge advises identifying evaluation and transactional pages, ensuring that comparison content is indexed early, and watching category-specific retention patterns. The data indicates two areas where brands can focus their efforts. One is supporting AI during research and review stages. The other is improving organic search visibility for purchasing queries. The 18 percent year-over-year consistency figure also shows that flexibility is needed because the queries shown in AI Overviews change frequently.

Although the behavior of AI Overviews may seem volatile, BrightEdge’s research suggests that the changes follow a consistent pattern. AI surfaces when people are learning and evaluating and withdraws when users shift into buying. Categories that require explanations or comparisons see the highest retention in AI Overviews, and November remains the key period when AI can use that content. The overall pattern gives brands a clearer view of how AI fits into the shopping journey and how user intent shapes where AI shows up.

Read BrightEdge’s report:
Google AI Overview Holiday Shopping Test: The 57% Pullback That Changes Everything

Featured Image by Shutterstock/Misselss

Ecommerce MGMT 0 Comments
Nov 12 2025
Why Web Hosting Is A Critical Factor To Maximize SEO Results via @sejournal, @MattGSouthern

Most SEO professionals obsess over content, links, and technical implementations. We track algorithm updates and audit on-page elements with precision. But there’s one factor that determines whether all that work can deliver results.

Your web hosting controls every user’s first interaction with your site. It determines load speeds, uptime consistency, and Core Web Vitals scores before anyone reads a word you’ve written.

Here’s the reality. Your hosting provider isn’t a commodity service. It’s the infrastructure that either supports or sabotages your SEO efforts. When technical SEO fails, the problem can trace back to hosting limitations you don’t know exist.

Your Host Controls The Metrics Google Measures

Core Web Vitals are a key part of how hosting can impact SEO through slow page speeds. These metrics measure what your server infrastructure determines.

Your Largest Contentful Paint (LCP) score starts with server response time. When Google’s crawler requests your page, your host must respond, process the request, and start delivering content.

Fast servers respond in under 200 milliseconds. Slower infrastructure takes 500+ milliseconds, degrading your LCP before optimization work matters.

Research analyzing 7,718 businesses across 676 sectors found top 10 ranking positions consistently showed faster server response than competitors. Google’s algorithm recognizes and rewards infrastructure quality.

Your hosting provider controls these metrics through several factors:

  • SSD storage processes read/write operations exponentially faster than traditional hard drives.
  • HTTP/3 protocol support reduces latency by 3-7% compared to HTTP/2. [1, 2]
  • Content Delivery Networks distribute content to servers closer to users, eliminating distance delays.

Sites on infrastructure optimized for Core Web Vitals consistently achieve LCP under 2.5 seconds and INP under 200 milliseconds. These are Google’s “good” thresholds. Sites on legacy infrastructure struggle to meet these benchmarks regardless of front-end optimization.

Distance Still Matters In A Connected World

Server location introduces physical limitations that no optimization can overcome. Data travels at light speed through fiber optic cables, but distance matters. A California server serving New York users introduces approximately 70 milliseconds of latency from physical distance alone.

This affects SEO through Core Web Vitals performance. Geographic distance introduces latency that affects page load times. Sites struggle to meet Core Web Vitals thresholds when server infrastructure sits far from their primary audience, as distance contributes to performance problems that optimization alone can’t fully resolve.

The solution depends on your architecture. Shared, VPS, and dedicated hosting place your site on physical servers in specific data centers. Choose data centers close to your primary audience to reduce latency.

Cloud hosting distributes content differently. It serves content from multiple geographic points, mitigating distance penalties. But it requires careful configuration to ensure search engines can efficiently crawl your distributed content.

Uptime Affects How Often Google Crawls Your Site

Google allocates crawl budget partly based on your site’s reliability. When crawlers consistently encounter server timeouts, Google reduces crawl frequency to avoid wasting resources on unreliable infrastructure.

This creates a compounding problem.

Lower crawl frequency means new content takes longer to appear in search results. Updated pages don’t get re-indexed promptly. For sites publishing time-sensitive content or competing in fast-moving markets, hosting-related crawl delays can mean missing ranking opportunities.

Industry standard uptime guarantees of 99.9% translate to roughly 8.8 hours of downtime per year, or about 1.44 minutes daily. This sounds negligible, but timing matters. If those minutes occur when Google’s crawler attempts to access your site, you’ve lost that crawl opportunity. If they occur during peak traffic, you’ve lost conversions and sent negative signals to algorithms.

The business impact varies by industry:

  • Ecommerce sites lose immediate sales and long-term ranking potential.
  • News properties miss brief windows when content is most valuable.
  • Local businesses miss moments when potential customers search for their services.

Any host claiming 100% uptime should raise skepticism. Server maintenance, network routing issues, and data center problems ensure some downtime will occur. Select providers whose infrastructure design minimizes both frequency and duration of outages.

Modern Protocols Create Measurable Performance Advantages

Google’s Page Experience signals extend beyond Core Web Vitals to security and modern web standards. HTTPS has been a confirmed ranking factor since 2014, and its importance continues growing.

Modern hosts include free SSL certificates through services like Let’s Encrypt as standard features. Legacy providers may charge for SSL or create barriers that discourage upgrading to secure connections.

Beyond basic HTTPS, hosting infrastructure determines whether you can leverage protocols that improve performance. HTTP/2 introduced multiplexing capabilities that reduce latency. HTTP/3 further reduces latency through improved connection handling and better performance on unreliable networks.

These improvements translate to measurable Core Web Vitals gains. HTTP/3 can reduce page load times by 3-7% compared to HTTP/2, particularly for mobile users. Since mobile performance increasingly drives rankings, hosting infrastructure supporting the latest protocols provides competitive advantages.

Security extends beyond encryption to broader concerns. Hosts with modern security practices protect against DDoS attacks that cause downtime, implement rate limiting that prevents bot traffic from overwhelming your server, and maintain updated server software preventing exploitation of vulnerabilities.

Scalability Prevents Success From Becoming A Problem

One of hosting’s most overlooked SEO implications emerges when you succeed. Content goes viral. A campaign drives unexpected traffic. Your site appears on a major news outlet. Suddenly, the hosting plan adequate for normal traffic becomes a bottleneck.

Server resource limits (CPU, RAM, bandwidth) determine how many simultaneous users your site can serve before performance degrades. When your infrastructure can’t handle success, SEO consequences arrive quickly:

The worst-case scenario sees viral success damaging your organic performance. Content driving traffic performs poorly for new visitors, creating negative signals. Meanwhile, Google reduces crawl frequency across your site, delaying indexation of new content designed to capitalize on visibility.

Hosting providers offering easy scaling paths prevent this. Cloud platforms can automatically scale resources to match traffic demands. Traditional providers with multiple plan tiers allow upgrades without changing providers or migrating your site, reducing technical risk and preserving existing configuration.

Evaluating Hosts as Strategic Infrastructure

The hosting decision requires evaluating providers as infrastructure partners whose capabilities enable or constrain your SEO strategy, not as feature checklists to compare.

Before selecting hosting, audit your requirements. Geographic distribution of your target audience determines whether server location matters or CDN coverage is essential. Content publication frequency affects how much crawl consistency matters. Traffic patterns indicate whether you need spike-handling resources or steady-state capacity.

Consider these strategic factors when evaluating hosts:

  • Review network infrastructure and data center locations relative to your primary markets.
  • Verify track record on actual uptime rather than advertised guarantees.
  • Examine scaling options to ensure you can grow without migration disruption.
  • Evaluate technical support quality. 24/7 availability and demonstrated expertise matter during problems affecting organic performance.

Third-party monitoring services track real-world performance across major hosts, providing verification beyond marketing claims.

Why Infrastructure Determines Your SEO Ceiling

Web hosting functions as a multiplier on SEO efforts. Excellent hosting won’t compensate for poor content, but poor hosting can completely undermine excellent optimization work.

Think of hosting as a building’s foundation. A weak foundation limits how high you can build and how much weight the structure can support. You can create architectural marvels on that foundation, but they remain vulnerable. Similarly, you can implement sophisticated SEO strategies on inadequate infrastructure, but those strategies will consistently underperform their potential.

The most successful SEO programs recognize infrastructure as a strategic investment rather than a commodity expense. They select hosting providers whose capabilities align with performance requirements, whose geographic distribution matches their audience, and whose technical sophistication supports modern web standards and protocols.

As search algorithms increasingly emphasize user experience through metrics like Core Web Vitals, the hosting decision becomes more consequential. The gap between sites on modern infrastructure and those on legacy systems will widen. The organic visibility advantages of fast, reliable, geographically distributed hosting will compound over time as Google’s algorithm continues refining how it measures and rewards site performance.

Your hosting provider should be a strategic partner in your SEO program, not just a vendor in your technology stack. The infrastructure decisions you make today determine the ceiling on your organic performance potential for months or years to come.

Good hosting runs in the background without you thinking about it. That’s what an SEO-friendly web host should do: Enable your optimization work to deliver results rather than limiting what’s possible.

More Resources:

Featured Image: N Universe/Shutterstock

Ecommerce MGMT 0 Comments
Nov 12 2025
Is AI Search SEO Leaving Bigger Opportunities Behind? via @sejournal, @martinibuster

A recent podcast by Ahrefs raised two issues about optimizing for AI search that can cause organizations to underperform and miss out on opportunities to improve sales. The conversation illustrates a gap between realistic expectations for AI-based trends and what can be achieved through overlooked opportunities elsewhere.

YouTube Is Second Largest Search Engine

The first thing noted in the podcast is that YouTube is the second-largest search engine by queries entered in the search bar. More people type search queries into YouTube’s search bar than any other search engine except Google itself. So it absolutely makes sense for companies to seriously consider how a video strategy can work to increase traffic and brand awareness.

It should be a no-brainer that businesses figure out YouTube, and yet many businesses are rushing to spend time and money optimizing for answer engines like Perplexity and ChatGPT, which have a fraction of the traffic of YouTube.

Patrick Stox explained:

“YouTube is the second largest search engine. There’s a lot of focus on all these AI assistants. They’re in total driving less than 1% of your traffic. YouTube might be a lot more. I don’t know how much it’s going to drive traffic to the website, but there’s a lot of eyes on it. I know for us, like we see it in our signups, …they sign up for Ahrefs.

It’s an incredible channel that I think as people need to diversify, to kind of hedge their bets on where their traffic is coming from, this would be my first choice. Like go and do more video. There’s your action item. If you’re not doing it, go do more video right now.”

Tim Soulo, Ahrefs CMO, expressed curiosity that so many people are looking two or three years ahead for opportunities that may or may not materialize on AI assistants, while overlooking the real benefits available today on YouTube.

He commented:

“I feel that a lot of people get fixated on AI assistants like ChatGPT and Perplexity and optimizing for AI search because they are kind of looking three, five years ahead and they are kind of projecting that in three, five years, that might be the dominant thing, how people search.

…But again, if we focus on today, YouTube is much more popular than ChatGPT and YouTube has a lot more business potential than ChatGPT. So yeah, definitely you have to invest in AI search. You have to do the groundwork that would help you rank in Google, rank in ChatGPT and everything. …I don’t see YouTube losing its relevance five years from now. I can only see it getting bigger and bigger because the new generation of people that is growing up right now, they are very video oriented. Short form video, long form video. So yeah, definitely. If you’re putting all your eggs in the basket of ChatGPT, but not putting anything in YouTube, that’s a big mistake.”

Patrick Stox agreed with Tim, noting that Instagram and TikTok are big for short-form videos that are wildly popular today, and encouraged viewers and listeners to see how video can fit into their marketing.

Some of the disconnect regarding SEO and YouTube is that SEOs may feel that SEO is about Google, and YouTube is therefore not their domain of responsibility. I would counter that YouTube should be a part of SEOs’ concern because people use it for reviews, how-to information, and product research, and the searches on YouTube are second only to Google.

SEO/AEO/GEO Can’t Solve All AI Search Issues

The second topic they touched on was the expectations placed on SEO to solve all of a business’s traffic and visibility problems. Patrick Stox and Tim Soulo suggested that high rankings and a satisfactory marketing outcome begin and end with a high-quality product, service, and content. Problems at the product or service end cause friction and result in negative sentiment on social media. This isn’t something that you can SEO yourself out of.

Patrick Stox explained:

“We only have a certain amount of control, though. We can go and create a bunch of pages, a bunch of content. But if you have real issues, like if everyone suddenly is like Nvidia’s graphics cards suck and they’re saying that on social media and Reddit and everything, YouTube, there’s only so much you can do to combat that.

…And there might be tens of thousands of them and there’s one of me. So what am I gonna do? I’m gonna be a drop in the bucket. It’s gonna be noise in the void. The internet is still the one controlling the narrative. So there’s only so much that SEOs are gonna be able to do in a situation like that.

…So this is going to get contentious in a lot of organizations where you’re going to have to do something that the execs are going to be yelling, can’t you just change that, make it go away?”

Tim and Patrick went on to use the example of their experience with a pricing change they made a few years ago, where customers balked at the changes. Ahrefs made the change because they thought it would make their service more affordable, but despite their best efforts to answer user questions and get control of the conversation, the controversy wouldn’t go away, so they ultimately decided to give users what they wanted.

The point is that positive word of mouth isn’t necessarily an SEO issue, even though SEO/GEO/AEO is now expected to get out there and build positive brand associations so that they’re recommended by AI Mode, ChatGPT, and Perplexity.

Takeaways

  • Find balance between AI search and immediate business opportunities:
    Some organizations may focus too heavily on optimizing for AI assistants at the expense of video and multimodal search opportunities.
  • YouTube’s marketing power:
    YouTube is the second-largest search engine and a major opportunity for traffic and brand visibility.
  • Realistic expectations for SEO:
    SEO/GEO/AEO cannot fix problems rooted in poor products, services, or customer sentiment. Long-term visibility in AI search depends not just on optimization, but on maintaining positive brand sentiment.

Watch the video at about the 36 minute mark:

Featured Image by Shutterstock/Collagery

Ecommerce MGMT 0 Comments
Nov 11 2025
Budget SEO For Capacity, Not Output via @sejournal, @Kevin_Indig

Marketing leaders are still budgeting to grow clicks in 2026, even though AI Overviews cut organic traffic in half and AI Mode kills it almost entirely.

Image Credit: Kevin Indig

Meanwhile, close to 60% of those who responded to my recent poll report their stakeholders don’t understand the value of brand mentions in LLMs.

The SEO budget conversation has to move from “Why isn’t SEO driving more clicks?/What can we do to drive more traffic?” to “What capabilities do we need to build authority in new discovery channels?”

In 2026, the best marketing teams will stop measuring SEO success by clicks and start treating it as what it really is: a capacity and influence system.

1. Traffic-Based ROI Is A Decayed Model

Marketing budgets, on average, rose modestly in the last 12 months. Overall, marketing budgets are up 3.31%. And digital marketing spending specifically is up 7.25%.

SEO gets less than 10% of the marketing budget despite being one of the most efficient channels.

Image Credit: Kevin Indig

And for years, marketers invested this sliver of SEO budget like paid media – spend more, get more clicks. It’s time to let this go. There’s discomfort here, of course: We’re losing a significant leading indicator with traffic stagnation. In theory, SEO now appears to take “longer” to show results.

As Google dials AI in the search results up, organic clicks are destined to shrink. AI surfaces decouple visibility from clicks. Your brand can appear in every AI output response and get zero measurable traffic. In Semrush’s AI Mode study, 92-94% of AI Mode sessions produced no external clicks. (But that doesn’t mean people buy less. The opposite could be true.) Slowed growth in clicks is not a performance issue of an SEO team – it’s a system feature, and it’s the future of search. Platforms want users to stay within their ecosystems.

The implication: Traffic no longer equals demand. Brand visibility happens upstream inside AI responses, UGC threads, and recommendation loops that don’t often show in your analytics.

Image Credit: Kevin Indig

2. SEO Budgets Are Capacity Allocation, Not Spend-To-Output Trading

With paid ads, you’re buying impressions. Double your spend, you roughly double your impressions (with diminishing returns). There’s a direct, measurable relationship.

But most SEO costs are fixed: salaries, tool subscriptions, infrastructure. You pay for capacity regardless of whether your team delivers a 10% or 50% lift.

65% of those surveyed by Search Engine Journal don’t expect a reduction in SEO budget for 2026.

When deciding on next year’s budget, the question “What ROI do we expect from this spend?” is an outdated one. Instead, you need to answer this query: “What capabilities do we need to earn visibility?”

The variable isn’t spend; it’s prioritization and execution quality:

  • Paid media is transactional: Spend → user impression → user click.
  • SEO is compounding: Optimization → brand visibility → user impressions → brand influence.

Your SEO dollars don’t buy results. They buy the ability to earn trust and surface in the right systems.

3. Design Your SEO Budget Around Influence, Not Output In 2026.

Your budget planning must be scenario-based, not traffic-forecasted.

Because your SEO costs are mostly fixed, you can model it out: “If we allocate 40% of capacity to digital PR, 30% to technical SEO, 20% to content operations, and 10% to foundational research, what visibility outcomes can we reasonably expect?”

Allocate resources by priority, not by historical traffic performance. Strategize your resources for the zero-click world ahead:

  1. Digital PR: Third-party signals drive 85% of brand visibility in LLMs. Digital PR and high-quality, topically related backlink investment are crucial. The biggest gains come when you hit the upper boundaries of link quality/authority over volume.
  2. Technical SEO + UX: Get the foundation right. Agents need to review your site and make recommendations or decisions quickly.
  3. Audience + first-party data research: Users are making decisions about brands within the AI Mode outputs – know your audience and which search surfaces they use. Data from one study showed 71% of companies that exceeded revenue goals had documented personas.
  4. Content operations + re-optimizations: Content recency is non-negotiable, and LLMs prefer it. Some evidence shows refreshing every ~90 days could be a competitive edge.
  5. Additive content rich with information gain: Evergreen content is less valuable. Additive content that provides net-new takes, insights, and conversations is rewarded.
  6. Engineering + design support for interactive tools:Once the validation click is earned, you must provide value that’s worth on-page engagement.
  7. Video and custom graphics: Organic low-fi video content and custom graphics are earning highly visible mid-output placement in AIOs. Don’t let restricted resources stop you from investing in this visibility lever.

Your brand’s prioritization could vary based on audience, goals, and – of course – capacity.

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Featured Image: Paulo Bobita/Search Engine Journal

Ecommerce MGMT 0 Comments
Nov 11 2025
Google Is Not Diminishing The Use Of Structured Data In 2026 via @sejournal, @martinibuster

A recent announcement on the Google Search Central blog gave a Redditor the impression that Google was significantly reducing the use of structured data, causing them to ask if it’s worthwhile to use it anymore.

The person on Reddit posted:

“Google just posted a new update — they’re removing support for some structured data types starting in January 2026. Dataset already works only in Dataset Search, and rich results are getting more selective.

So… is schema still worth it? Or are we moving past it entirely?”

Matt Southern covered the blog post (Google Deprecates Practice Problem Structured Data In Search), focusing on the specific structured data that Google was deprecating. Google’s blog post, authored by John Mueller, could, if read quickly, be accidentally interpreted to be more alarming than it was intended to be.

Google’s announcement explained:

“We’re constantly working to simplify the search results page, so that it’s quick and easy to find the information and websites you’re looking for. As part of this effort, we regularly evaluate all of our existing features to make sure they’re still useful, both for people searching on Google and for website owners.

Through this process, we’ve identified some features that aren’t being used very often and aren’t adding significant value to users. In these cases, we’ve found that other advancements on the search results page are able to get people what they’re looking for more seamlessly. So we’re beginning to phase these lesser-used features out.

For most searches, you likely won’t notice a major difference — most of these features didn’t trigger often and weren’t interacted with much by users. But overall, this update will simplify the page and improve the speed of search results.”

Ending with the following sentence:

“Starting in January 2026, we’ll remove support for the structured data types in Search Console and its API.”

Google’s Search Features Are Always Changing

Someone responded to the initial post to reassure them that Google’s search features and the structured data that triggers them are always changing. That’s true. Google Search has consistently been in a state of change and never more visibly on the front end as it is today with AI search.

Google’s John Mueller responded to the Redditor who noted that Google is constantly changing by affirming that markup types (which includes Schema.org structured data) are always changing.

He responded:

“Exactly. Understand that markup types come and go, but a precious few you should hold on to (like title, and meta robots).”

Structured Data Curation Is Automatic

Keeping up with Schema.org structured data is easy with any modern content management system through plugins or as part of a native functionality because they are responsive to Google’s structured data guidance. So in general, it’s not something that a publisher or SEO needs to think about. Publishers on WordPress just need to keep their plugins updated.

Featured Image by Shutterstock/pathdoc

Ecommerce MGMT 0 Comments
Nov 10 2025
How To Cultivate Brand Mentions For Higher AI Search Rankings via @sejournal, @martinibuster

Building brand awareness has long been an important but widely overlooked part of SEO. AI Search has brought this activity to the forefront. The following ideas should assist in forming a strategy for achieving brand name mentions at a ubiquitous scale, with the goal of achieving similar ubiquity in AI search results.

Tell People About The Site

SEOs and businesses can become overly concerned with getting links and forget that the more important thing to do is to get the word out about a website. A website must have unique qualities that will positively impress people and make them enthusiastic about the brand. If the site you’re trying to build traffic to lacks those unique qualities then building links or brand awareness can become a futile activity.

User behavior signals have been a part of Google’s algorithms since the 2004 Navboost signals were kicking in and the recent Google antitrust lawsuit shows that user behavior signals have continued to play a role. What has changed is that SEOs have noticed that AI search results tend to recommend sites that are recommended by other sites, brand mentions.

The key to all of this has been to tell other sites about your site and make it clear to potential consumers or website visitors what makes your site special.

  • So the first task is always to make a site special in every possible way.
  • The second task is to tell others about the site in order to build word of mouth and top-of-mind brand presence.

Optimizing a website for users and cultivating awareness of that site are the building blocks of the external signals of authoritativeness, expertise, and popularity that Google is always talks about.

Downside of Backlink Searches

Everyone knows how to do a backlink search with third-party tools but a lot of the data consists of garbage-y sites; that’s not the tool’s fault, it’s just the state of the Internet. In any case, a backlink search is limited, it doesn’t surface the conversations real people are having about a website.

In my experience, a better way to do it is to identify all instances of where a site is linked from another site or discussed by another site.

Brand And Link Mentions

Some websites have bookmark and resource pages. These are low hanging fruit.

Search for a competitor’s links:

example.com site:.com “bookmarks” -site:example.com

example.com site:.com “resources” -site:example.com

The “-site:example.com” removes the competitor site from the search results, showing you just the sites that might mention the full URL of the site which may or may not be linked.

The TLD segmented variants are:

example.com site:.net "resources" 
example.com site:.org "resources" 
example.com site:.edu "resources" 
example.com site:.ai "resources" 
example.com site:.net "links" 
example.com site:.org "links" 
example.com site:.edu "links" 
example.com site:.ai "links" 
Etc.

The goal is not necessarily to get links. It’s to build awareness of the site and build popularity.

Brand Mentions By Company Name

One way to identify brand mentions is to search by company name using the TLD segmentation technique. Making a broad search for a company’s name will only get you some of the brand mentions. Segmenting the search by TLD will reveal a wider range of sites.

Segmented Brand Mention Search

The following assumes that the competitor’s site is on the .com domain and you’re limiting the search to .com websites.

Competitor's Brand Name site:.com -site:example.com

Segmented Variants:

Competitor's Brand Name site:.org
Competitor's Brand Name site:.edu
Competitor's Brand Name site:.Reddit.com
Competitor's Brand Name site:.io
etc.

Sponsored Articles

Sponsored articles are indexed by search engines and ranked in AI search surfaces like AI Mode and ChatGPT. These can present opportunities to purchase a sponsored post that enables you to present your message with links that are nofollow and a prominent “sponsored post” disclaimer at the top of the web page – all in compliance with Google and FTC guidelines.

Brand Mentions: Authoritativeness Is Key

The thing that some SEOs never learned is that authoritativeness is important and quite likely millions of dollars have been wasted on paying for links from low-quality blogs and higher quality sites.

ChatGPT and AI Mode are found to recommend sites that are mentioned in high quality authoritative sites. Do not waste time or money paying for mentions on low quality sites.

Some Ways To Search

Product/Service/Solution Search

Name Of Product Or Service Or Problem Needing Solving site:.com “sponsored article”
Name Of Product Or Service Or Problem Needing Solving site:.net “sponsored article”
Name Of Product Or Service Or Problem Needing Solving site:.org “sponsored article”
Name Of Product Or Service Or Problem Needing Solving site:.edu “sponsored article”
Name Of Product Or Service Or Problem Needing Solving site:.io “sponsored article”
etc.

Sponsored Post Variant

Name Of Product Or Service Or Problem Needing Solving site:.com “sponsored post”
Name Of Product Or Service Or Problem Needing Solving site:.net “sponsored post”
Name Of Product Or Service Or Problem Needing Solving site:.org “sponsored post”
Name Of Product Or Service Or Problem Needing Solving site:.edu “sponsored post”
Name Of Product Or Service Or Problem Needing Solving site:.io “sponsored post”
etc.

Key insight: Test whether “sponsored post” or “sponsored article” provides better results or just more results. Using quotation marks, or if necessary the verbatim search tool, will stop Google from stemming the search results and prevents it from showing a mix of both “post” and “article” results. By forcing Google to be specific, you’re forcing Google to show more search results.

Competitor Search

Competitor’s Brand Name site:.com “sponsored post”
Competitor’s Brand Name site:.net “sponsored post”
Competitor’s Brand Name site:.org “sponsored post”
Competitor’s Brand Name site:.edu “sponsored post”
Competitor’s Brand Name site:.io “sponsored post”
etc.

Pure Awareness Building With Zero Internet Presence

This method of getting the word out is pure gold, especially for B2B but also for professional businesses such as in the legal niches. There are organizations and associations that print magazines or send out newsletters to thousands, sometimes tens of thousands, of people who are an exact match for the people you want to build top of mind brand name recognition with.

Emails and magazines do not have links and that’s okay. The goal is to build name brand recognition with positive associations. What better way than getting interviewed in a newsletter or magazine? What better way than submitting an article to a newsletter or magazine?

Don’t Forget PDF Magazines

Not all magazines are print, many magazines are in the form of a PDF. For example, I subscribe to a surf fishing magazine that is entirely in a proprietary web format that can only be viewed by subscribers. If I were a fishing company, I would make an effort to meet some of article authors, in addition to the publishers, at fishing industry conferences where they appear as presenters and in product booths.

This kind of outreach is in-person, it’s called relationship building. 

Getting back to the industry organizations and associations, this is an entire topic in itself and I’ll follow up with another article, but many of the techniques covered in this guide will work with this kind of brand building.

Using the filetype search operator in combination with the TLD segmentation will yield some of these kinds of brand building opportunities.

[product/service/keyword/niche] filetype:pdf site:.com newsletter
[product/service/keyword/niche] filetype:pdf site:.org newsletter

1. Segment the search for opportunities search by TLD .net/.com/.org/.us/.edu, etc.
Segmenting by TLD will help you discover different kinds of brand building opportunities. Websites on a Dot Org domain often link to a site for different reasons than a Dot Com website. Dot org domains represent article writing projects, free links on a links page, newsletter article opportunity, and charity link opportunities, just to name a few.

2. Consider Segmenting Dot Com Searches
The Dot Com TLD will yields an overabundance of search results, not all of them useful. This makes it imperative to segment the results to find all available opportunities. Even if you’re

Ways to segment the Dot Com are by:

  • A. Kinds of sites (blog/shopping related keywords/product or service keywords/forum/etc.)
    This is pretty straightforward. If you’re looking for brand mentions be sure to add keywords to the searches that are directly relevant to what your business is about. If your site is about car injuries then sites about cars as well as specific makes, models, and kinds of automobiles are how you would segment a .com search
  • B. Context – Audience Relevance Not Keyword Match
    Context of a sponsored article is important. This is not about whether the website content matches what your site, business, product, or service are about.  What’s important is to identify if the audience reach is an exact match to the audience that will be interested in your product, business, or service.
  • C. Quality And Authoritativeness
    This is not about third-party metrics related to links. This is just about making a common sense judgment about whether a site where you want a mention is well-regarded by those who are likely to be interested in your brand. That’s it.

Takeaway

The thing I want you to walk away with is that it’s useful to just tell people about a site and to get as many people as possible aware of it. Identify opportunities for ways to get them to tell a friend. There is no better recommendation than the one you can get from a friend or from a trusted organization.  This is the true source of authoritativeness and popularity.

Featured Image by Shutterstock/Bird stocker TH

Ecommerce MGMT 0 Comments
Nov 10 2025
Why Strategic Review Is The Missing Layer In Many SEO Campaigns via @sejournal, @coreydmorris

Whether you call your SEO efforts a strategy, campaign, or channel, many SEO programs start strong but slowly drift. That could be in the form of reports getting routine, dashboards taking over for thinking, and moving into a mode of “doing SEO” versus challenging and building it.

In many cases, there’s an initial audit, roadmap, and then turn to implementation. Those are all good things, and I strongly advocate for the right level of strategy, research, and planning before moving into any level of ongoing work. However, monthly reports or dashboards, and little reflection can lead to stale tactics.

When activity, tactics, and implementation are the biggest part of what is reported on and/or measured, I question if enough strategic thinking and approach exist.

A strategic review and approach included a structured, periodic checkpoint within the process to assess performance. That includes a mixture of team (and resource/partner/vendor) alignment, execution, and continued connection to overall business goals that SEO is mapped out to impact.

Similar to a retrospective or ending a sprint in agile methodology, it is time for a look backwards at what worked, what didn’t, and where we need to go next in the overall SEO investment. This is different than just a set of reports and metrics; it is time for true reflection and recalibration beyond just measurement.

Why Strategy Is Often Missing

There are some common reasons SEO teams and resources skip strategic review and don’t have the layer fully in place. At times, SEO can seem like an ongoing checklist of things to audit, crawl, fix, and optimize. It can also feel like something that is always on or never-ending.

While all of those things are true to some degree, I think with SEO being a longer-term discipline before seeing return on investment (ROI), there’s pressure to show activity as progress before seeing tangible results, and this can be hard to change after habits and patterns form are embedded in the process.

Agency and client relationships can become rooted in deliverables and lose strategic direction over time. Or, a lack of ownership can exist where no one person or entity truly feels accountable for stepping back and considering if the strategy is still right and delivering.

Risks Of Skipping Strategy

When teams lack or drift from strategy, they run the risk of optimizing for the wrong things. Whether that is the topics, content, context, or even chasing the wrong key performance indicators (KPIs). Going for traffic and things that show activity and progress alone, and are disconnected from the bottom line, lead to danger when they can’t convert at some point.

Additionally, silos can exist, and insights can stay within the silos. When SEO is reduced to activities, tactics, and just actions, learnings from content, dev, brand, product development, customer service, leadership, and other functions aren’t shared with SEO, and vice versa.

Plus, in a world where new information, strategies, and opportunities seemingly emerge daily with how SEO works, AI search, and other areas of change, it is easy to get outdated quickly with assumptions about intent, audience behavior, and connections to the bottom line.

Strategy Integrated Ongoing SEO

Establish A Cadence

The ideal timing for how often to revisit strategy or how it integrates into the ongoing SEO effort is different for everyone. Whether it is quarterly, monthly, or on some frequency that matches the speed at which SEO can and will be implemented, along with the speed of the rest of the moving parts in digital marketing, it is important to lock it in. And, adjust where necessary, but do not keep pushing it down the road.

Since SEO is often an indefinitely ongoing investment, I like the use of sprints and agile thinking, and in this case, building into the agile process. Ultimately, the goal is to not drift or move into a void far enough where strategy problems start happening, yet are missed or ignored.

Dig Deep Enough

However and whenever you build in the strategic review part of the process, there are some key questions to ask however formally you format the process.

This starts with strategy alignment. Are our current goals still the right ones to anchor to? Do they map out to business outcomes versus indicators or vanity metrics? Can we get deep enough in measurement of impact and attribution?

From there, execution and focus are important to review. This includes looking at the tactics that had an impact versus those that didn’t. And, to fully understand why.

Now, we can set our sights on the next sprint or period, looking forward. Consider the opportunities ahead, including trends, SERP features, audience behaviors, AI, and anything else that has emerged that needs to be factored into the effort.

Bring People Together

A tale as old as time in SEO having the best plans stalled out by a lack of resources or a strong resource plan. This means we need to make sure we have the right people, whether they are on the team, in another department, freelance, or at a vendor company, booked and lined up to help us implement.

Better yet, if you can have them in the room with you at any part of the strategic review to learn from the insights you’re seeing and help shape the plan, sharing out of their subject matter expertise and perspective, even better. This is your chance to break down silos and get more integration of SEO with other functions.

Be Structured

I have to confess that I love to iterate and try new things with processes. That’s part of what drew me into SEO over 20 years ago. However, I think that there has to be consistency in the approach and process. You don’t want to spend too much time overdoing it in ongoing strategic reviews. At the same time, you don’t want to be too shallow and gloss over it.

I recommend borrowing some agile retrospective agenda formats and structures to look at what to start, stop, continue, and plan what’s next. Borrow from that if you are struggling to come up with a simple enough, yet powerful review criteria and process.

Revise The Plan

It might feel like a given that you’ll take the work you did and integrate it into your plan and efforts. I simply want to wrap up here by stating the obvious that you need to feed insights into the next period’s plan. That could also include adjusting goals, KPIs, and tactical priorities.

The key is to take things from talk and spreadsheets to action. Especially if your efforts have multiple layers, integrations of teams, or client/agency relationships.

Wrapping Up

SEO is a long game, but progress happens in shorter cycles. It can become a routine, a checklist, or a thing to “do” over time. Often, outdated strategies and tactics come from a lack of frequent enough critical strategic review and adjustment.

My goal for you is to not encounter these issues or find out later than you wished that your SEO has been drifting or gotten stale and isn’t delivering (and hasn’t for some time). The most strategic SEO efforts aren’t always the busiest or most activity-filled with quantity, but are focused on quality and have the mechanisms in place and often enough to adapt intentionally.

The best SEO teams and efforts aren’t just executing; they’re evolving.

More Resources:

Featured Image: Master1305/Shutterstock

Ecommerce MGMT 0 Comments
Nov 10 2025
A Step-By-Step AEO Guide For Growing AI Citations & Visibility via @sejournal, @fthead9

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

After years of trying to understand the black box that is Google search, SEO professionals have a seemingly even more opaque challenge these days – how to earn AI citations.

While at first glance inclusion in AI answers seems even more of a mystery than traditional SEO, there is good news. Once you know how to look for them, the AI engines do provide clues to what they consider valuable content.

This article will give you a step-by-step guide to discovering the content that AI engines value and provide a blueprint for optimizing your website for AI citations.

Take A Systematic Approach To AI Engine Optimization

The key to building an effective AI search optimization strategy begins with understanding the behavior of AI crawlers. By analyzing how these bots interact with your site, you can identify what content resonates with AI systems and develop a data-driven approach to optimization.

While Google remains dominant, AI-powered search engines like ChatGPT, Perplexity, and Claude are increasingly becoming go-to resources for users seeking quick, authoritative answers. These platforms don’t just generate responses from thin air – they rely on crawled web content to train their models and provide real-time information.

This presents both an opportunity and a challenge. The opportunity lies in positioning your content to be discovered and referenced by these AI systems. The challenge is understanding how to optimize for algorithms that operate differently from traditional search engines.

The Answer Is A Systematic Approach

  • Discover what content AI engines value based on their crawler behavior.
    • Traditional log file analysis.
    • SEO Bulk Admin AI Crawler monitoring.
  • Reverse engineer prompting.
    • Content analysis.
    • Technical analysis.
  • Building the blueprint.

What Are AI Crawlers & How To Use Them To Your Advantage

AI crawlers are automated bots deployed by AI companies to systematically browse and ingest web content. Unlike traditional search engine crawlers that primarily focus on ranking signals, AI crawlers gather content to train language models and populate knowledge bases.

Major AI crawlers include:

  • GPTBot (OpenAI’s ChatGPT).
  • PerplexityBot (Perplexity AI).
  • ClaudeBot (Anthropic’s Claude).
  • Googlebot crawlers (Google AI).

These crawlers impact your content strategy in two critical ways:

  1. Training data collection.
  2. Real-time information retrieval.

Training Data Collection

AI models are trained on vast datasets of web content. Pages that are crawled frequently may have a higher representation in training data, potentially increasing the likelihood of your content being referenced in AI responses.

Real-Time Information Retrieval

Some AI systems crawl websites in real-time to provide current information in their responses. This means fresh, crawlable content can directly influence AI-generated answers.

When ChatGPT responds to a query, for instance, it’s synthesizing information gathered by its underlying AI crawlers. Similarly, Perplexity AI, known for its ability to cite sources, actively crawls and processes web content to provide its answers. Claude also relies on extensive data collection to generate its intelligent responses.

The presence and activity of these AI crawlers on your site directly impact your visibility within these new AI ecosystems. They determine whether your content is considered a source, if it’s used to answer user questions, and ultimately, if you gain attribution or traffic from AI-driven search experiences.

Understanding which pages AI crawlers visit most frequently gives you insight into what content AI systems find valuable. This data becomes the foundation for optimizing your entire content strategy.

How To Track AI Crawler Activity: Find & Use Log File Analysis

The Easy Way: We use SEO Bulk Admin to analyze server log files for us.

However, there’s a manual way to do it, as well.

Server log analysis remains the standard for understanding crawler behavior. Your server logs contain detailed records of every bot visit, including AI crawlers that may not appear in traditional analytics platforms, which focus on user visits.

Essential Tools For Log File Analysis

Several enterprise-level tools can help you parse and analyze log files:

  • Screaming Frog Log File Analyser: Excellent for technical SEOs comfortable with data manipulation.
  • Botify: Enterprise solution with robust crawler analysis features.
  • Semrush: Offers log file analysis within its broader SEO suite.
Screenshot from Screaming Frog Log File AnalyserScreenshot from Screaming Frog Log File Analyser, October 2025

The Complexity Challenge With Log File Analysis

The most granular way to understand which bots are visiting your site, what they’re accessing, and how frequently, is through server log file analysis.

Your web server automatically records every request made to your site, including those from crawlers. By parsing these logs, you can identify specific user-agents associated with AI crawlers.

Here’s how you can approach it:

  1. Access Your Server Logs: Typically, these are found in your hosting control panel or directly on your server via SSH/FTP (e.g., Apache access logs, Nginx access logs).
  2. Identify AI User-Agents: You’ll need to know the specific user-agent strings used by AI crawlers. While these can change, common ones include:
  • OpenAI (for ChatGPT, e.g., `ChatGPT-User` or variations)
  • Perplexity AI (e.g., `PerplexityBot`)
  • Anthropic (for Claude, though often less distinct or may use a general cloud provider UAs)
  • Other LLM-related bots (e.g., “GoogleBot” and `Google-Extended` for Google’s AI initiatives, potentially `Vercelbot` or other cloud infrastructure bots that LLMs might use for data fetching).
  1. Parse and Analyze: This is where the previously mentioned log analyzer tools come into play. Upload your raw log files into the analyzer and start filtering the results to identify AI crawler and search bot activity. Alternatively, for those with technical expertise, Python scripts or tools like Splunk or Elasticsearch can be configured to parse logs, identify specific user-agents, and visualize the data.

While log file analysis provides the most comprehensive data, it comes with significant barriers for many SEOs:

  • Technical Depth: Requires server access, understanding of log formats, and data parsing skills.
  • Resource Intensive: Large sites generate massive log files that can be challenging to process.
  • Time Investment: Setting up proper analysis workflows takes considerable upfront effort.
  • Parsing Challenges: Distinguishing between different AI crawlers requires detailed user-agent knowledge.

For teams without dedicated technical resources, these barriers can make log file analysis impractical despite its value.

An Easier Way To Monitor AI Visits: SEO Bulk Admin

While log file analysis provides granular detail, its complexity can be a significant barrier for all but the most highly technical users. Fortunately, tools like SEO Bulk Admin can offer a streamlined alternative.

The SEO Bulk Admin WordPress plugin automatically tracks and reports AI crawler activity without requiring server log access or complex setup procedures. The tool provides:

  • Automated Detection: Recognizes major AI crawlers, including GPTBot, PerplexityBot, and ClaudeBot, without manual configuration.
  • User-Friendly Dashboard: Presents crawler data in an intuitive interface accessible to SEOs at all technical levels.
  • Real-Time Monitoring: Tracks AI bot visits as they happen, providing immediate insights into crawler behavior.
  • Page-Level Analysis: Shows which specific pages AI crawlers visit most frequently, enabling targeted optimization efforts.
Screenshot of SEO Bulk Admin AI/Bots ActivityScreenshot of SEO Bulk Admin AI/Bots Activity, October 2025

This gives SEOs instant visibility into which pages are being accessed by AI engines – without needing to parse server logs or write scripts.

Comparing SEO Bulk Admin Vs. Log File Analysis

Feature Log File Analysis SEO Bulk Admin
Data Source Raw server logs WordPress dashboard
Technical Setup High Low
Bot Identification Manual Automatic
Crawl Tracking Detailed Automated
Best For Enterprise SEO teams Content-focused SEOs & marketers

For teams without direct access to server logs, SEO Bulk Admin offers a practical, real-time way to track AI bot activity and make data-informed optimization decisions.

Screenshot of SEO Bulk Admin Page Level Crawler ActivityScreenshot of SEO Bulk Admin Page Level Crawler Activity, October 2025

Using AI Crawler Data To Improve Content Strategy

Once you’re tracking AI crawler activity, the real optimization work begins. AI crawler data reveals patterns that can transform your content strategy from guesswork into data-driven decision-making.

Here’s how to harness those insights:

1. Identify AI-Favored Content

  • High-frequency pages: Look for pages that AI crawlers visit most frequently. These are the pieces of content that these bots are consistently accessing, likely because they find them relevant, authoritative, or frequently updated on topics their users inquire about.
  • Specific content types: Are your “how-to” guides, definition pages, research summaries, or FAQ sections getting disproportionate AI crawler attention? This can reveal the type of information AI models are most hungry for.

2. Spot LLM-Favored Content Patterns

  • Structured data relevance: Are the highly-crawled pages also rich in structured data (Schema markup)? It’s an open debate, but some speculate that AI models often leverage structured data to extract information more efficiently and accurately.
  • Clarity and conciseness: AI models excel at processing clear, unambiguous language. Content that performs well with AI crawlers often features direct answers, brief paragraphs, and strong topic segmentation.
  • Authority and citations: Content that AI models deem reliable may be heavily cited or backed by credible sources. Track if your more authoritative pages are also attracting more AI bot visits.

3. Create A Blueprint From High-Performing Content

  • Reverse engineer success: For your top AI-crawled content, document its characteristics.
  • Content structure: Headings, subheadings, bullet points, numbered lists.
  • Content format: Text-heavy, mixed media, interactive elements.
  • Topical depth: Comprehensive vs. niche.
  • Keywords/Entities: Specific terms and entities frequently mentioned.
  • Structured data implementation: What schema types are used?
  • Internal linking patterns: How is this content connected to other relevant pages?
  • Upgrade underperformers: Apply these successful attributes to content that currently receives less AI crawler attention.
  • Refine content structure: Break down dense paragraphs, add more headings, and use bullet points for lists.
  • Inject structured data: Implement relevant Schema markup (e.g., `Q&A`, `HowTo`, `Article`, `FactCheck`) on pages lacking it.
  • Enhance clarity: Rewrite sections to achieve conciseness and directness, focusing on clearly answering potential user questions.
  • Expand Authority: Add references, link to authoritative sources, or update content with the latest insights.
  • Improve Internal Linking: Ensure that relevant underperforming pages are linked from your AI-favored content and vice versa, signaling topical clusters.

This short video walks you through the process of discovering what pages are crawled most often by AI crawlers and how to use that information to start your optimization strategy.

Here is the prompt used in the video:

You are an expert in AI-driven SEO and search engine crawling behavior analysis.

TASK: Analyze and explain why the URL [https://fioney.com/paying-taxes-with-a-credit-card-pros-cons-and-considerations/] was crawled 5 times in the last 30 days by the oai-searchbot(at)openai.com crawler, while [https://fioney.com/discover-bank-review/] was only crawled twice.

GOALS:

– Diagnose technical SEO factors that could increase crawl frequency (e.g., internal linking, freshness signals, sitemap priority, structured data, etc.)

– Compare content-level signals such as topical authority, link magnet potential, or alignment with LLM citation needs

– Evaluate how each page performs as a potential citation source (e.g., specificity, factual utility, unique insights)

– Identify which ranking and visibility signals may influence crawl prioritization by AI indexing engines like OpenAI’s

CONSTRAINTS:

– Do not guess user behavior; focus on algorithmic and content signals only

– Use bullet points or comparison table format

– No generic SEO advice; tailor output specifically to the URLs provided

– Consider recent LLM citation trends and helpful content system priorities

FORMAT:

– Part 1: Technical SEO comparison

– Part 2: Content-level comparison for AI citation worthiness

– Part 3: Actionable insights to increase crawl rate and citation potential for the less-visited URL

Output only the analysis, no commentary or summary.

Note: You can find more prompts for AI-focused optimization in this article: 4 Prompts to Boost AI Citations.

By taking this data-driven approach, you move beyond guesswork and build an AI content strategy grounded in actual machine behavior on your site.

This iterative process of tracking, analyzing, and optimizing will ensure your content remains a valuable and discoverable resource for the evolving AI search landscape.

Final Thoughts On AI Optimization

Tracking and analyzing AI crawler behavior is no longer optional for SEOs seeking to remain competitive in the AI-driven search era.

By using log file analysis tools – or simplifying the process with SEO Bulk Admin – you can build a data-driven strategy that ensures your content is favored by AI engines.

Take a proactive approach by identifying trends in AI crawler activity, optimizing high-performing content, and applying best practices to underperforming pages.

With AI at the forefront of search evolution, it’s time to adapt and capitalize on new traffic opportunities from conversational search engines.

Leverage AI Insights

Image Credits

Featured Image: Image by TAC Marketing. Used with permission.

In-Post Images: Image by TAC Marketing. Used with permission. 

Ecommerce MGMT 0 Comments
Nov 7 2025
Google’s Preferred Sources Tool Is Jammed With Spam via @sejournal, @martinibuster

Google’s Preferred Sources tool is meant to let fans of certain websites tell Google they want to see more of their favorite sites in the Top News feature. However, Google is surfacing copycat spam sites, random sites, and parked domains. Some of the sites appearing in the tool are so low quality that only their home pages are indexed. Shouldn’t this tool just show legitimate websites and not spam?

Google Preferred Sources

Google’s Preferred Sources feature gives users control over which news outlets appear more often in Google’s Top Stories feature. Rather than relying on Google’s ranking system alone, users can make their preferred news sources appear more frequently. This change doesn’t block other sites from appearing, it only personalizes what a user sees to reflect their chosen sources. Preferred Sources enablers users to have more control over which news sources appear more often.

Similar Domains In Preferred Sources

What appears to be happening is that people are registering domains that are similar to those of well-known websites. One way they’re doing it is by domain squatting on an exact match to domain name using a different TLD. For example, when a popular domain name is registered with a .com or .net the domain squatters will register the same domain name using a .com.in or .net.in domain name.

Screenshot Of A Random Subdomain Ranking For Automattic

Preferred Sources Errors

It’s unclear if people are registering domain names and adding them to the Preferred Sources tool or if they are being added in some different manner. A search for a popular SEO tool surfaces the correct domain but also a parked domain in the Indian .com.in ccTLD:

Screenshot Of An Indian Parked Domain

What is known is that people are registering copycat domains but how they’re getting into Google’s Preferred Sources tool is not well known. Preferred Sources is currently available in the USA and in India, which may explain the Indian domains showing up in the tool.

Screenshot Of Indian NYTimes Parked Domain

For example, a search within the Preferred Sources tool for Huffpost surfaces a copycat site on an Indian country code level domain.

Screenshot Of HuffPost In Source Preferences

That site Indian Huffpost site features articles (and links) to topics like payday loans, personal injury lawyers, and luxury watches. Not surprisingly, it doesn’t look like Google is indexing more than the home page of that site.

Screenshot Of A Site Search

There’s also an Indian site squatting on Search Engine Journal’s domain name.

Screenshot Of SEJ In Source Preferences Tool

What Is Going On?

It’s possible that SEOs are registering copycat domains and then submitting their domains to the Preferred Sources tool. Or it could be that Google picks them up automatically and is just listing whatever is out there.

Ecommerce MGMT 0 Comments
Nov 6 2025
The New Optimization Stack: Where SEO Meets AI Retrieval via @sejournal, @DuaneForrester

Search isn’t ending. It’s evolving.

Across the industry, the systems powering discovery are diverging. Traditional search runs on algorithms designed to crawl, index, and rank the web. AI-driven systems like Perplexity, Gemini, and ChatGPT interpret it through models that retrieve, reason, and respond. That quiet shift (from ranking pages to reasoning with content) is what’s breaking the optimization stack apart.

What we’ve built over the last 20 years still matters: clean architecture, internal linking, crawlable content, structured data. That’s the foundation. But the layers above it are now forming their own gravity. Retrieval engines, reasoning models, and AI answer systems are interpreting information differently, each through its own set of learned weights and contextual rules.

Think of it like moving from high school to university. You don’t skip ahead. You build on what you’ve already learned. The fundamentals (crawlability, schema, speed) still count. They just don’t get you the whole grade anymore. The next level of visibility happens higher up the stack, where AI systems decide what to retrieve, how to reason about it, and whether to include you in their final response. That’s where the real shift is happening.

Traditional search isn’t falling off a cliff, but if you’re only optimizing for blue links, you’re missing where discovery is expanding. We’re in a hybrid era now, where old signals and new systems overlap. Visibility isn’t just about being found; it’s about being understood by the models that decide what gets surfaced.

This is the start of the next chapter in optimization, and it’s not really a revolution. It’s more of a progression. The web we built for humans is being reinterpreted for machines, and that means the work is changing. Slowly, but unmistakably.

Image Credit: Duane Forrester

Algorithms Vs. Models: Why This Shift Matters

Traditional search was built on algorithms, sets of rules, linear systems that move step by step through logic or math until they reach a defined answer. You can think of them like a formula: Start at A, process through B, solve for X. Each input follows a predictable path, and if you run the same inputs again, you’ll get the same result. That’s how PageRank, crawl scheduling, and ranking formulas worked. Deterministic and measurable.

AI-driven discovery runs on models, which operate very differently. A model isn’t executing one equation; it’s balancing thousands or millions of weights across a multi-dimensional space. Each weight reflects the strength of a learned relationship between pieces of data. When a model “answers” something, it isn’t solving a single equation; it’s navigating a spatial landscape of probabilities to find the most likely outcome.

You can think of algorithms as linear problem-solving (moving from start to finish along a fixed path) while models perform spatial problem-solving, exploring many paths simultaneously. That’s why models don’t always produce identical results on repeated runs. Their reasoning is probabilistic, not deterministic.

The trade-offs are real:

  • Algorithms are transparent, explainable, and reproducible, but rigid.
  • Models are flexible, adaptive, and creative, but opaque and prone to drift.

An algorithm decides what to rank. A model decides what to mean.

It’s also important to note that models are built on layers of algorithms, but once trained, their behavior becomes emergent. They infer rather than execute. That’s the fundamental leap and why optimization itself now spans multiple systems.

Algorithms governed a single ranking system. Models now govern multiple interpretation systems (retrieval, reasoning, and response), each trained differently, each deciding relevance in its own way.

So, when someone says, “the AI changed its algorithm,” they’re missing the real story. It didn’t tweak a formula. It evolved its internal understanding of the world.

Layer One: Crawl And Index, Still The Gatekeeper

You’re still in high school, and doing the work well still matters. The foundations of crawlability and indexing haven’t gone away. They’re the prerequisites for everything that comes next.

According to Google, search happens in three stages: crawling, indexing, and serving. If a page isn’t reachable or indexable, it never even enters the system.

That means your URL structure, internal links, robots.txt, site speed, and structured data still count. One SEO guide defines it this way: “Crawlability is when search bots discover web pages. Indexing is when search engines analyze and store the information collected during the crawling process.”

Get these mechanics right and you’re eligible for visibility, but eligibility isn’t the same as discovery at scale. The rest of the stack is where differentiation happens.

If you treat the fundamentals as optional or skip them for shiny AI-optimization tactics, you’re building on sand. The university of AI Discovery still expects you to have the high school diploma. Audit your site’s crawl access, index status, and canonical signals. Confirm that bots can reach your pages, that no-index traps aren’t blocking important content, and that your structured data is readable.

Only once the base layer is solid should you lean into the next phases of vector retrieval, reasoning, and response-level optimization. Otherwise, you’re optimizing blind.

Layer Two: Vector And Retrieval, Where Meaning Lives

Now you’ve graduated high school and you’re entering university. The rules are different. You’re no longer optimizing just for keywords or links. You’re optimizing for meaning, context, and machine-readable embeddings.

Vector search underpins this layer. It uses numeric representations of content so retrieval models can match items by semantic similarity, not just keyword overlap. Microsoft’s overview of vector search describes it as “a way to search using the meaning of data instead of exact terms.”

Modern retrieval research from Anthropic shows that by combining contextual embeddings and contextual BM25, the top-20-chunk retrieval failure rate dropped by approximately 49% (5.7 % → 2.9 %) when compared to traditional methods.

For SEOs, this means treating content as data chunks. Break long-form content into modular, well-defined segments with clear context and intent. Each chunk should represent one coherent idea or answerable entity. Structure your content so retrieval systems can embed and compare it efficiently.

Retrieval isn’t about being on page one anymore; it’s about being in the candidate set for reasoning. The modern stack relies on hybrid retrieval (BM25 + embeddings + reciprocal rank fusion), so your goal is to ensure the model can connect your chunks across both text relevance and meaning proximity.

You’re now building for discovery across retrieval systems, not just crawlers.

Layer Three: Reasoning, Where Authority Is Assigned

At university, you’re not memorizing facts anymore; you’re interpreting them. At this layer, retrieval has already happened, and a reasoning model decides what to do with what it found.

Reasoning models assess coherence, validity, relevance, and trust. Authority here means the machine can reason with your content and treat it as evidence. It’s not enough to have a page; you need a page a model can validate, cite, and incorporate.

That means verifiable claims, clean metadata, clear attribution, and consistent citations. You’re designing for machine trust. The model isn’t just reading your English; it’s reading your structure, your cross-references, your schema, and your consistency as proof signals.

Optimization at this layer is still developing, but the direction is clear. Get ahead by asking: How will a reasoning engine verify me? What signals am I sending to affirm I’m reliable?

Layer Four: Response, Where Visibility Becomes Attribution

Now you’re in senior year. What you’re judged on isn’t just what you know; it’s what you’re credited for. The response layer is where a model builds an answer and decides which sources to name, cite, or paraphrase.

In traditional SEO, you aimed to appear in results. In this layer, you aim to be the source of the answer. But you might not get the visible click. Your content may power an AI’s response without being cited.

Visibility now means inclusion in answer sets, not just ranking position. Influence means participation in the reasoning chain.

To win here, design your content for machine attribution. Use schema types that align with entities, reinforce author identity, and provide explicit citations. Data-rich, evidence-backed content gives models context they can reference and reuse.

You’re moving from rank me to use me. The shift: from page position to answer participation.

Layer Five: Reinforcement, The Feedback Loop That Teaches The Stack

University doesn’t stop at exams. You keep producing work, getting feedback, improving. The AI stack behaves the same way: Each layer feeds the next. Retrieval systems learn from user selections. Reasoning models update through reinforcement learning from human feedback (RLHF). Response systems evolve based on engagement and satisfaction signals.

In SEO terms, this is the new off-page optimization. Metrics like how often a chunk is retrieved, included in an answer, or upvoted inside an assistant feed back into visibility. That’s behavioral reinforcement.

Optimize for that loop. Make your content reusable, designed for engagement, and structured for recontextualization. The models learn from what performs. If you’re passive, you’ll vanish.

The Strategic Reframe

You’re not just optimizing a website anymore; you’re optimizing a stack. And you’re in a hybrid moment. The old system still works; the new one is growing. You don’t abandon one for the other. You build for both.

Here’s your checklist:

  • Ensure crawl access, index status, and site health.
  • Modularize content and optimize for retrieval.
  • Structure for reasoning: schema, attribution, trust.
  • Design for response: participation, reuse, modularity.
  • Track feedback loops: retrieval counts, answer inclusion, engagement inside AI systems.

Think of this as your syllabus for the advanced course. You’ve done the high school work. Now you’re preparing for the university level. You might not know the full curriculum yet, but you know the discipline matters.

Forget the headlines declaring SEO over. It’s not ending, it’s advancing. The smart ones won’t panic; they’ll prepare. Visibility is changing shape, and you’re in the group defining what comes next.

You’ve got this.

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This post was originally published on Duane Forrester Decodes.

Featured Image: SvetaZi/Shutterstock

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