The label doesn’t matter nearly as much as understanding the shift behind it.
At the center of that shift lies one idea that explains everything: AI availability – and here’s why it matters.
What is AI availability?
The idea of AI availability comes from Byron Sharp, research professor at the Ehrenberg-Bass Institute, who introduced it in a comment on one of my LinkedIn posts.
Sharp’s work underpins modern brand science and shows that growth depends on availability.
Brands grow through sales, and sales grow through two kinds of availability: mental and physical.
Mental availability refers to the likelihood of being considered in a purchasing situation.
Physical availability refers to the ease and convenience with which an item can be bought.
For years, these two principles have guided brand strategy.
They explain why Coca-Cola invests in constant visibility and why Amazon makes every click lead to a checkout.
But in the era of generative search, there’s now a third kind of availability marketers need to understand – the likelihood that your brand or product will be recommended by an AI system when a user is ready to buy.
That is AI availability – and it changes everything.
AI as the new influencer
If you are still thinking of AI as a technology, you are already behind.
Think of it instead as the world’s most powerful influencer.
ChatGPT alone is used by about 10% of the global adult population, according to recent research from OpenAI, Harvard, and Duke.
That makes it far more pervasive than any social media platform at a similar stage in its life cycle.
Most people do not use it to code or write poetry – they use it to make decisions.
Nearly 80% of ChatGPT conversations, the same study found, fall into three categories:
Practical guidance.
Seeking information.
Writing.
In other words, people are asking AI to help them decide what to do, buy, and believe.
The study also shows that these conversations are increasingly focused on everyday decisions rather than work.
The distinction between search, research, and conversation is collapsing.
AI systems are now the gatekeepers of modern discovery. They decide what information to surface and which businesses appear in front of consumers.
Forget the Kardashians. Forget influencer marketing.
If you’re invisible to AI, you’re invisible to the market.
AI is the new influencer.
From keywords to fitness signals
The SEO industry has spent two decades optimizing for how humans search with keywords – but that is changing.
Large language models (LLMs) infer meaning from context, probability, and performance.
They are scanning for what we can call fitness signals – a term from network science.
Fitness describes a product or service’s inherent ability to outcompete rivals, allowing one business to dominate a market even if others started earlier or invested more.
Think of how Google overtook Yahoo.
It wasn’t just about better search algorithms – it was a better business model built on a stronger performance attribute: relevance.
These performance attributes are what make a business fit for survival. They are the qualities that define how well you solve a problem for a customer.
AI deploys search strategies to identify which businesses solve which problems most effectively.
Because it exists to serve human needs, those same signals determine your AI availability.
Yes, AI uses search strings, fan-out queries, and reciprocal rank fusion, among many other strategies and tactics.
It doesn’t search like humans because it isn’t bound by the same cognitive and speed limitations.
Humans search by “satisficing.” Keywords + Page 1 rankings = good enough.
Machines operate on an industrial scale – searching, gathering, assessing, and recommending.
To make your brand visible to machines that now mediate discovery, you need to understand how and where that visibility is built.
Start with a visibility audit
Diagnose your current presence.
Identify the category entry points most relevant to your products, and ask what prompts a user might type when they are ready to buy.
Tools such as Semrush’s AI Enterprise platform can simulate these scenarios and show where your brand appears.
Get listed where AI looks
Identify the sources that AI models reference.
Many LLMs use a mix of training data and live search, with listicles, directories, and “best of” articles among the most common data sources.
Being included in those lists is a sensible marketing strategy.
Just as supermarkets stock their own shelves with their best products, you should position your brand among the best available options.
Expand your owned ecosystem
Over time, you’ll find saturation points where every competitor appears in the same lists.
At that stage, innovation and owned media become essential.
Start your own publication, commission original research, and contribute to conversations in your category.
Create context that earns recommendations
Digital shelf space isn’t the problem. Credible context amplifies your fitness signals.
Efficient, data-led, and creative, this is GEO’s manufactured style. But its success depends entirely on having a brand worth recommending.
That’s why GEO is the outcome of proper marketing.
Still, it’s proper marketing with a specific focus: increasing the likelihood of being recommended by AI.
The future of visibility
SEO has always been about optimization.
GEO is about promotion – building and distributing enough credible, distinctive information about your business that an AI can recognize it as a trusted source.
The techniques look familiar: PR, branding, copywriting, partnerships, directories, and reviews.
The difference lies in intent. You’re not feeding a search engine – you’re training an intelligence.
This requires a new mindset.
You’re no longer optimizing for human users who type short queries into Google. You’re optimizing for a probabilistic model that interprets human intent across millions of contexts.
It doesn’t care about your title tags. It cares about whether you look like the right answer to a real problem.
GEO is both exciting and humbling.
It reconnects brand marketing and search after years of false division, and reminds us that while the tools evolve, the fundamentals endure.
You still need to be known, available, and distinctive.
And now your audience includes machines that think like humans but learn on their own terms.
Back to fundamentals, forward with AI
GEO is a return to marketing fundamentals seen through a new lens.
Businesses still grow by increasing availability.
Consumers still buy from the brands they notice and can easily access.
What has changed is the mediator: AI has become the primary distributor of attention.
Your task as a marketer is to make your brand’s performance attributes, category entry points, and distinctive assets visible in the data that AI consumes.
The goal hasn’t changed – to be chosen. Only the mechanics are new.
Because in the age of AI, the only brands that matter are the ones the machines remember.
https://i0.wp.com/dubadosolutions.com/wp-content/uploads/2025/11/The-three-pillars-of-brand-availability-A9cyga.png?fit=696%2C780&ssl=1780696http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-11-11 15:00:442025-11-11 15:00:44Why AI availability is the new battleground for brands
Keywords in reviews are generally believed to help local rankings, although their impact is still actively debated within the local SEO community.
Regardless of where the truth on ranking impact ultimately lands, keyword-rich reviews can still provide meaningful value for local SEO beyond pure rankings.
Below are seven reasons why you should still encourage keyword-rich reviews.
1. Review justifications
If your reviews consistently mention a keyword related to your business, the likelihood that your Profile will get a Review justification in search increases.
This visibility can boost click-through rates. Higher engagement may lead to a secondary improvement in search engine rankings.
2. Place Topics
Google creates clickable Place Topics from keywords in your reviews. These topics:
Highlight your specialties.
Filter reviews for customers.
Can boost your Profile’s engagement.
3. Review snippets
Google bolds frequently mentioned terms in three review snippets on the Business Profile. This draws users searching for those terms to your Profile, hopefully increasing click-through rates.
4. Menu Highlights (restaurants)
The Menu Highlights are generated from customer reviews and photos, similar to Place Topics.
Keywords in reviews impact the Menu Highlights section.
Therefore, when you get a menu highlight for a term mentioned in your reviews, you should rank better for that term.
5. AI editorial summaries
Google’s AI-generated business summaries pull concepts from reviews (e.g., “cozy”) to describe your business.
While Google’s AI summaries aren’t something you can edit, encouraging customers to include specific keywords in their reviews could influence the AI to emphasize aspects most beneficial to your business.
6. AI review summaries
Google’s AI generates review summaries by analyzing common sentiments and tips from customer feedback.
If your customers mention the right keywords in their reviews, your review summary will appear more compelling.
7. Ask Maps about this place feature
Google is phasing out the old Q&A section and replacing it with an AI-powered feature that pulls answers from customer reviews.
This means reviews with detailed info (and the right keywords) are more valuable than ever.
How do you get keywords in your reviews?
It does not make sense to directly ask your customers, “Can you please add [keyword] to your review?” It’s unnatural and weird and will leave the customer wondering what your deal is.
But that doesn’t mean you have no options.
To encourage customers to naturally include relevant keywords in their reviews, begin by upgrading your review request templates.
Miriam Ellis recently wrote a helpful guide all about how to get keyword-rich reviews, which also includes three review request templates to make it extra easy for every business owner.
These templates guide customers on what to say, encouraging longer, more detailed, keyword-rich reviews — and can even prompt them to add photos to their reviews.
Here are three of those templates:
Scenario 1: Requesting reviews of specific products
Hi [customer name], I’m [your name and job title] from [company name], and I’m writing to check in with you on your purchase of [product]. It’s my job to be sure you’re satisfied, and I wondered if you would be willing to provide your feedback in a review at [link]? I’m enclosing a photo of [product] for your use in your review if you don’t have your own photo, and I’d be so grateful if you could review your experience with: – The features of this product that stand out most to you– What you like or dislike about it– How you’ve been using the product since you purchased it If there’s anything we could have done better for you, please feel free to contact us directly at [phone number or feedback form link]. I want to be sure you’re fully satisfied and we’re so grateful for your business. Thank you very much if you can take the time to tell us about your personal experience in your review. [review us here link or button] Sincerely,[name, job title, business]
Scenario 2: Requesting reviews of specific services
Hello [customer name], This is [your name and job title] from [company name], and we were so happy to [service provided]. It’s my job to be sure you’re satisfied, and I wondered if you would be willing to provide your feedback in a review at [link]? I’m enclosing a photo of [the service that was provided] for your use in your review if you don’t have your own photo, and I’d be so grateful if you could review your experience with: – Whether the service met your expectations– What you like/dislike about the service– How we did with our customer service If there’s anything we could have done better for you, please feel free to contact us directly at [phone number or feedback form link]. I want to be sure you’re fully satisfied, and we’re so grateful for your business. Thank you very much if you can take the time to tell us about your personal experience in your review. [review us here link or button] Sincerely,[name, job title, business]
Scenario 3: Requesting reviews when you’re not sure what a customer purchased
Email template
Hello [customer name], Thank you for being our customer. I’m [your name and job title] from [company name], It’s my job to be sure you’re satisfied, and I wondered if you would be willing to provide your feedback in a review at [link]? I’m enclosing a photo of [the business premises] for your use in your review if you don’t have your own photo, and I’d love it if you could review: – Whether you found our customer service helpful– What you like/dislike about our store– Why you chose our store If there’s anything we could have done better for you, please feel free to contact us directly at [phone number or feedback form link]. I want to be sure you’re fully satisfied and we’re so grateful for your business. Thank you very much if you can take the time to tell us about your personal experience in your review. [review us here link or button] Sincerely,[name, job title, business]
Now, make it work for you
By implementing a few simple improvements in your review requests, you will receive more detailed reviews from your customers, and their enhanced feedback will provide numerous benefits.
You may even increase your Google rankings for additional keywords, but I can’t guarantee anything. With all the other benefits, rankings shouldn’t be your primary goal anyway.
https://i0.wp.com/dubadosolutions.com/wp-content/uploads/2025/11/plumbing-google-review-justifications-y1aXp1.webp?fit=1999%2C974&ssl=19741999http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-11-11 13:00:002025-11-11 13:00:007 local SEO wins you get from keyword-rich Google reviews
Google is rolling out asset-level reporting for Display campaigns, giving advertisers a clearer view of how individual creative assets perform — a move that brings Display closer to the visibility already seen in Performance Max campaigns.
Why we care. Until now, Display campaign insights have been limited to overall ad performance. With this update, advertisers can analyze results at the asset level — images, headlines, descriptions — to pinpoint what’s driving engagement and what’s not.
How it works. A new Assets tab in Google Ads will let users:
Compare performance of each creative asset.
View when assets were last updated to track iteration history.
Decide which assets to keep, refresh, or remove based on data.
The details. A new Google support page, “About asset reporting in Display,” outlines the update with links to:
Get started
How it works
Asset reporting for your Display campaigns
Evaluating asset performance
Between the lines. This upgrade mirrors reporting tools available in Performance Max, signaling Google’s continued effort to unify insights across campaign types and improve transparency in automated advertising.
What’s next. The feature hasn’t been spotted live yet, but its appearance on Google’s help center — first noticed by PPC News Feed founder Hana Kobzová — suggests a wider rollout is imminent.
A recent Google blog post announced the expansion of Opal, a Google tool that uses AI to get people create mini apps, and touted that the tool can be used to create “optimized” content in a “scalable way.” Many SEOs are asking if this is against Google search guidelines, specifically the scaled content abuse policy.
What Google wrote. Google wrote on the Google blog about reasons one should use Opal:
“Creators and marketers have also quickly adopted Opal to help them create custom content in a consistent, scalable way.”
“Marketing asset generators: Tools that take a single product concept and instantly generate optimized blog posts, social media captions and video ad scripts.”
“Scaled content abuse is when many pages are generated for the primary purpose of manipulating search rankings and not helping users. This abusive practice is typically focused on creating large amounts of unoriginal content that provides little to no value to users, no matter how it’s created.”
The examples Google provided include:
“Using generative AI tools or other similar tools to generate many pages without adding value for users.”
Is this against Google’s policies. So the big question is, what Google promoted on its blog as a reason to use Opal is actually against Google’s policies. Google can argue that as long as your “primary purpose” is not “of manipulating search rankings” and it is to help users, than it is fine to use Opal or any other AI tool.
In fact, Reddit talked about how it was using AI tools to translate its pages at scale and it turned out, Google was okay with it.
SEOs not happy. Many SEOs feel these are double-standards and think Google should take a strong stance on using AI to generate content. Here are some of the complaints I posted from the community:
Google has historically opposed to any kind of content creation “at scale”. So, I’m a bit sad to see this language in their official communication channels
Google has employees who have been trying to get rid of spam for decades, and now it’s offering AI spam creation services. I wonder how those employees feel about this.
Well, they are not always opposed to it. I wrote a two-part article covering Reddit’s AI translations. That’s massive scaling but Google is OK with it.
They provided this statement to me at the time: “While we don’t comment on the status of specific sites or pages, nor do we… pic.twitter.com/WNKjklzzq7
Why we care. Everyone is talking about “AI slop” and how it can ruin the web. When it comes to Google Search, Google has said it has algorithms to reward content that is helpful to users and that AI is not necessarily a bad thing.
Ultimately, if you are going to be using an AI tool, like Opal, to help you create content, you should use it as a tool and let it help you but don’t let it do it for you, fully automated, without oversight and at incredible scale.
Be careful with these tools.
I should note, we reached out to Google for a statement but we have not heard back yet. If we do, we will update the story with that statement.
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Google statement. Google sent me the following statement:
This Google Labs experiment helps people develop mini-apps, and we’re seeing people create apps that help them brainstorm narratives and first drafts of marketing content to build upon. In Search, our systems aim to surface original content and our spam policies are focused on fighting content that is designed to manipulate Search while offering little value to users.
https://i0.wp.com/dubadosolutions.com/wp-content/uploads/2021/12/web-design-creative-services.jpg?fit=1500%2C600&ssl=16001500http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-11-10 17:00:082025-11-10 17:00:08Google’s new AI tool touts creating optimized content in a scalable way
As of this writing, Reddit’s stock price has risen 177.6%. If you’d bought 100 shares of RDDT then, you’d be $13,113 richer today.
In a June 2025 analysis of 150,000 AI citations, Semrush found that Reddit was the top source, appearing in more than 40% of LLM responses.
So what happened? It comes down to the law of supply and demand.
The supply-and-demand crisis of online answers
The demand for answers has skyrocketed as people increasingly turn to LLMs.
ChatGPT, Perplexity, Gemini, and Grok will try to come up with the answers from their training data, and failing that, they’ll search the web.
ChatGPT uses Bing, Gemini uses Google, and Claude, Grok, and Perplexity use their own internal search engine.
The web search engine will quickly find that the supply of long-tail answers is nonexistent.
And so it will surface the closest thing it can find: a Reddit thread that matches the keywords, but could very well have been written by a novice, an armchair expert, or a troll.
Whose fault is it that the web is devoid of meaningful long-tail content?
Ultimately, it was Google’s.
Even the best SEO professionals among us were told by our clients and bosses that nothing mattered except for the One Ring – getting ranked on the top for a competitive head term.
We all started to write the same blog posts to try to grab that top spot, while the vast long tail went ignored.
The irony is that if your brand has any kind of expertise or authority in your space, you always could – and still can – completely own the undiscovered country of the long-tail of search for your industry, a frontier of questions no brand has yet answered.
The advantages of user-generated content
The best way to do this – by far – is through user-generated content (UGC), which has several key characteristics:
It matches search intent: Users post the same way they search, using the same words.
It’s always up-to-date: New posts keep topics current without constant editorial work.
It’s accurate: Assuming your brand can attract experienced experts who contribute, each new reply will add value or correction.
It builds semantic depth: Conversations naturally surface related terms, subtopics, and entities that boost SEO and LLM discovery.
It’s trustworthy and AI-proof: Authentic human discussion is the one thing that LLMs can’t replicate.
If this all sounds familiar to you, it’s the same old E-E-A-T that Google has been trying to get us to do for years.
Only now, it really counts.
Why brands hesitate
Most companies instinctively resist the idea of launching a forum.
Here are the objections I hear most often – and how I respond.
It’s too expensive: Ironically, forum and Q&A software is among the most mature software in the open-source world. You can literally have a production-ready system up and running in a week at a cost less than a few cups of coffee. I’ll share some examples below.
We don’t have the development resources: If you’re not familiar with the concept of open-source, you don’t need development resources other than for tasks like skinning and building single sign-on, which your developers can do in their sleep.
We tried it before, and it didn’t work: In most cases, this is because forums were treated as side projects, and not owned media.
There’s no clear ROI: Forums have always reduced support tickets, but because it’s hard to prove a negative, most companies treated both online and offline customer service as cost centers – and the first things to cut. Today, forums still lower service costs and add valuable, search-friendly content. It’s time to redo the math.
Moderation is too much of a hassle: Today’s spam filters, coupled with smart heuristics, enforced policies, and AI-supported moderation, can handle 90% of bad actors. A strong community of users and in-house moderators can easily handle the rest.
Everyone’s already on Reddit or Discord: Exactly. And those platforms own your audience, your brand, and your data. It’s time to take it back.
Forums are outdated: Reddit is a forum. It has a market cap of $38 billion. Time to re-do the math on that one, too.
Discussion boards vs. Q&A sites
I tend to use the phrase “forums” interchangeably to refer to two kinds of sites: discussion boards and Q&A sites.
There are key differences, depending on your company’s goals.
A discussion board is built for ongoing conversation.
It’s a social space where customers can connect, share experiences, swap ideas, and engage in the occasional friendly debate, like an always-on company event or conference.
A Q&A site, by contrast, is built for resolution. Each post centers on a single question from a community member.
Some brands limit responses to verified experts, while others invite the whole community to contribute and vote on the best answer.
The goal is clarity: one question, one accepted solution.
Both formats create a treasure trove of owned, uniquely human content.
While other companies rely on generative AI to churn out soulless copy, with the help of your community, you’ll be building fresh content that feeds AI and, more importantly, reaches real customers.
As derivative AI-generated content floods the web, that authentic human signal will become a huge competitive edge.
While many enterprise and SaaS options exist, most businesses can start with open-source software – ideal for small, mid-sized, or cost-conscious enterprises.
Here’s why open source makes sense.
Open source software is free
Every software package I recommend below will be free.
All you need is a web server or hosting plan (your own infrastructure, a cloud provider, or even a managed host), and you can run it yourself.
Open source software is customizable
Most mature open-source platforms enable brands to easily customize and extend functionality through plug-ins and extensions – all with a fraction of the development effort required to build a system from scratch.
Instead of building a huge system from scratch, your team can focus on customization, such as:
Customizing the front-end design to match your brand website.
Using single sign-on with your existing customer database to make access seamless for your customers.
Adding reputation and gamification systems, such as upvotes, leaderboards, and badges, to promote the most credible voices.
You own your own data
When you self-host your forum, you own the data and can export it at any time, with no dependencies on third-party platforms or APIs.
This is increasingly important as we enter an era where unique content is literally an asset.
SEO and LLM visibility
Most mature forum and Q&A software have SEO best practices built in, from automatic title tags to best internal linking practices that make it easy for search engines and AI bots to discover content.
Moderation tools
Active moderation is crucial to the success of online communities.
Choosing the right discussion board software
After extensive research, my go-to recommendations for discussion boards are Flarum and Discourse.
I like Flarum for its sleek, minimalist interface and Reddit-like familiarity.
Built on PHP with Laravel components, it’s fast, lightweight, and highly extensible, supported by an active developer community.
It’s ideal for small to mid-sized businesses, startups, and niche communities.
Discourse is the gold standard for modern forums, built on Ruby on Rails and Ember.js.
It offers robust features out of the box, including SSO, analytics, trust levels, and a powerful API, plus a paid option for fully managed deployments.
Used by major brands like OpenAI, Samsung, and Shopify, it’s ideal for larger organizations, SaaS companies, and professional communities.
Honorable mention goes to NodeBB and phpBB, older platforms that require a bit more care and feeding, but also have their advantages.
Platforms built for Q&A
My go-tos here include Apache Answer and Question2Answer.
Apache Answer is a modern, actively supported platform from the Apache Software Foundation, with a solid pedigree.
Built on Go and Vue.js, it offers a full feature set – voting, accepted answers, categories, and a Reddit-style reputation system.
Question2Answer, first released in 2010 and still actively maintained, is inspired by Stack Overflow, offering features such as voting and tagging.
Its out-of-the-box interface looks dated, but a good designer can easily modernize it. It’s built in PHP.
AskBot and Scoold are also worth exploring.
Test them out. They all have links to a demo and real-world client implementations on their sites.
Find one you like. Pay $50 for a shared web hosting service, and another $50 for pizza for engineers and developers.
You’ll have a fully functional forum within a week.
Where most forums succeed – or fail
Unlike most software projects, building a discussion board or Q&A site is relatively straightforward.
But it’s maintaining and running it that will determine whether it’ll be successful.
I’ve been fortunate enough to have launched, managed, and moderated several successful discussion forums and Q&A sites over the years.
Here’s some practical advice.
Have a zero tolerance for spam
I mentioned this in my previous article; it’s the number one reason forums fail.
The moment you launch a discussion board, it will be attacked.
Fortunately, tools like Akismet, StopForumSpam, CleanTalk, and reCAPTCHA can block most spam before it reaches your site.
You can even run your server logs through an LLM to generate smart filtering rules for your CDN.
And if anything slips through, remove it fast – spam spreads apathy faster than any troll.
With Q&A sites, you’ll have a bit more control, depending on how many of the questions and answers you’d like to open up to the public.
Require detailed and authentic titles
This is another Achilles’ Heel of many forums.
Discussion boards often have non-descript titles, such as “Help!” or “Need Advice!” You’ll also want to have a zero-tolerance policy toward those.
Have instructional copy that reminds them to leave detailed titles, and if any slip through the cracks, either generate a title for them or reject the post.
Similarly, for Q&A sites, your titles must reflect actual questions that users ask in their own language, not the words of a marketer or other internal voice.
Seed popular topics
To understand the questions people are asking, review:
Your on-site search data.
Google Search Console data.
Customer service inquiries.
External sites like Reddit.
Post them to the discussion board from a moderator account, provide high-quality answers, and invite comments.
As long as you’re authentic and transparent, users will respond.
Establish clear, public community guidelines
Set rules and boundaries clearly up-front and display them prominently.
Keep them short enough that real users will read them, ideally 5-7 bullet points.
Some thought starters:
Linking policy: Generally, you’ll want to allow only accounts that have been vetted or passed certain criteria to be able to post links.
Reinforce tone: “Disagree without being disagreeable”
Rules against harassment and bad language.
Rules against off-topic posts.
Establish clear categories
Define categories and tags clearly.
Take a large pool of typical questions or discussion topics and categorize them. (Hint: Use your favorite LLM to help.)
Ensure that category names are immediately intuitive to users. Move or delete off-topic content quickly.
Empower trusted regulars
Over time, many forums start to attract regular visitors.
If this happens to your brand, tap into their passion by inviting them to take on small moderation privileges (e.g., editing titles, retagging, or flagging spam).
Depending on your relationship with these fans, you can incentivize them with recognition, branded merchandise, free product, or monetary compensation.
Community self-correction scales far better than centralized policing.
Gamify contributions for everyone with leaderboards, badges, upvote milestones, etc.
Archive or merge duplicates
Especially in Q&A boards, you’ll want to make sure to avoid repeating questions.
That causes duplicate content issues for SEO, but worse, it can frustrate visitors.
Own the conversation before your competitors do
There are plenty more ways to run a successful discussion board or Q&A site.
But the most important rule is this: don’t treat it as an SEO tactic, an LLM feeder, or a necessary evil.
Build a destination you and your team would actually want to visit – a place for lively conversation, useful knowledge, and genuine connection with your customers and fans.
That’s the real formula for success.
A year ago, I suggested that you start a forum. This year, it’s not optional.
Reddit has proven that conversation has real value, and your competitors will soon catch on.
Claim the conversations that belong to your brand, and you’ll:
https://i0.wp.com/dubadosolutions.com/wp-content/uploads/2025/11/Reddits-stock-price-NOYADm.webp?fit=733%2C419&ssl=1419733http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-11-10 14:00:002025-11-10 14:00:00The reign of forums: How AI made conversation king
Generative engine optimization (GEO) platform Lorelight, is shutting it down – not because it failed, but because the problem it solved didn’t need solving, according to its founder Benjamin Houy.
“Customers were churning because the product didn’t change what they needed to do. They would pursue the same brand-building fundamentals whether they had the data or not,” Houy wrote in a blog post.
The big idea. Launched in April, Lorelight pitched itself as a “proactive AI brand monitoring” tool. Lorelight promised real-time alerts when large language models, such as ChatGPT or Claude, misrepresented a brand.
The goal: To help marketers control their brand narrative in the age of AI by detecting inaccuracies, biases, or outdated info in AI-generated responses.
Lorelight claimed to offer visibility into how AI models “interpreted” brands and give companies a chance to correct or influence that narrative before misinformation spread.
Why it failed. Lorelight could show where brands appeared (or didn’t) in AI answers, but that data rarely led to new action, according to Houy. After months of analysis, Houy found that the brands showing up most often in AI-generated results shared familiar traits:
High-quality, helpful content.
Mentions in authoritative publications.
Strong reputations and subject-matter expertise.
Houy wrote:
“It’s the exact same stuff that’s always worked for SEO, PR, and brand building.
“There was no secret formula. No hidden hack. No special optimization technique that only applied to AI.
“There’s no secret GEO strategy. AI models reward the same fundamentals that already drive SEO and PR.”
The bigger picture. Houy concluded that GEO makes more sense as a feature within existing SEO platforms, not as a standalone category. Building a dedicated tool for tracking brand visibility in AI responses simply didn’t deliver enough unique value to sustain a business, he said.
Established SEO platforms, including Semrush, have already begun expanding into AI visibility and brand monitoring, integrating features that help marketers understand how brands appear in generative search results.
What they’re saying. Many SEO practitioners applauded the candor, via comments on Houy’s LinkedIn post. Some of the reactions:
Lily Ray said the post was something “the industry needs to hear.”
Gaetano DiNardi called it “saying the quiet part out loud.”
Kristine Strange praised Houy’s courage to step away from the idea he believed in.
Randall Choh countered that LLM visibility is already driving conversions, citing data showing that ChatGPT-sourced signups convert six times better than Google traffic.
Panos Kondylis argued the GEO space is “premature” – visibility tracking is early-stage and most tools echo what SEO platforms already do.
Yes, but. Beware of confirmation bias. One tool’s failure (that you probably hadn’t even heard about before it shut down) doesn’t prove an entire discipline is worthless. It’s still early.
If you believe in the Gartner Hype Cycle, GEO may simply be passing through the Trough of Disillusionment – when inflated expectations crash and weaker players fold before the survivors evolve into something more durable.
Lorelight lived for about seven months – from its April launch to its October shutdown. Its quick demise may be more about timing than the longer-term viability of GEO.
Some advertisers are noticing oddly cropped product images in Google Shopping ads — and it turns out Google Merchant Center’s “Smart Cropping” feature is behind it.
Why we care. Smart Cropping, enabled by default, uses automation to zoom in on what Google determines is the most relevant part of a product image. While the goal is to improve ad visuals, the result can sometimes be awkwardly cropped images that don’t match the uploaded product photos.
The backstory. An email from Google explains that there’s no option in the Merchant Center UI to disable Smart Cropping. Advertisers must instead contact Google support to have it manually turned off for their account.
The tip-off. Zato Founder Kirk Williams first raised the issue after spotting unusual ad visuals despite correctly formatted image uploads. He shared the finding on LinkedIn — and Google’s response — with the PPC community.
The bottom line. If your Shopping ads look off, Smart Cropping could be the culprit. Check your visuals and reach out to Google support if you want the feature disabled.
https://i0.wp.com/dubadosolutions.com/wp-content/uploads/2025/11/1761939627888-1-rUHRhI.jpg?fit=720%2C290&ssl=1290720http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-11-04 18:13:262025-11-04 18:13:26Google’s “Smart Cropping” may be trimming your Shopping Ad images
Google’s AI Overviews and AI-driven search are reshaping content creation, SEO, and user behavior.
As we watch this fascinating evolution of search – and continue to debate what we call this new marketing discipline (HubSpot is opting for AEO, or answer engine optimization) – I interviewed Aja Frost, senior director of global growth and paid media at HubSpot. Some of the topics covered in our interview:
The need to redefine success metrics for AEO, prioritizing visibility and share of voice
HubSpot’s experimental journey, including creating hyperspecific, data-rich content and optimizing for LLMs.
Traffic directly from LLMs converts about 3x better than traditional search traffic for HubSpot.
This transcript has been edited for length and clarity.
Danny Goodwin: Hey everybody, this is Danny Goodwin, editorial director of Search Engine Land, and, today I’m being joined by Aja Frost. We have an interesting discussion coming up about GEO, AEO, AI, and all the good hot topics. It’s great to meet you Aja. ’cause I’ve actually never, uh, run into you on the conferences or anywhere. So it’s really nice to connect with you.
Aja Frost: You know, Danny, I was gonna say, it’s nice to see you, which is my go-to if I’m not sure whether I’ve seen someone, I met someone before. I figured we had met because we definitely run in the same circles. But I’m delighted to be finally, officially making your acquaintance.
Danny Goodwin: Absolutely. Before we dive in for the people watching or listening, do you want to introduce yourself? Tell us a little bit about who you are and what you do?
Aja Frost: Yep. I am Senior Director of Global Growth and Paid Media at HubSpot. Global Growth is our catch-all for top-of-funnel non-paid demand, which largely translates to SEO and now AEO. And I’ve been at HubSpot for a little over nine years, which is about eight years longer than I thought I would be. For those who don’t know, HubSpot is the customer platform that powers 268,000 teams. And it changes, I would say, as a company, every few years, which is what has kept me there. I think we have had a really interesting journey to this point, and we are embarking on what I believe is the most interesting era of SEO, AEO, and really marketing yet.
Danny Goodwin: Absolutely. So, yeah, it is a very fun time and you’ve been around for a few years at this point, so very curious to get your take. So, we had SMX Advanced a while back, our conference returned in person and at that point in time I’m like, oh, this whole a AEO versus GEO versus whatever we’re gonna call a debate – it’s gotta be settled by the time like October, November comes around. And I’m surprised that it has not still been settled. So I’m curious from your perspective, where do you stand on that whole name debate? What are you calling it, you know, this new form of SEO, or if it’s some, even if you consider it a new form of SEO, you know, has been GEO, AEO, some people call it AI SEO. What are you kind of calling this practice right now internally and, and why have you settled on whatever term that is?
Aja Frost: Yeah, great question because this was the topic of much debate internally at HubSpot. I think we debated all of the names that you just mentioned and probably 10 more. And we ultimately landed on AEO, or answer engine optimization, because we think it best reflects how people are using AI and what businesses/brands should be doing in response. So I think SEO, you wanted to rank in the results, like that was pretty clear. Now you wanna be a part of the answer. And so answer engine optimization is the tactics, the plays that you run to show up as part of that answer. Also, it just sounds cooler than GEO in my opinion, but we’ll see how long the debate rages on. I have learned not to underestimate how long people in our particular world can spend haggling and debating this type of thing.
Danny Goodwin: Yes, I know it’s, it’s sort of like subdomains versus subfolders. If you’ve been around long enough, you’ll know what that means and how long that debate has been going on. And I can’t even tell you, uh, more than a decade, I’m safe in assuming. Whatever we call it ultimately or whatever it gets decided it is called, this does feel like a big transition point for search from traditional ranking search to AI search is more about retrieval. So for you, how has it changed the way you’re thinking about visibility and strategy?
Aja Frost: Yeah, we are very much thinking about AEO as an evolution of SEO, which I did my homework and I’m just a Danny Goodwin fan, so I know that I think we’re on the same page there. And yes, that was an intentional pun. I think one thing that has actually always been a very HubSpot philosophy is do what’s best for the customer. And that’s always overlapped really neatly with our SEO strategy. It’s also what Google has preached for many years – do what’s best for the customer. You may miss out on some short-term wins, but in the long run, your site is going to perform better. And that is at the heart of our AEO strategy. I also think that the three buckets of plays that we’re running are familiar from SEO. So the what hasn’t changed, but the how has, and I’ll go a click deeper there. Those three buckets for us are content, technical, and offsite.
Our content for AEO looks fairly different than it does for SEO. It’s much more specific. It’s much nicher and deeper. It’s structured differently. It’s written differently. But it’s always intended to be what’s best for the customer or best for the reader.
The second bucket is technical. And again, I think that Google indexes/ingests content differently than AI bots do. And so we need to adjust our technical strategies to match while not doing anything that’s harmful for GoogleBot, because of course we still care about Google.
And then offsite, one thing that is probably the clearest from SEO to AEO is the emphasis on brand mentions rather than links. And so we’re really shifting our offsite strategy to be much more about positive mentions in the places that AI is training and citing versus getting backlinks on high domain authority websites.
Danny Goodwin: That is a big shift. I think still a lot of people aren’t ready for. So much of the stuff the tactics have been ingrained for – and I forget, how long have you been doing SEO roughly?
Aja Frost: I’ve been doing SEO for a little over a decade.
Danny Goodwin: So SEO is probably about near 30 years old at this point.
Aja Frost: Oh, Danny, we didn’t say we were gonna talk about my age on the podcast.
Danny Goodwin: Hey. But yeah. Um, sorry about that.
Aja Frost: No, they’re all good.
Danny Goodwin: So yeah, I mean, it’s just like, there’s this kind of, this whole playbook I think that a lot of people are attached to. And change is scary for a lot of people. Rethinking that stuff is important because nothing is static. And especially right now things are just kind of chaotic. The amount of changes we’re seeing, it’s crazy.
Aja Frost: Oh my God. Change is so scary.I think change is scary for us. We also had the pressure of not just figuring this out for our own internal strategy, but for figuring it out for our customers. The strategy that we are shipping right now, I have a very direct line to our VP of product for our marketing hub. I also spend a lot of time with the head of product for content hub. Those two products basically represent your website and content strategy and HubSpot. Everything that we’re doing. I’m telling them about the stuff that’s working, the stuff that’s not working, so they can turn that into product learnings as quickly as possible. I think it is terrifying and exhilarating and exciting all at once.
Danny Goodwin: Yeah. And with that change, I think there’s a lot of rethinking about how we define success, right? So AEO is not going to be the same success metrics that we had with SEO. So how are you actually thinking about that right now? It used to be like, how many links can I acquire? But what are you thinking about now? What’s important? Is it visibility in a AI answers, getting citations or mentions the actual conversions from the traffic, which again, is not as large as traffic from search, but – there is debate over whether it’s higher quality at this point, which maybe we’ll get into a little bit later. How are you sort of defining success with AEO?
Aja Frost: This was also a topic of much debate, and we actually published the results on our Loop Marketing page. We have a new scorecard for how companies should be thinking about marketing in the age of AI. And AEO, which fits into this loop marketing framework has a few new North Star metrics.
The first, and the one that I would argue is the most important, is visibility. And it’s visibility and not traffic, or not citations, because visibility is what’s going to ultimately inform whether someone converts. And they might not convert in that session. They’re probably not gonna convert directly from their interaction with the LLM. We know that LLMs just are really bad at navigational search. And so they’re probably opening up a new tab or maybe two days later, five days later, going to the website. But the, the visibility is what informs what we care about, which is the conversion. So that’s number one.
That takes, by the way, a lot of education with your exec leadership. And I am very lucky to work at a company, whose leadership is deeply embedded in all these conversations, and I think gets it. But if you are at a company where your CEO is not reading Search Engine Land, it’s definitely worth doing a deep dive to help them understand why visibility is the number one.
Second is share of voice. So what is your visibility like relative to your competitors? And I think that’s a really useful benchmark. I know that there was a lot of coverage back in mid-September when ChatGPT really turned down the dial on visibility for brands. And if you are just looking at visibility, you might think, oh, something’s going haywire with my strategy. If you look at share voice and share voice is constant or growing, you know that you’re doing the right thing, agnostic of some of the algorithmic changes.
Then we get to mentions, or sorry, mentions goes into visibility, then we get to citations. How many times is your website used as a source in answer engine responses? And I think this is really important. I think a lot of brands go after citations first. I’m putting it third on our list. I think it is important because if you get the citation, what we have found is your average ranking and the response and the sentiment of that description, they’re both better, which makes a ton of sense. If you control the source, you’re always gonna say the nicest things about yourself and put yourself first. If you overindex on citations, however, you’re gonna miss out on a wide swath of visibility that I think is pretty critical.
Danny Goodwin: You’ve done a lot of experimenting, which I want to get into in a minute, with optimizing for LLMs and AI-generated answers. What ways do you see SEO and AEO being similar? And then maybe where do you see them separating a little bit?
Aja Frost: Yeah, I think this goes back to what I was talking about – solving for the customer or doing what is good for the end user. I think that is shared for SEO and AEO. And one of the questions you probably get, ’cause I get it all the time, is, well, if I do this for AEO, will it be bad for SEO? And my answer is always no. If you are doing, if you were rolling out an AEO strategy that is good for the end user.
So an example of what would be bad for the end user would be burying secret instructions in content for an AI agent. A good thing would be creating really helpful specific content that’s going to answer a really niche query that someone is asking ChatGPT. And as long as you are solving for that end user, I think that you’ll benefit in both disciplines. You’ll, benefit in answer engines as well as Google.
And then I think the three higher level categories of plays are similar, but where I think things get very different are, again, the content is just, we’re going from these very broad, high level topics, these ultimate guides, which HubSpot – this is a, I don’t know, a dubious claim to fame. But when I started an SEO at HubSpot, then I was telling the blog team what keywords I thought we should target and, and recommending search friendly titles. And I really liked Ultimate Guide. I just thought it sounded nice. So every title I recommended was Ultimate Guide, this Ultimate Guide that. And then of course, a lot of websites started using Ultimate Guide, and now I’ll click through the SERPs and I see Ultimate Guide. I’m like, I think this is my fault.
So you’re going from the ultimate guide to, you know, this is the exact use case that this exact persona wants to accomplish, and here’s how to do it, and here’s some original data that we’ve gotten from customers just like you. And if you come from an answer engine, it’s gonna be tailored exactly to what we know about you. And so it’s a very different style of content and content journey.
Yeah. Yeah, yeah, for sure. ’cause I, I feel like, and I’ve, I had this conversation not publicly, but there were conversations after the whole bruhaha about all the traffic. HubSpot lost when that, that came out on, I don’t even remember what month that was this year, earlier probably in the spring. And just how much traffic they were losing. Everybody was losing their minds over it. And I was like, wow. You know, you kind of forget the influence that HubSpot had on content marketing as a whole. Your playbook that you guys came up with was used by so many other websites. Like there’s just, you know, repurposed for their specific topic or niche or whatever. But yeah, like HubSpot, that playbook was huge for a lot of years. Right. I think that’s, that was started like right before COVID around that time and then just sort of exploded., Is that the right timeframe?
Aja Frost: I think it depends on what you are talking about. If you’re talking about inbound, inbound I think is really at the heart of the web. At least for a lot of companies that were publishing educational content and inbound goes way, way back. I think we have always been very much a build and public company and, and we share our successes and our strategies along the way. Which is what we’re doing right now with Loop Marketing. I think that has led to a lot of companies saying, oh, this was really successful for HubSpot, I’m gonna adopt it as well, which is good. That’s what we wanted.
But I also think that when we started seeing declines from the emergence of AI Overviews and the changing nature of Google, that was a bit of a bellwether for what I think a lot of websites are now seeing. And so one response could have been, oh, we’re not gonna build in public anymore. We’re gonna be very cagey about what we’re doing and what’s working. So that doesn’t happen again. But that’s obviously not what we’re doing. We’re trying to be even more transparent and helpful. I really hope and believe that loop marketing, which is not a replacement of inbound, but meant to be, again, an extension of and, and a really helpful framework for companies can play that role.
Danny Goodwin: So just going back to that, that traffic drop. I was basically told it was about an 80% traffic drop and you kind of helped the company through that. And now in LLM world, HubSpot is the most cited CRM, is that correct?
Aja Frost: Or the most visible CRM
Danny Goodwin: Most visible. Okay. Gotcha. All right. And, and obviously this is, again, this is a fairly new technology. So, when you were starting to approach optimization on LLMs and AEO, how did you start that journey? Like, what were the first few things that you maybe either thought about or tried that did or did not work?
Aja Frost: Yeah. Well, the first thing I did that I would really recommend folks do if they don’t have an AEO function already stood up was I, um, pulled together some of the ICS on our team that were already doing a lot of experimentation and research in their own time. In my day-to-day, I am usually working with managers or directors. I’m not super close to the work. But I knew that I needed to be really close to this and really help guide it. And so I said, the three of us, we’re gonna meet once a day. We are going to launch one experiment per week if we can. I’m working with the dev team so that whatever we need to do, we can execute as quickly as possible. And so we took a very experimental mindset from the get go.
What we started out with was how do we scale good quality data-rich content? We had been thinking, and I think most people thought about content, maybe in a month you put out 30 pieces. If you’re a news publication, you could be putting out hundreds. But we’re thinking in multipliers of tens most teams. And I think we need to be thinking in multipliers of hundreds or thousands. And so with the team, I wanted to figure out how do we create that content? How do we start relatively small? So like batches of 10, generated with AI reviewed by a human, and then how do we scale that over time? That I think has been very successful.
We’re still experimenting with the types of content that get the most visibility in answer engines. And so that’s what a lot of experimentation revolves around. We also did a lot of what I think of as good clean AEO. Making sure that we were using all the available schema types across our website, making sure that things were really well structured and that we’re leading with the answer. And each section of the page is semantically complete and things are formatted in a Q and A format. You know, a lot of things that I think are now becoming like the standard AEO playbook.
Danny Goodwin: So you mentioned content types. I know there’s been a lot of noise about how some people are abusing top X lists – the top 10 best insert thing here. Is that the sort of stuff you’ve been playing around with? When you say content form, is there anything you can share about what you found that works maybe better?
Aja Frost: Yeah, so I’m not thinking so much about top X for Y, although I think that that still very much has a place in people’s content playbooks. But what we’re really experimenting with is – Danny, what’s the last thing you did research with ChatGPT to buy?
Danny Goodwin: Oh, to buy?
Aja Frost: Yeah.
Danny Goodwin: Uh, it’s, it’s probably researching to find a hotel for Christmas.
Aja Frost: Okay. Find a hotel for Christmas. So the context that ChapGPT is going to have when it recommends a hotel for you is probably about how much money you typically spend based on some demographic data it’s collected about you, if you’ve done any hotel research in the past, where you’re going, obviously how long you’re gonna stay. Hotels, we wanna provide the answers for all of those contextual clues. So if I were a hotel and I was trying to show up in answer engines, I would be creating content that spoke to your particular persona type and your particular use case. Now, I think the challenge is doing that without that content being duplicative or spammy. And to do that, this is what we spend a lot of time on. What are all the data sources that we can ingest to feed these systems essentially, so that all the content is unique, it’s grounded in what we know the persona needs, and it’s not repetitive from page to page.
Danny Goodwin: As, as you’ve gone through this process, were there any maybe big surprises like, oh my God, I didn’t think that would work. Or is there just like any kind of aha! moments, um, as you’ve been doing all this optimization for AI answers?
Aja Frost: The hardest part has been the measurement. I think that we are still very much as an industry, and I know this ’cause I talked to a lot of AEO vendors, figuring out how to correlate the actions that we are taking with specific visibility increases. And it’s highly dependent on the prompts you are tracking. I think that leaves the room for uncertainty and ambiguity because what if you’re tracking the wrong prompts? Or what if you’re tracking the right prompts, but not enough of them? It’s far less clear to say “I did X and Y happened” than it was with SEO. And even with SEO, you know, we couldn’t run A/B tests. We are always doing look backs. There’s so many variables at play.
I talked about education with execs around why visibility is the most important. I think the other really important piece of education, not just for executive leadership, but for, SEO/AEO teams is getting comfortable with less data and fewer direct lines between what we’re doing and the results. So that’s been, I don’t know if that’s been surprising ’cause I think I knew going in that that was going to be hard. But as we’ve progressed and we’ve done more and more teasing apart, the impact of individual experiments has gotten harder and harder.
Danny Goodwin: So I heard through on background of getting this interview set up that you sort of have a formula for getting ChatGPT to recommend a brand. So I want to hear all about that. What can you tell us about that?
Aja Frost: Well, I think that many of the best tactics that we are successfully using are ones that I’ve already mentioned. So we’ve spent a lot of time talking about hyper-specific persona-centric content. What we’ve talked about a little less is the off-site tactics that we’re using. And what we’ve done is identified ChatGPT and Google, because those are priority engines, we’ve identified their top training and citation sources. And then we have put together a concerted strategy to show up as positively and frequently as possible in those places. And two big areas for us have been YouTube and Reddit, which probably won’t surprise anyone as being very influential for answer engines. I can go a little bit more into some of the things we’ve done there, if that’s useful?
Danny Goodwin: Yeah, I think so. There’s been some research done around how heavily cited Reddit and YouTube and a few other sites are. So yeah, I’d be kinda curious to know, like from a strategic standpoint, maybe like how you guys are approaching Reddit and YouTube.
Aja Frost: Yeah. Very different strategies for each and one big learning for us, I wouldn’t say this is in the last year because we’ve been very active on both platforms for several years, but, um, treating every social media platform as its own beast and really getting to know the lay of the land and understanding the culture and the rules and the unspoken rules before we engage. I mean, that’s just a general best practice for any community or social media site.
But on YouTube, uh, we have a large slate of owned channels from Marketing Against the Grain and HubSpot Marketing, to how to HubSpot, science of scaling. It really runs the gamut. And we, the global growth or SEO AEO team works really closely with the teams creating those conthat content to weave in organic mentions of the products where they make sense and make sure that we are creating content on topics that we know answer engines and people care about. We also have a lot of creator partnerships with folks who speak to our relevant audience and somewhat similar playbook there. We want organic, relevant, contextual mentions of HubSpot.
Danny Goodwin: So that’s like influencer marketing, that sort of thing when you say creator?
Aja Frost: Yeah. I think you could call it influencer marketing. I mean, we, we sign, um, multi-month sometimes one-year contracts with creators and, and say, you know, we will pay you X, Y, Z and, in exchange you will create content on these wide topics. Well, we give them a lot of editorial freedom, but you know. You’ll mention HubSpot in X videos, that sort of thing.
And then on Reddit, it is a much more advocacy and community-centric approach. And I should have shouted out HubSpot Media on the YouTube front. They are a fantastic partner to my team. On the Reddit front, we work really closely with HubSpot community, another internal team. And in the last year we became the co-moderator of HubSpot’s subreddit. And we have spent most of our time making that subreddit as productive and engaging as possible because what we’ve seen, which is really interesting, is that the more activity that happens in our HubSpot, the more positive mentions of HubSpot there are across Reddit. Because basically you’re creating a team of advocates who are really excited about your brand, your product, and then they organically go out into conversations on our sales, our marketing, our CRM, and they say good things about HubSpot. So, very, very different strategies, but both focused on getting the right people to say nice things about HubSpot.
Danny Goodwin: I think we touched on this a little bit earlier. Google search versus traffic you get from AI engines, it’s very different. It’s not as large. We’ve actually reported, in the last couple months, three different stories basically saying that traffic that you get from LLMs is either worse or about on par with Google search in terms of converting. I’m curious what you’ve seen there. Do you see that to be the case or do you see quality traffic coming through?
Aja Frost: Yeah, the traffic that directly comes from LLMs converts at about three times better than traditional search for us. So we’re definitely seeing higher conversion rates. And I, I’ve read the SEL stories. I was looking at the one you most recently published, which was like 900 e-comm website over the course of a year. I shared that with my team last week. I was curious whether the difference in conversion rates had anything to do with the difference in the type of product and the buying journey. Like, I think by the time someone is coming to hubspot.com from an LLM, they’ve done a lot of research, at least that’s what our analysis suggests. And so they’re much readier to convert than someone who might in the old world have been coming to the blog to download an ebook on content marketing. It’s been another really fascinating area to watch the industry debate because I’ve also seen several different, uh, different stats.
Danny Goodwin: Right. Yeah. Again, it’s very early and these are not large scale studies, it’s just sort of anecdotal I guess we would say. But any data, I think is useful ’cause at least it gets people thinking about all of these things and it’s gonna always go back to, it depends. It may be different for ecomm versus B2B or whatever the case may be. I think there’s still a lot that’s going to change and where AI is now. I even today was seeing somebody saying we’re at peak AI already. Like really? Like it’s, it’s two years old. Like, come on.
Aja Frost: Yeah. I would disagree with that. Yeah. I think there are, to your point, some things that could be step function increases in conversion rates. Obviously instant checkout, that’s huge. I think that, yeah, I mean this was obviously over the course of a year and I do remember seeing in the study that conversion rates had increased over time, maybe as people got more comfortable or familiar with ChatGPT. But instant checkout’s huge. I don’t know what adoption for Atlas is going to be or for any of these ad browsers to be fair. But agent mode or agentic checkout would definitely improve conversion rates. So I think we’re at the very early innings of this.
Danny Goodwin: Where do you think AEO as a practice will be at maybe a year from now? Do you think it’ll be kind of its own thing? Do you think it’ll be part of SEO and is there anything that you were maybe kinda excited to see happen from ChatGPT or some of these other engines that could make these systems even better?
Aja Frost: I think a lot hinges on when Google makes AI Mode more of the primary search experience. I don’t believe that you are going to get an AI-powered answer for every search. My belief is for navigational queries, at the very least, you’re probably always gonna have something that feels like the traditional SERP and that it gets you from point A to point B very quickly. But I think for a lot, if not most other searches, you will probably be in some form of AI Mode and at that point, SEO and AEO become merged because there is no real traditional SERP to optimize for anymore.
Danny Goodwin: Yep. Exactly. That’s sort of been my problem with this whole naming debate. If you’re gonna call it AI SEO, what happens if that search engine goes away? There’s no more, there’s no more SE in SEO.
Aja Frost: Totally. Yeah. But yeah, and also that doesn’t exactly roll off the tongue. Like I don’t wanna stand up and and say I am an AI SEO.
Danny Goodwin: Right. Exactly. So if you could maybe give people one AEO type of experiment you think maybe they could run before the end of the year to kinda get a feel for it or just anything that you think might be helpful for them to kinda experiment with. Is there anything maybe you could suggest to people like, try this tactic or this strategy or whatever?
Aja Frost: I think if you want a real project, then I would try creating those hyper-specific, very persona-focused pages. I think if you’re looking for something that you could run with and get live by the end of the week, use one of the many query fan-out tools that are available online. Take a page that already exists on your website, plug like a, a likely reasonable query that would lead someone to that page into a query fan-out pool, and then assess whether your page answers or has content for all of the subqueries that that pool provides. And if it doesn’t add them and then see does your visibility for that head question increase.
Danny Goodwin: Awesome. Any final thoughts? Anything we didn’t talk about that you’d love to comment on or leave people with some parting words of wisdom?
Aja Frost: Yeah, I would, I would be remiss not to direct people to hubspot.com/loopmarketing. We have spent a lot of time on AEO. Of course, AEO is one of the tactics in this new growth framework for the AI era, but there’s a lot more that we believe businesses can and should be doing to not just survive but thrive. Check it out. I think there’s a lot there.
Danny Goodwin: Awesome. And just, just for anyone who’s listening and doesn’t know what is loop marketing like, can you give us just a quick overview of what that is? ’cause you mentioned a couple times.
Aja Frost: Yeah. Loop marketing is a growth framework for businesses. There are four phases: express, tailor, amplify, and evolve. Each of those four phases has a host of plays and tactics. But the general idea is that, as the web changes, as folks go from progressing through this ever narrowing funnel to getting an answer in an LLM, then going to your Instagram, then reading a review and, and really having like a much more messy, much less linear journey, we need a new framework for marketing. And so this framework is an ever-evolving, much more flexible dynamic framework.
Danny Goodwin: Right. So it’s sort of like that old bendy straw, the messy middle as Google put it, I think. Right?
Aja Frost: Yes. Yes. I will say messy middle came up many times in our conversations around the loop.
Danny Goodwin: Yeah. Awesome. Alright, well that is all the time I have for you for today. It was a great conversation. I really appreciate you taking the time to chat with us. Look forward to seeing more from you in the future and wishing you nothing but success heading forward.
Aja Frost: Thanks so much, Danny. This was really fun.
Danny Goodwin: All right. Thanks. Aja. Bye everybody.
https://i0.wp.com/dubadosolutions.com/wp-content/uploads/2025/11/twp4ozh58oy-PQnfoh.jpg?fit=1280%2C720&ssl=17201280http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-11-04 17:22:402025-11-04 17:22:40Aja Frost on AI search, content strategy, and AEO success metrics
AI search isn’t killing SEO. It’s forcing it to evolve into a new, multi-platform discipline called search everywhere optimization, where social and user-generated content (UGC) are the new trust engines driving discoverability.
When I presented this concept at brightonSEO San Diego, what stood out wasn’t just the excitement around AI.
What stood out was the unexpected convergence of ideas across sessions. You might expect every talk to center on AI, yet a broader shift was quietly taking shape.
Across these discussions, one message echoed clearly: social and UGC now shape which brands audiences trust and engage with.
Below are four recurring themes from those talks, along with post-event insights from each speaker on how marketers can apply a search everywhere mindset.
1. Search is not a platform, it’s a behavior
Search no longer lives in one box – and users aren’t just Googling anymore. They’re discovering through:
Conversations.
Communities.
Creators.
While AI platforms are becoming part of that journey, much of it still happens where authentic discussions thrive: Reddit, TikTok, YouTube, LinkedIn, and Instagram, to name a few.
Search has never been more multi-platform, multi-touch, or multi-intent.
Marketers must now adapt to fragmented journeys that may start socially, evolve through AI, and end in branded discovery.
Garg, founder and CEO of Writesonic, said it well when he recently shared with me:
“Your website is no longer your main asset – your presence across the entire web is. Brands optimizing only for Google are missing 40% of their audience who’ve already moved to ‘search everywhere.’”
My presentation defined this concept as search everywhere optimization, emphasizing that success depends on SEO, social, PR, and brand teams working together to drive unified discoverability.
Other speakers echoed these points, even if they used different language.
Liddell defines this similarly as “search everywhere” – where social, brand, and search operate together to drive discoverability.
Hudgens said, “Social is evolving to become the new open web,” citing data showing traffic and engagement growth from social ecosystems.
Blyskal quantified the behavior: AI platforms cite Reddit and YouTube way more than any traditional websites. More proof that discovery has evolved beyond Google’s SERP.
In speaking with Blyskal, head of AI strategy and research at Profound, he noted:
“Search everywhere isn’t a trend anymore, it’s reality. Our data shows that consumers are asking ChatGPT, Claude, and Perplexity the same questions they used to ask Google, but the answers are being built from fundamentally different sources. UGC platforms like Reddit now drive more influence in AI recommendations than most corporate websites because they represent unfiltered human experience at scale.”
2. UGC and social content drive modern discovery
User-generated content and social discourse have become the connective tissue of search.
From product reviews to LinkedIn posts to Reddit threads, these conversations shape what AI and many humans believe to be authoritative.
Social platforms are now the front door to search intent, sparking curiosity and building interest that eventually leads users to branded and organic experiences.
Blyskal’s analysis of 40 million AI search results found Reddit to be the single most-cited domain across ChatGPT, Copilot, and Perplexity.
While some shifts have occurred recently, he confirmed on Oct. 21 that “Reddit is still the most cited website overall in AI and is still second in ChatGPT.”
Garg echoed this finding, noting that Reddit and other community-driven content dominate citations across industries – a clear signal for marketers to engage where real conversations happen.
Liddell’s award-winning BullyBillows case study demonstrated how social-first content can drive measurable SEO impact, including:
A 65% rise in brand searches.
A 195% increase in “brand + keyword” searches.
A 139% lift in revenue.
Reynolds likewise emphasized the value of social resonance, recommending that marketers invest in content that performs well on social platforms, even if it underperforms in organic search.
Seer Interactive’s own data backs this up: while social generates 89% less traffic than search, it produces 20% more leads.
Together, this data proves that social and UGC are not just amplification channels. They’re search inputs themselves, and a core component of search everywhere optimization.
In a follow-up conversation, Hudgens – founder and CEO of Siege Media – remarked:
“Search traffic to LinkedIn pages is up significantly, and I expect it to continue to grow, eventually coming close to Reddit and Quora in impact on B2B. Brands need to be considering how they show up and contribute on LinkedIn in order to best impact all search surfaces.”
Many are seeing this firsthand in their analytics – clicks are declining even when rankings remain steady.
The real goal now is preference: being chosen, not just seen.
Both humans and AI systems increasingly value authenticity and consensus over keyword precision and link quantity.
Today, search visibility depends as much on how others describe your brand as on the content you create yourself.
Liddell frames this shift through the lens of preference = authority + trust + relevance.
Reynolds highlights the rise of community platforms – LinkedIn, Reddit, Slack, and WhatsApp – urging SEOs to focus on spaces where people share content with personal endorsement, offering more genuine reach than traditional formats that dominate the SERP.
Hudgens describes the 2021–2026 content marketing evolution from “high DR (domain rating) links” to “high influence mentions,” signaling that social proof and reputation now act as the modern PageRank.
Garg quantifies it: AI now weighs third-party mentions three times higher than a brand’s own website.
In short, as search engines are learning to mirror people, they trust signals, not tactics. This is the preference component of search everywhere optimization.
Liddell, co-founder and Search Everywhere director at Deviation, summarized it nicely to me, sharing:
“Brands can’t win on rankings alone anymore; they win on trust. Modern discovery happens where people talk, not where algorithms dictate – and that means investing in authentic UGC and social visibility is as critical to search as backlinks once were.”
4. Search everywhere success starts with breaking down silos
In 2025, silos remain one of the biggest obstacles to growth.
Many of our clients experience this firsthand – and other industry experts agree that maximizing discoverability now depends on cross-functional collaboration.
Search teams can no longer operate in isolation. PR, brand, and social teams all feed the trust loop that AI, search engines, and users rely on.
Future success will depend on these groups meeting regularly, sharing ideas, and aligning on shared goals.
My presentation emphasized building cross-channel roadmaps with social, content, PR, and paid to ensure each team’s efforts reinforce each other.
Hudgens showed that the future of content marketing lies in blending PR, organic social, thought leadership, and SEO – creating compounding impact instead of treating them as separate channels.
Reynolds underscored the need for shared metrics, measuring impact not in rankings but in trust, reach, and conversion.
The new search equation runs on trust
While the speakers offered diverse perspectives, they all agreed on one central truth: search success is shifting from gaming algorithms to authentically earning audience trust.
Reddit posts, offsite reviews, social media, and third-party references now serve as critical trust signals – not because they link, but because they validate and build confidence in a brand.
This shift – evident across all four takeaways, from breaking down silos to valuing preference over ranking – underscores a broader reality: search isn’t something people do anymore.
It’s something they experience, everywhere.
The brands that will thrive in this new era won’t be those with the most backlinks or the sharpest keyword strategy, but those whose audiences genuinely connect with and vouch for them.
Over the past year, Google Ads has increasingly embraced automation, shifting the account manager’s role in both practice and strategy.
The granular control and transparency we once took for granted are rapidly disappearing.
As 2026 approaches, it’s time to face reality – five PPC tactics are falling out of favor in the new era of automation.
1. Relying on phrase match keywords
Once the go-to option for advertisers who weren’t ready for a broad match strategy but wanted to expand search volume, phrase match has recently fallen out of favor.
Google continues to redefine how match types work.
Because Smart Bidding and broad match rely on multiple intent signals, these signals now match user intent more accurately than phrase match did under the same strategy.
When targeting a specific query, exact match tends to provide stronger control, while phrase match often returns ads for irrelevant searches.
As a result, phrase match has become both too limited to scale an account and not precise enough to maintain the level of control advertisers need in a keyword match type.
2. Skipping standard shopping campaigns
Although Performance Max has been Google’s main focus for some time, advertisers continue to see strong results from testing standard shopping campaigns.
This became even more apparent after the ad rank update at the end of 2024, which removed Performance Max’s built-in priority over standard shopping.
Since then, standard shopping campaigns have outperformed Performance Max in many cases.
Standard shopping also provides greater channel control and a clearer attribution path, as conversions typically come from direct clicks within the Google Shopping network.
While Performance Max now offers campaign-level search terms, standard shopping has long provided both that data and impression share insights at the product-group level – valuable for benchmarking and understanding competitive performance.
If you’re concerned about brand safety, standard shopping is the safer choice. It helps keep your ads off irrelevant or inappropriate placements across the Display Network or YouTube.
3. Making GA4 your primary conversion action
Remember the days of Universal Analytics, when Google would always advise advertisers to use UA conversion tracking as the primary metric?
It seems the guidance has gone back and forth ever since.
Ideally, your main conversion metric in Google Ads should align with account conversions to deliver real-time data signals for Smart Bidding.
GA4’s tracking pixel doesn’t provide that freshness – imported GA4 events are delayed in processing.
Additionally, GA4 attributes conversions to the date the conversion occurred, whereas the native Google Ads tag attributes them to the date of the ad click.
Third-party tools such as Elevar or Analyzify often provide the most reliable setup for accurate conversion tracking.
If a third-party solution isn’t feasible, Google increasingly recommends the Google and YouTube app as an alternative.
It’s relatively easy to configure, but avoid syncing products or shipping settings during setup to prevent duplicate products or overwritten shipping details in Merchant Center.
GA4 should still be linked for audience building and secondary reporting, but it’s best not to use it as the primary conversion metric.
It simply doesn’t deliver the real-time data accuracy needed for optimal Smart Bidding performance.
Performance Max campaigns tend to favor branded queries, so it’s important to segment branded terms rather than allowing them to run within broader campaigns.
This matters most when aiming for incremental traffic growth, not just conversions you would have earned from branded searches anyway.
Performance Max prioritizes easy wins, bidding heavily on branded terms and often inflating campaign-level ROAS, making results appear stronger than they actually are.
Separating branded traffic into a dedicated brand search campaign provides more control over both budget allocation and bid strategy for those terms.
However, there are factors to consider before excluding branded terms from existing Performance Max campaigns.
Doing so can affect performance, and the right approach isn’t one-size-fits-all.
Review:
The campaign’s age.
History.
Contribution to overall performance.
The share of brand traffic it drives.
In large accounts, for instance, if a single PMax campaign is responsible for most conversions and spend, it may be unwise to exclude branded terms immediately.
Likewise, in accounts with limited budgets, keeping branded terms within the same campaign may still make sense.
5. Over-pinning responsive search ads
The pinning debate has been around for a while, but more advertisers are now leaning toward fewer responsive search ad (RSA) assets instead of over-pinning existing ones.
This helps maintain control over messaging while still giving Google enough flexibility to test which headline and description combinations perform best – without overwhelming the system with endless variations.
And yes, the question always comes up, “What about my ad strength?”
Realistically, ad strength should be treated as a guide for creative quality, not a direct measure of performance.
While it can highlight issues such as limited variety or missing keywords, it does not directly impact ad rank or quality score.
Ad strength is a diagnostic tool, not a KPI.
Chasing an “excellent” score by stuffing headlines and descriptions can easily result in weaker performance for the sake of a vanity metric.
Don’t fight the machine – feed it
As 2026 approaches, the most successful account managers will be those who adapt to the new landscape.
The goal isn’t to fight automation but to feed it the right data.
Focus on high-value inputs and let automation do the heavy lifting – the most profitable PPC practices are the ones that save time, not consume it.
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