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.
Read more at Read More
When you think of SEO, your brain probably jumps to Google. But there’s another major search engine people often overlook, YouTube.
With over 2.7 billion monthly users and more than 500 hours of content uploaded every minute, YouTube is the second-largest search engine in the world, and video is one of the most popular content delivery methods online.
And here’s the kicker. YouTube videos don’t just show up on YouTube. They rank in Google results, too. So if you’re not optimizing your videos, you’re leaving a ton of organic reach on the table.
That’s where YouTube SEO comes in.
Just like you optimize blog posts to rank on Google, you need to optimize your videos to rank on YouTube. Different platforms, different rules, but the same goal: get discovered.
This guide breaks down exactly how to do that, with updated strategies, data-backed tips, and easy wins you can apply to your next upload.
YouTube SEO means optimizing your videos and channel so they appear in YouTube search results, and often in Google search results as well.
So how does YouTube decide what to rank? It’s not just about keywords. The YouTube algorithm looks at how users interact with your content.
YouTube wants to feature videos that people watch all the way through, engage with, and find relevant. That includes:
It also weighs other elements like thumbnail design, captions, and even your video file name.
If your video gets clicks but users bounce after 10 seconds, that’s a red flag. But if they watch to the end and hit subscribe? That’s a signal your video is delivering real value.
The goal isn’t to outsmart the system, it’s to help YouTube understand why your content deserves visibility. When your video SEO aligns with the ranking factors that matter, you improve your chances of being discovered.
Traditional SEO and YouTube SEO share a few principles, but they’re built for different behaviors.
Here’s how they differ:
Traditional SEO (search engines):
Video SEO (YouTube):
YouTube rewards content that performs, not just content that’s well-optimized. Another note is that as of right now, YouTube competition is lower than conventional blogs just because there’s so much more blog content out there.
YouTube SEO helps your brand get found across more than just YouTube.
Google’s shift toward Search Everywhere means results now pull from all kinds of content, web pages, videos, images, and forums. YouTube isn’t just along for the ride. It’s a key input.
YouTube content can surface in a range of Google SERP features, from AI Overviews to video carousels and rich results.. It also improves your odds of showing up in AI-powered summaries, where large language models (LLMs) highlight sources that are relevant, clear, and trustworthy. This is Search Everywhere Optimization in action, and YouTube is a key cornerstone of this strategy.
When your brand shows up consistently on YouTube, you build credibility. That reinforces everything else you’re doing, blog content, backlinks, schema markup, and on-page SEO.
Video isn’t just part of your content strategy. It strengthens your presence in search.
Next, we’ll break down what you can do to improve your YouTube SEO and get your videos in front of the right audience.
You don’t need to guess what works, there are proven YouTube SEO tips that make your videos more discoverable.
From how you title your videos to how you hold attention, small changes can lead to more views, more engagement, and better rankings. Let’s break them down.
Strong YouTube SEO starts with the right keywords, and your research process needs to match how people actually search on the platform.
YouTube queries tend to be intent-driven: tutorials, reviews, comparisons, and questions. That means your keyword list should include real phrases your audience types into the YouTube search bar.
Start with YouTube’s autocomplete. Type a broad topic into the search bar and look at the suggested queries. These are gold, purely based on actual user behavior.
Next, check out high-performing competitor videos. What phrases show up in their titles, descriptions, and tags?
You can also use tools like Ubersuggest, vidIQ, or TubeBuddy to explore search volume, competition, and related keyword ideas. Ubersuggest doesn’t go as deep on YouTube-specific data as others, but it’s a good starting point to find popular keywords to build videos around.
Once you’ve built a list, prioritize keywords with clear intent and moderate competition. If people are searching for it and your video delivers, it’s a win for rankings and engagement.
Make keyword research a habit. The better you understand how your audience searches, the easier it is to create videos that get found.
Your video title is one of the most important signals YouTube uses to understand your content and it’s also what drives clicks.
A good title does three things: matches the search query, promises value, and grabs attention without feeling clickbaity.
Use your primary keyword early in the title. Then add a hook that creates curiosity or outcome-driven interest.
Outdated: “Small Business Marketing Tips to Grow Your Revenue”
Stronger: “Small Business Marketing: 7 Tactics That Actually Drive Revenue in 2026”
This updated version is more specific, adds a number, includes a timeliness cue, and still leads with the core keyword.
The examples below show these principles in action, giving you clear examples of what you will get in the video.
YouTube tags still help clarify what your video is about, but they’re no longer a major ranking factor.
Use tags that are closely aligned with your video title, topic, and primary keyword.
You don’t need dozens. Stick to a few highly relevant tags.
Instead of thinking in terms of “LSI keywords,” focus on real search terms your audience might use.
For example, a video about growing succulents indoors might include tags like: succulent care, indoor gardening, how to grow succulents, succulent tips.
Your YouTube description helps both viewers and YouTube’s algorithm understand what your video is about.
Start with a clear, one-sentence summary of your video that includes your target keyword early on.
After that, use the remaining space to give context, outline what viewers will learn, and link to any relevant resources.
Avoid keyword stuffing. Instead, use related terms naturally throughout your copy.
If your video covers multiple steps or topics, consider adding timestamps.
You should also include a few branded or evergreen links at the bottom—think blog posts, landing pages, or your email signup.
A strong description can boost your ranking, increase watch time, and drive more clicks from both YouTube and Google.
Looking at what top competitors are doing on YouTube is one of the fastest ways to improve your own SEO strategy.
Search for videos ranking for terms you want to target, then study their titles, thumbnails, tags, and video descriptions.
Look for patterns in phrasing, topic angles, or keywords they repeat across multiple uploads.
You can also use tools like TubeBuddy or vidIQ to explore the tags used and how often certain phrases show up in popular videos.
The goal isn’t to copy what works, but understand what’s already resonating with your shared audience.
From there, refine your keyword strategy to stand out while still aligning with search demand.
Well-organized YouTube playlists help you group related videos together in a way that increases watch time, session duration, and topical relevance.
From an SEO perspective, playlists are crawlable by YouTube and Google, especially if you include keywords in the title and description.
Use playlists to guide viewers through multi-part tutorials, related topics, or evergreen series. The goal is to keep people watching without needing to click away. Take a look at this e-commerce playlist and how it helps viewers walk through different aspects of the topic.
Just avoid overstuffing. A focused playlist with a logical flow will perform better than a catch-all bucket.
Done right, playlists act like internal linking for your channel by connecting videos around topics that matter to your audience and to the algorithm.
Cards and end screens are built-in tools that keep viewers engaged and watching more of your content.
Cards are clickable links that appear during a video—use them to recommend related videos, playlists, or even external links if you’re eligible.
End screens appear in the final 5–20 seconds of your video and let you promote additional content, encourage subscriptions, or push viewers to a playlist.
These features help increase session time and send positive engagement signals to YouTube’s algorithm.
Make sure your end screens point to videos with similar topics or formats. That increases the chance viewers will keep watching.
You can add cards and end screens inside YouTube Studio under the “Editor” tab for each video.
Engagement signals tell YouTube your content is worth promoting, and they go beyond just comments and subscriptions.
Ask viewers to leave a comment by posing a simple, relevant question in your video.
Encourage likes, subscriptions, playlist saves, and shares. You can also ask viewers to vote in a Community tab poll or engage with a follow-up Short.
Use tools like pinned comments, end screens, and YouTube’s subscribe buttons to drive those actions.
The key is to be specific. Instead of “Leave a comment,” try “What’s the biggest SEO mistake you’ve made? Let me know below.”
Stronger engagement not only improves discoverability, it keeps people connected to your brand.
Production value doesn’t have to mean studio-level gear, but it does make a difference.
Clear audio, clean visuals, and simple edits help your content feel more professional and trustworthy.
Your background doesn’t have to be fancy, but it should be free of distractions. Use lighting that keeps you visible and present.
Strong delivery matters, too. Speak clearly, stay on-topic, and bring energy. YouTube tracks engagement, and your performance affects watch time.
Think of production as a multiplier. If your title, thumbnail, and keywords get the click, good production keeps the view.
YouTube doesn’t use thumbnails as a direct ranking factor, but they can strongly influence your click-through rate. That impacts how often your video gets recommended.
A clear, well-designed thumbnail helps your video stand out and gives viewers a reason to click.
Use large, readable text (four to five words max), strong contrast, and a visual that supports your title.
Avoid cluttered screenshots, generic imagery, or designs that mislead viewers.
For example, a thumbnail with the phrase “SEO Checklist” next to a presenter and recognizable brand colors is both clear and scroll-stopping.
Think of your thumbnail as a visual hook that earns attention and builds trust.
Closed captions and transcripts both support accessibility, and they help with SEO, too.
Captions allow your video content to be indexed more accurately by YouTube and Google. Transcripts can be added to your description or linked in the comments to provide even more context.
YouTube’s automatic captions are a helpful start, but they’re sometimes inaccurate. Always edit them or upload your own.
Accurate captions support viewers who are deaf or hard of hearing, improve clarity for non-native speakers, and make your videos easier to follow in sound-off environments.
This is one of those tricks that may or may not dramatically impact your SEO, but it’s nevertheless important to do.
The idea is to rename your raw file so that it reflects your title or your focus keyword.
So for example, your file may default to a name like “VID_230912.mp4.”
But if you rename it and use your focus keyword (e.g., “youtube_keyword_research_tips.mp4”), you’ll tell YouTube what your video is about.
Social shares drive clicks and help build links to your channel and videos, which improves your long-term YouTube SEO.
When your video is embedded or linked on high-traffic platforms, you’re reinforcing its authority. That helps YouTube understand it deserves broader distribution.
Facebook: Pair your video with a short, benefit-driven post. Native uploads still get good reach, but YouTube links with the right framing still perform.
Twitter/X: Share with a one-liner hook, a stat, or a contrarian take. Quote-tweet your own video to build thread engagement.
LinkedIn: Great for expert tips, B2B, or tutorial content. Use a headline-style intro and keep it professional but personal.
Reddit: Find subreddits where your content solves a problem or answers a recurring question. Don’t spam, be useful.
TikTok: Post a short preview or teaser clip from your full YouTube video. Add a CTA like “Full video on YouTube—link in bio.”
Strategic social sharing expands your reach and builds the signals YouTube looks for when recommending content.
Your email list is a direct line to viewers who already trust your content—use it to boost early video views and engagement.
When you publish a new video, send a short email that tees up the topic, builds curiosity, and includes a direct link.
Example:
“Just dropped: My 5-part YouTube SEO checklist. These are the exact tactics I use to rank. Watch it here.”
Avoid overloading your email with text or embedding full videos. Keep it simple, scannable, and focused on the value of the video itself.
Early views and clicks from your email list help signal relevance to YouTube’s algorithm and can give your video a faster lift.
Embedding your YouTube videos into your site helps with both visibility and watch time, two things that matter for SEO.
The best place to embed is inside blog posts that already get traffic, especially content that aligns with the topic of your video.
For example, I embedded a video about Customer Lifetime Value (CLV) in a blog on Customer Acquisition Cost (CAC).
Avoid placing the video at the very end of the post. Higher placement improves play rate and session time.
You can also embed videos on landing pages, FAQ pages, or resource libraries to drive discovery.
Every additional view helps build authority for your channel, and the contextual match between the page and video strengthens relevance.
Watch time, the total minutes viewers spend watching your content, is one of the most important signals YouTube uses to rank videos.
The longer someone watches, the more YouTube sees your video as valuable. That leads to higher visibility across search and suggested content.
To improve watch time, you need to know where viewers are dropping off. Start by checking the Watch Time and Audience Retention reports in YouTube Studio.
Go to Analytics > Content to see average view duration, key drop-off points, and which videos are keeping people engaged.
Then head to Analytics > Audience to view Returning Viewers data. This shows how many people come back to your channel and which videos they rewatch.
Use this data to spot patterns: Which intros keep people watching? Do tutorials hold attention better than explainers? Are certain upload times leading to stronger engagement?
You can also play your video inside YouTube Studio to watch second-by-second retention data and see exactly when people leave.
Over time, optimizing your content based on this data will boost watch time, keep people on your channel longer, and help you rank higher.
YouTube’s engagement reports give you critical insights into how viewers interact with your content and where you can improve.
In YouTube Studio, go to Analytics > Engagement to track key metrics like Average Percentage Viewed and Top Videos by End Screen.
Use Average Percentage Viewed to spot weak retention. If people drop off early, your hook or pacing might need work.
End Screen and Card CTRs show how well you’re keeping people in your content ecosystem.
You can also monitor Subscriber changes by video to see what content drives the most loyalty.
These reports won’t boost SEO on their own, but they show you exactly what’s working, so you can double down on content that keeps people watching.
The first 15 seconds of your video are critical, most drop-off happens right at the start.
To hold attention, you need a strong hook that quickly communicates what the video is about and why it matters.
You can open with a surprising stat, a pointed question, or a bold statement that previews the outcome.
Keep your energy high, use tight editing, and avoid long intros or branding sequences.
For example: “Most creators lose half their audience in the first 30 seconds. Here’s how to stop that.”
The goal is to immediately frame value, build curiosity, and give viewers a reason to stay.
If they bounce early, it sends negative signals to YouTube and hurts your chances of ranking.
Getting featured on another YouTube channel is one of the most effective ways to grow your audience and strengthen your SEO presence.
When another channel links to yours in the description or recommends your video, it sends referral traffic and authority signals YouTube notices.
Partnerships work best when the content is complementary, not directly competitive. A design channel could collaborate with a branding expert. A tech channel might feature a startup founder with a product demo. I regularly appear on other channels to talk about marketing and entrepreneurship.
Interviews, guest appearances, channel takeovers, or content swaps are all viable formats. The key is to provide clear value to their audience.
When reaching out, pitch a topic or format that fits their content style. Make it easy for them to say yes by sharing links to your best-performing videos and suggesting a clear angle.
Be sure to ask for a link in the description and even suggest end screen placement or pinned comment visibility if appropriate.
Collaborations not only expand your reach. They build link equity, keep viewers moving between videos, and strengthen your channel’s position in YouTube’s recommendation engine.
There’s no universal “perfect length” for a YouTube video, but top-performing content often falls in the 10–12 minute range.
But that doesn’t mean every video should hit that mark.
TED Talks, for example, often run 15 minutes or higher, and viewers expect that kind of depth. Cut them shorter, and they’d feel incomplete.
Instead of aiming for a specific number, focus on how long it takes to fully deliver the value your title promises.
Track your average view duration and retention in YouTube Studio to spot trends. If people drop off early, try tightening your delivery. If they’re watching to the end, test slightly longer formats.
Your “ideal length” is whatever keeps people watching and coming back.
YouTube Shorts are a major discovery tool inside the platform.
They show up in their own feed, dominate the mobile experience, and often reach viewers who haven’t seen your main content yet.
One smart move is to repurpose key moments from your longer videos into Shorts. Take a tip, stat, or highlight and format it vertically with captions.
This expands your reach and helps new viewers discover your channel.
Use your video description or a pinned comment to link to the full video or playlist.
If you’re skipping Shorts, you’re likely missing out on an audience that prefers quick, mobile-first content.
YouTube SEO is how you optimize your videos and channel to rank in YouTube searches.. It involves things like keywords, video structure, thumbnails, and watch time, all to help your content get discovered and watched longer.
Start by finding the right keywords, then use them in your title, description, and video file name. Create a strong hook, add closed captions, use end screens and playlists, and encourage engagement. The more signals you send that viewers enjoy your content, the better your SEO.
TubeBuddy and vidIQ are two of the best. They help with keyword research, tag suggestions, and competitive insights. Ubersuggest can also help if you want to look for broader SEO and content trends to guide your video strategy.
Yes. When embedded in blog posts or linked across the web, YouTube videos can improve time on page, add relevance to your content, and build backlinks to your channel. That’s good for your site SEO and your video rankings.
YouTube isn’t just for uber-famous superstars, you can get in on the action, too.
If you work hard to make videos that really help people, you’ll watch the views roll in.
Then you can send that traffic to your website, or you can ask people to subscribe to your list for more content.
You don’t need a huge budget to start making great videos. You can produce a viral video using just the phone in your pocket and a free video editor.
The best channels stand out because they have something unique to offer.
If you have a unique value proposition of your own, and if you go the extra mile to create videos people love, you can become very successful on YouTube.
Read more at Read More
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.
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.
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:
Houy wrote:
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.
What they’re saying. Many SEO practitioners applauded the candor, via comments on Houy’s LinkedIn post. Some of the reactions:
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.
Read more at Read More
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.
Read more at Read More
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:
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.
Read more at Read More
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.
Five standout voices – Wil Reynolds, Josh Blyskal, Samanyou Garg, Ross Hudgens, and Ashley Liddell – all surfaced similar insights about where search is headed.
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.
Search no longer lives in one box – and users aren’t just Googling anymore. They’re discovering through:
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:
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.
In speaking with Blyskal, head of AI strategy and research at Profound, he noted:
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:
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:
Visibility alone no longer wins.
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.
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:
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.
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.
Read more at Read More
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.
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.
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.
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:
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.
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.
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.
Read more at Read More
There’s been a lot of buzz around llms.txt.
But no major AI platform has confirmed that they use it.
Not yet, anyway.
And there’s no evidence that any major large language model (LLM) actually uses it when crawling.
So, why are some SEOs and site owners already adding it to their sites?
Because LLM traffic is projected to explode over the next few years.
Which means AI models could soon become your biggest traffic source.
Remember: robots.txt was once optional, too.
Today, it’s essential for managing search crawlers.
LLMs.txt could follow a similar path — becoming the standard way to guide AI to your most important content.
In this guide, you’ll learn how llms.txt files work, the key pros and cons, and the exact steps to create one for your site.
You’ll also see different llms.txt examples from real sites.
First up: a quick explainer.
LLMs.txt is a plain-text file that tells AI models which pages to prioritize when crawling your site.
This proposed standard could make your content easier for AI systems to find, process, and cite.
Here’s how it works:
For example, here’s what Yoast SEO’s llms.txt file looks like:
Short answer: No.
They serve different purposes.
Robots.txt tells crawlers what they’re allowed to access on a site.
It uses directives like “Allow” and “Disallow” to control crawling behavior.
LLMs.txt suggests which pages AI models should prioritize.
It doesn’t control access — it just provides a curated list. And makes it easier for crawlers to understand your content.
For example, you might use robots.txt to block crawlers from your admin dashboard and checkout pages.
Then, use llms.txt to point AI systems toward your help docs, product pages, and pricing guide.
Here’s a full breakdown of the differences:
| LLMs.txt | Robots.txt | |
|---|---|---|
| Purpose | Provides a curated list of key pages that AI models may use for information and sources | Sets rules for search engine crawlers on what to crawl and index |
| Target audience | LLMs like ChatGPT, Gemini, Claude, Perplexity | Traditional search engine bots (Googlebot, Bingbot, etc.) |
| Syntax | Markdown-based; human-readable | Plain text, specific directives |
| Enforcement | Proposed standard; adherence is not confirmed by major LLMs | Voluntary; considered standard practice and respected by major search engines |
| SEO/AI impact | May influence AI-generated summaries, citations, and content creation | Directly impacts search engine indexing and organic search rankings |
So, what goes inside this file — and how should you structure it?
LLMs.txt should be created as a plain-text file and formatted with markdown.
Markdown uses simple symbols to structure content.
This includes:
This makes the file easy for both humans and AI tools to read.
You can see the main elements in this llms.txt example:
# Title
> Description goes here (optional)
Additional details go here (optional)
## Section
- [Link title](https://link_url): Optional details
## Optional
- [Link title](https://link_url)Now that you know how to format the file, let’s break down each part:
To put all the pieces together, let’s look at some examples.
Here’s how BX3 Interactive, a website development company, structures its llms.txt file:
It features:
BX3 Interactive also includes target terms and specific CTAs for each URL.
If adopted, this approach could shape how LLMs reference the brand, guiding them toward BX3 Interactive’s preferred messaging and phrasing.
LLMs.txt files can also be more complex, depending on the site.
Like this example from the open-source platform Hugging Face:
It organizes hundreds of pages with nested headings to create a clear hierarchy.
But it goes well beyond URL lists and summaries.
It includes:
This way, AI systems would get direct access to Hugging Face’s most valuable documentation without needing to crawl every page.
This could reduce the risk of key details getting missed or buried.
Keep in mind that the ideal structure depends on the scope of your site. And the depth of information you want AI to understand.
Further reading: Vibe Marketing: Hype, Reality, and Real Case Studies
The jury is out.
It’s possible that an llms.txt file could boost your AI SEO efforts over time.
But that would require widespread adoption.
No major AI platform has officially supported the use of llms.txt yet.
And Google has been especially clear — they don’t support it and aren’t planning to.
But big players like Hugging Face and Stripe already have llms.txt files on their sites.
Most notably, Anthropic, the company behind Claude, also has an llms.txt file on its website.
If one of the leading AI companies is using it themselves, it could mean they see potential for these files to play a bigger role in the future.
Note: While Anthropic has an llms.txt file on its site, it hasn’t publicly stated that its crawlers use or read these files.
Bottom line?
Treat llms.txt as a low-risk experiment, not a guaranteed way to boost AI visibility.
Right now, the benefits are theoretical.
But if llms.txt catches on, you could benefit in multiple ways:
The skepticism around llms.txt is valid.
Here are the biggest concerns:
Further reading: 6 AI Content Tools Worth Using
Creating an llms.txt file is pretty simple — even if you don’t have much technical experience.
One caveat: You may need a developer’s help to upload it.
Start by selecting the pages you want AI systems to crawl first.
Pro tip: Don’t dump your whole sitemap into your llms.txt file. Focus on your most valuable pages — not an exhaustive inventory.
Think about the evergreen content that best represents what you do — your core product pages, high-value guides, FAQ sections, key policies, and pricing details.
For example, BX3 Interactive lists this web development service page first in its llms.txt file:
Why? Because it’s a core service they offer.
And by featuring it in llms.txt, they’re signaling to AI crawlers that this page is central to their business.
Next, open any plain-text editor and create a new file called llms.txt.
Options include Notepad, TextEdit (on Mac), and Visual Studio Code.
Pro tip: Don’t just list bare URLs. Add a brief description for each one that explains what the page covers and who it’s for. This context could help AI understand when and how to cite your brand.
Not comfortable with markdown formatting?
Ask your developer to handle it (if you have one).
Or let an LLM do the work — ChatGPT and Claude can generate these files instantly.
Here’s a prompt to get you started:
Create an llms.txt file in markdown format using this information:
Company Name: [Your Company Name]
Company Description: [One sentence about what you do]
Important Notes (optional):
- [Key differentiator or important detail]
- [What you do or don’t do]
- [Another key point]
Products/Services
- URL: [https://yoursite.com/product-1]
- Description: [What it does and who it’s for]
- URL: [https://yoursite.com/product-2]
- Description: [What it does and who it’s for]
Blog/Resources
- URL: [https://yoursite.com/blog-post-1]
- Description: [What readers will learn]
- URL: [https://yoursite.com/blog-post-2]
- Description: [What readers will learn]
Company Pages
- About: [https://yoursite.com/about] – [Company background and mission]
- Contact: [https://yoursite.com/contact] – [How to reach you]
- Pricing: [https://yoursite.com/pricing] – [Plan overview]
Format this as a proper llms.txt file with markdown headings (#, ##), bullet points (-), and link syntax.
There are also llms.txt generators you can use.
For example, Yoast SEO lets you generate an llms.txt file in one click, complete with markdown.
Remember, the structure isn’t set in stone.
Include your most valuable pages, accompanied by descriptive summaries.
Then, customize the layout based on what matters most for your company.
Where your llms.txt file goes depends on what it covers.
You might need a developer’s help for this next step.
They’ll log in to your hosting panel, navigate to your public_html folder, and upload the file.
Once it’s uploaded, you’re ready to test.
Open a new tab and type in https://yoursite.com/llms.txt.
If you see something like this, you’re set:
Want to go a step further?
Use Semrush’s Site Audit tool to verify the file is crawlable and automatically check for any technical issues.
Your llms.txt isn’t a set-it-and-forget-it file.
Schedule a review every few months:
This ensures AI systems always see your most relevant content.
Further reading: LLM Seeding: A New Strategy to Get Mentioned and Cited by LLMs
As SEOs like to say, “it depends.”
If setup is quick and you’re curious to experiment, it’s worth doing.
Worst case, nothing changes.
Best case, you’re ahead of the curve if AI platforms start paying attention.
In the meantime, don’t neglect proven SEO fundamentals.
Structured data, high-authority backlinks, and helpful content are what help AI — and traditional search engines — understand, trust, and surface your pages.
Want to boost your AI visibility now?
Check out our AI search guide for a framework that’s already working.
The post Does Your Website Need an LLMs.txt File? + How to Create One appeared first on Backlinko.
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More than half of searches in 2025 don’t lead anywhere. People get answers from ChatGPT, Perplexity, and Gemini without clicking a single link.
Not showing up in those responses? You’re invisible to half the internet.
That’s where answer engine optimization (AEO) comes in. It helps your brand become the answer that AI tools deliver.
This guide breaks down how AEO works, how it compares to SEO, and what steps you can take to make your content more findable across modern search platforms.
Answer engine optimization (AEO) makes your content easy for AI tools to find and use as a direct answer.
This started with rich results in Google like Featured Snippets and People Also Ask, but today, AEO is about showing up in a full ecosystem of AI-driven answer engines like ChatGPT, Perplexity, Gemini, and Google’s AI Overviews.
While there are technically still links as a part of these tools, there’s no guarantee a user will click on them.
Your content needs to match how large language models (LLMs) process information if you want to appear in those answers. This includes:
These systems rely on machine learning and natural language processing to determine what content best fits the user’s query. If your site structure and content format aren’t optimized for this, you are less likely to be cited.
AEO isn’t some future tactic. It’s how visibility works now.
Search has changed. It’s not just about blue links on a results page anymore. Tools like ChatGPT, Perplexity, and Google’s AI Overviews are changing how people access information and how brands show up.
The rise of these answer engines has led to a sharp increase in zero‑click searches. In many cases, users now get what they need without ever visiting a website. That means if your content isn’t optimized for those responses, you’re missing visibility.
Voice assistants like Alexa, Siri, and Google Assistant work the same way. As generative AI improves by summarizing the web, fewer sources get shown per query, putting more pressure on marketers to be the one selected.
People expect answers fast. They won’t scroll through ten links when one will do. AEO is about aligning your content to that expectation: clear answers, fast.
And the impact isn’t just on organic traffic. AEO boosts brand visibility, strengthens trust signals, and improves discoverability across AI tools and platforms. If you’re investing in SEO but ignoring answer engine optimization, you’re missing opportunities.
AEO and SEO work toward the same outcome (getting your content discovered) but the paths they take are different.
Search engine optimization (SEO)focuses on improving rankings within search engine results pages. That includes optimizing technical elements, matching content to user intent, building links, and improving site structure. It’s about increasing visibility across a range of possible results.
Answer engine optimization (AEO) focuses on earning the single, summarized response delivered by an AI system. These systems rely more heavily on structured answers, clarity, and content that fits within specific answer formats. You’re competing for the only spot that gets shown, not position ten.
AEO is often confused with Generative Engine Optimization (GEO), which is related but distinct. GEO focuses on creating content that gets cited by AI tools as a source. AEO focuses on optimizing existing content to be surfaced directly within the answer. Both matter, but they solve different problems.
AI hallucinations happen when tools like ChatGPT give answers that sound right but are completely wrong. This happens when AI pulls outdated, misattributed, or low-quality information when summarizing information.
In one example, users asked a chatbot for medical advice and received fabricated product suggestions. Other tools have invented studies, misquoted statistics, or pulled misleading content from forums.
The risk increases when a brand has little online authority or inconsistent information across platforms. If the AI can’t verify what’s real, it fills in the blanks and gets it wrong.
To reduce your risk of hallucinated results about your business:
Protecting your brand from hallucinations goes beyond technical fixes. It’s part of owning your visibility.
Keywords alone won’t get you featured in AI responses. You need clear, credible, well-structured content that’s easy for machines to understand.
The strategies below are designed to help your site show up in AI summaries, voice results, and other answer-first formats.
Before you start new optimizations, start by reviewing what’s already working. You may already have content showing up in AI searches like Perplexity, ChatGPT with browsing, or AI Overviews in Google.
Platforms like Ubersuggest Profound track brand and URL visibility across AI answers. These tools show what questions your site already ranks for, what sources AI is pulling from, and where gaps exist.
You can also run manual prompts in ChatGPT or Perplexity using branded and non-branded queries. Try asking questions you’d want your content to answer, and take note of what shows up.
This audit shows you where you stand and helps you prioritize. If certain pages are already being pulled into AI results, you may just need small tweaks. If others aren’t surfacing at all, you’ll know where to focus first.
Search engines, chatbots, and voice assistants all aim to solve one thing: what the user actually wants to know. That’s where search intent comes in, and it’s a foundational piece of answer engine optimization.
AI tools don’t just crawl your content. They interpret it. If your page doesn’t match the kind of answer a user is looking for, it likely won’t get picked.
Intent typically falls into four categories: informational, transactional, navigational, or commercial. But when it comes to AEO, you also need to understand how people phrase questions. “What is,” “how to,” “best tools for,” and “should I” are all common patterns.
So how can you learn the intent behind the keywords you’re targeting or ranking for? Keyword research tools, like Ubersuggest and Semrush can help.
Once you understand what search terms your website ranks for, you can dig into the most popular terms. Using Ubersuggest’s Keyword Overview tool, for example, lets you see search volume and SEO difficulty.
The keywords in the above screenshot are largely informational. The searcher is hoping to learn more about digital marketing. As we continue to scroll through the list of queries , we begin to see more commercial and transactional results.
Take “digital marketing platforms” as an example:
There’s certainly some informational intent behind the question, but it’s also possible to be commercial intent. For example, a business who is looking to subscribe to a platform may want to learn more about it so they can make the right decision.
If you’re a digital marketing agency with a platform, and you understand the intent behind that keyword, you can create content that captures the customer within the purchase journey.
Content that targets the transactional intent of this keyword may be a digital marketing platform or tool roundup. You can position your platform as the best option, or even create a post with affiliate links to other relevant platforms.
Intent matters as much as the question itself. This is why you must consider the whole picture when incorporating such keywords into your content.
If your content doesn’t look like an answer, AI tools won’t treat it like one. That’s why formatting matters more than ever in answer engine optimization.
Start by identifying the questions your audience is asking. Then give them a direct response near the top of your content, ideally within the first few sentences or paragraphs.
Use clear H2 or H3 headings for common queries. Add a dedicated FAQ section if your topic has multiple related questions. Bullet points, concise summaries, and short paragraphs all help AI models parse your content more accurately.
You’re not just helping users skim. You’re helping machines understand what your content is trying to say and where it fits.
Google’s AI Overviews, People Also Ask, and tools like Perplexity and Gemini all pull from content that’s been structured clearly and answers a defined question.
This is one of the simplest changes you can make to support AEO, and it pays off fast.
Answer engines don’t just scan your website. They also pull from structured data across the web. That includes business directories, local listings, and public profiles.
Tools like ChatGPT and Perplexity can surface business info from places like Google Business Profile, Yelp, Apple Maps, and Bing. If your data is missing or inconsistent, your brand may be excluded from results.
Make sure your listings include accurate details like name, address, phone number (NAP), hours, and website. Add photos, reviews, and categories where possible. These signals all feed into the authority and relevance AI models look for.
Some key directories to prioritize:
Don’t treat this as a one-time setup. Keep listings up to date, especially if your business has multiple locations or seasonal changes.
The goal is to make it easy for AI systems to confirm your legitimacy and context. You’re giving them structured proof of who you are and what you offer.
AI systems scan for more than keywords. They look for trusted voices. If your brand is consistently cited, reviewed, and linked to across the web, you’re more likely to be featured in AI-generated responses. When we surveyed a group of marketing professionals who said that optimizing their content to appear in chatbot responses has been a major priority for them, 34 percent had the top goal of building brand awareness and loyalty.
That trust is built through authority. This includes third-party mentions, earned backlinks, expert-led content, and consistent appearances in respected directories or roundups.
Authoritative brands are also more likely to be surfaced in zero-click search, local packs, and answer engine results. Why? Because these platforms want to deliver credible information. If your site has proven expertise on a topic, it’s more likely to be chosen.
To build that authority, focus on publishing effective content, earning brand mentions in your niche, and contributing insights on third-party platforms. Guest posts, research, and interviews can all help grow your presence.
This takes time, but it compounds. The stronger a thought leader you are seen as, the harder it is for AI tools to ignore your content.
AI is changing how people search and how we create content. Used correctly, it can help you build pages that are more likely to surface in answer engines.
Start by using tools like ChatGPT to test your topic coverage. Ask sample questions your audience might type into an AI search. What comes up? If your site isn’t mentioned, or the answers are thin, you’ve found a gap to fill.
Many marketers are already leaning into this. In a survey we ran, over 81 percent of professionals optimizing for AI responses said they had been incorporating AI into their business processes for six months or more.
The top use cases included improving efficiency, sparking innovation, and enhancing customer experience. But AEO-focused content creation is where AI can deliver quick wins.
You can use AI to generate question-based outlines, draft summaries, or test how clearly your answers come across. Just don’t skip the human layer. Tools can help you move faster, but high-quality content still requires expertise.
Schema markup helps AI tools understand your content better. That can make the difference between being ignored or included in an answer.
Schema is a form of structured data that tells search engines and AI systems what your page is about. It adds a layer of clarity in the background without changing how your content looks to users.
For example, if you have a FAQ section, adding FAQ schema helps Google and answer engines extract that content more confidently. The same goes for how-to schema, product schema, article schema, and organization schema.
The more structured your content is, the easier it is for AI to match it to the right query. Schema also increases your chances of appearing in AI Overviews, People Also Ask, and AI-generated summaries.
You don’t need to add schema manually. Most SEO plugins, like Yoast or Rank Math, include built-in schema tools. There are also free generators available online if you want to apply it page by page.
Think of schema as a translator between your content and the AI tools deciding what gets shown. The clearer your signals, the better your visibility.
Answer engine optimization isn’t a one-time fix. Once you implement AEO strategies, you need a plan for tracking performance and making improvements.
Set a regular schedule to check whether your content is being picked up by AI tools. Look for patterns in which pages get cited, what queries they appear for, and where your visibility drops off.
This doesn’t require complex reporting. You can track progress using a simple spreadsheet, noting the presence or absence of your brand in AI summaries across key queries.
When something stops appearing, that’s your signal to re-optimize. Refresh the content, clarify the structure, or align it more closely with search intent. If something continues to perform well, look at what’s working and replicate that approach elsewhere.
AEO is still evolving, which makes monitoring even more important. The brands that adapt fastest will stay visible the longest.
We ran a study to understand why ChatGPT recommends certain brands in its responses. After testing over 80 possible factors, six rose to the top.
Brand mentions: The more your brand is cited across the web, the higher the likelihood ChatGPT will surface it.
Reviews: Quality and volume of customer reviews, especially on third-party sites, play a major role.
Relevancy: If your site’s keywords match the user’s query, and the page offers helpful context, you’re more likely to get picked.
Age: Older, more established brands tend to be trusted more often by AI models.
Recommendations: Listicles and curated “best of” roundups (even those using affiliate links) still influence ChatGPT outputs.
Authority: High-authority domains with credible backlinks and consistent content earn more inclusion in AI answers.
You can’t control every factor, but you can influence most of them by building strong, reliable content that other sites and users want to reference.
Answer engine optimization is the process of improving your content so it appears in AI-generated answers. It focuses on clarity, structure, authority, and accuracy—so tools like ChatGPT, Perplexity, and Google’s AI Overviews can pull your content as a trusted response.
It builds on traditional SEO but adapts it for zero-click and conversational search experiences.
Start by identifying the types of questions your audience is asking. Then create clear, concise answers—formatted with proper headers, schema markup, and supporting data. Use tools to track which content appears in AI results, and optimize based on visibility gaps.
Focus on building authority and publishing quality content that answer engines can trust.
AEO is about getting your content pulled into AI-generated responses. SEO is about ranking in search engine results pages. Both use similar tactics, but AEO requires more structured, answer-ready content.
AI is already reshaping how people search, and answer engines are gaining traction fast. If your content isn’t built for these platforms, you’re likely losing visibility—even if you’re ranking well in traditional search.
The good news: if you’ve been investing in SEO, many of the foundations are already in place. AEO simply takes it further, focusing on clarity, structure, and intent.
Tools like Ubersuggest can help you find question-based keywords, track content performance, and identify optimization gaps. From there, it’s about building better answers—and making sure they’re easy for AI to find.
Now is the time to get proactive. The longer you wait to adapt, the harder it’ll be to catch up.
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Google has added a new user agent to its help documentation named Google-CWS. This is the Chrome Web Store user agent that is a user-triggered fetchers.
More details. Google posted about the new user agent over here, it reads; “The Chrome Web Store fetcher requests URLs that developers provide in the metadata of their Chrome extensions and themes.”
What are user-triggered fetchers. A user-triggered fetchers are initiated by users to perform a fetching function within a Google product.
The example provided by Google was “Google Site Verifier acts on a user’s request, or a site hosted on Google Cloud (GCP) has a feature that allows the site’s users to retrieve an external RSS feed. Because the fetch was requested by a user, these fetchers generally ignore robots.txt rules. The general technical properties of Google’s crawlers also apply to the user-triggered fetchers.”
Why we care. If you see this user agent in your crawl logs, you now know where it is from. The Chrome Web Store fetcher requests URLs that developers provide in the metadata of their Chrome extensions and themes.
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