Wow, what a whirlwind 2025 was in the ever-evolving world of SEO! I found myself constantly amazed at the pace of change, especially with the rise of GEO and AI-driven discoveries.
The incredible advances—from multi-platform searches to innovative AI applications—made this year truly groundbreaking. As I dove into these shifts, Search Engine Land remained my trusted guide, helping me navigate what’s happening, what’s on the horizon, and, most importantly, what really matters.
I’m thrilled to share with you the 10 most-read SEO columns of 2025. These pieces, penned by some of the best minds in the field, captivated and informed readers like never before.
Reflecting on Google’s 2025 algorithm adventures, I’m reminded that fewer confirmations don’t equate to less excitement in search rankings.
Google rolled out four confirmed algorithm updates this year, including three core updates and one spam update. Interestingly, this is a decrease from prior years—seven updates in 2024 and nine in 2023.
Fewer updates confirmed, more surprises for search. Google might be confirming fewer updates, but that doesn’t mean there are fewer changes under the hood. As they’ve stated, not all core updates are announced, and I’ve experienced plenty of volatility tracking all the unconfirmed tweaks.
I’ve followed numerous unconfirmed updates on the Search Engine Roundtable, making 2025 a year of unpredictability despite fewer confirmations.
Google confirmed algorithm update summary
Here’s a timeline that visualizes all these exciting developments in 2025, showcasing the rollercoaster of changes throughout the year.
Three Google core updates in 2025. Spread over the months, we saw these core updates rolling out in March, June, and December.
March 2025 core update. The journey began on March 13, taking 14 days to unfold by March 27. Google assured us it was a routine core update, enhancing search results.
It was reminiscent of prior updates, as reflected in historical data.
June 2025 core update. Commencing on June 30 and concluding by July 17, this update repeated the thematic improvements seen previously, capturing further interest.
Intriguingly, some sites reported partial recoveries post-update, signifying its intense impact.
December 2025 core update. Starting on December 11, its rollout remains incomplete, but it’s consistently producing expected outcomes across the board.
The updates stirred considerable volatility, particularly noted during weekends like December 13th and December 20th.
One Google spam update in 2025
August 2025 spam update. Launched on August 26 and concluded by September 22, this update rapidly impacted site rankings and thankfully, some saw recoveries.
Reflecting on another year in the world of search, I’ve seen how Google labeled 2025 as year three of a 10-year transformative shift. This change, centering on AI, became undeniably evident. No longer just an experiment, AI has now firmly integrated into the core processes of search.
Here, I’ll share the most significant SEO news stories of 2025 from Search Engine Land.
Note: This overview excludes Google algorithm updates, which Barry Schwartz has covered in a separate recap published today.
10. Perplexity Ranking Factors and Systems
Diving into the intricacies, independent researcher Metehan Yesilyurt examined browser-level interactions, revealing how Perplexity scores, ranks, and sometimes drops content. His findings uncovered a three-layer machine learning system reordering entity searches, manual authority whitelists, and many engagement signals.
He also observed that authoritative domains, early strong performance, and tech-focused topics received boosts. The ranking further mirrored time decay, interconnected content clusters, and trending YouTube content that amplified visibility.
In a move all about clarity, Google introduced Query groups to the Search Console Insights report. By employing AI, it groups similar search queries into distinct audience topics. These don’t influence rankings but make performance trends more apparent, especially for high-volume sites.
I was surprised to see HubSpot’s organic traffic plummet from 13.5 million to 8.6 million within a month, mainly impacting its blog. This followed several Google updates, with SEOs pointing to thin, broad content not aligned with HubSpot’s core expertise.
The ongoing identity debate in SEO continues as Google rejects new terminologies like GEO (generative engine optimization) and AEO (answer engine optimization). They maintain that strong SEO practices are also effective for GEO, underpinning AI Overview rankings’ fundamentals.
Yet, as AI answers replace clicks, traditional search still plays a vital role in discovery, despite search behavior evolving with users seeking AI for quick answers but relying on Google for extensive research.
The expansion of Google AI Mode from a trial to an almost default, comprehensive search experience was rapid. It incorporated more in-depth research, agentic activities, personalization, and the advanced Gemini 2.5—a drastic evolution toward complex search behaviors.
This AI Mode initially struggled with transparency, breaking referral tracking and merging its performance data with standard Search Console reports, sparking concerns over visibility and attribution in a more AI-centric search landscape.
When Cloudflare CEO Matthew Prince spoke about AI disrupting the web’s search-driven business model, it resonated with many. He highlighted the disproportionate relationship—Google and AI companies scrape extensive content while returning minimal traffic, jeopardizing original publishing unless the economic model adapts.
Seeing Google’s search share dip below 90% globally for the first time since 2015 was significant, driven by shifts in Asia and the U.S. This opened opportunities for Bing, Yandex, and Yahoo to capture some of Google’s shrinking share.
Google’s stricter stance on AI-generated content was clear when it instructed quality raters to assign the Lowest ratings to predominantly auto-generated pages. The expanded spam definitions targeted scaled, low-effort AI implementations.
Concurrent tests of AI-generated and AI-summarized search snippets indicated a future where AI not only critically examines content but also influences its presentation in searches.
I noticed analysis from various sources showing a troubling trend: Google Search offered more impressions and AI Overview visibility but resulted in fewer clicks. This was especially evident with non-branded, informational queries where AI Overview overshadowed classic results.
Brands mentioned in AI Overviews saw improved CTR, whereas those outside these features lost prominence, emphasizing that AI visibility is pivotal in driving successful outcomes.
Google’s removal of the &num=100 search parameter has widely impacted the SEO industry, disrupting rank-tracking tools and coinciding with a noticeable decrease in Google Search Console impressions and query counts.
Initial evaluations suggested that the majority of sites experienced reduced visibility, especially beyond Page 1, hinting at historic overreported metrics and a more realistic view of organic performance going forward.
I recently delved into OpenAI’s intriguing move towards integrating ads within their AI responses, which could potentially transform digital marketing by providing advertisers with a highly contextual channel.
OpenAI is laying the foundation for developing an advertising model, which could signify a shift from solely relying on subscriptions and enterprise agreements for revenue generation.
Unpacking the Strategy. As reported by The Information, OpenAI is in the early stages of discussing ad formats and partnerships, potentially placing ads within AI-generated responses. These discussions are preliminary, but it’s clear that ads are becoming an integral part of OpenAI’s long-term financial strategy.
The Implications. This exploration into ads embedded in AI responses offers a unique opportunity to reach users right as they seek information. It positions OpenAI to compete with industry giants like Google and Meta, while also raising questions about user trust and engagement. Early adopters might gain a competitive edge since the dynamics differ from traditional digital ads, marking a new era in advertising.
Navigating User Experience. OpenAI seems to be cautiously approaching this initiative, focusing on maintaining a seamless user experience and not watering down trust in their AI models. Initially, any ad implementation will likely be carefully curated and contextually relevant to enhance, rather than disrupt, user interactions.
Considering the Broader Impact. Given the escalating costs of infrastructure and the increasing demand for revenue growth, integrating ads could be pivotal for OpenAI. This becomes especially relevant as generative AI continues to redefine how users search for information and discover products.
Future Developments. As these ad plans evolve from internal planning to public trials, a critical area to watch will be how transparently they are implemented and whether users will embrace ads within AI-driven results.
In Conclusion. OpenAI isn’t hurrying to deploy ads on the market, but the groundwork is being set. Their eventual full-scale deployment could reshape not only AI tools but also the digital advertising landscape as we know it.
Hey there, I know we’re in some murky waters right now. The drop in organic traffic is concerning, and it seems that the little bit of referral traffic we’re getting from LLMs like ChatGPT isn’t making up for it.
The truth is, the belief that “traffic is just coming from different places” isn’t entirely accurate. Sure, the way people search and engage is shifting, but click-through rates are plummeting in almost every sector.
Understandably, there’s a lot of anxiety in the industry about SEO’s future and whether AI will make our roles redundant. Bringing these concerns to the C-suite can be daunting, but now is not the time to shy away.
The reality is, it’s the perfect moment to tackle these issues head-first. Our leadership needs to know what’s happening and most importantly, how we’re responding.
This is a great opportunity to educate, realign expectations, and outline how our SEO strategy is evolving. Schedule that meeting, and let’s get this conversation started.
Here’s my plan to maximize the value of this crucial discussion.
Don’t avoid leadership — address AI visibility head-on
I’m not suggesting you picture leadership in their underwear to make conversations easier. Let’s leave the awkwardness aside.
Instead, show up ready to lead the dialogue. Here’s how to guide the discussion effectively.
Set the tone from the outset. They’ll appreciate you broaching the topic proactively rather than having someone else initiate it later.
Explain things honestly, provide clarity, and avoid sugarcoating the reality of what’s happening.
Let’s dive into the key facts to bring to leadership for a clearer picture.
Why SEO is down and how that impacts business
This is our chance to present the facts clearly rather than invoking fear. An honest overview of how the industry’s changes affect us is vital.
Here are critical events impacting performance:
Tools like ChatGPT, Gemini, and Perplexity are reshaping user behavior, diverting searches away from Google.
Google’s AI Overviews (AIOs) are increasing in search result pages, reducing clicks to third-party sites significantly. (Some report a 61% decrease in CTR.)
Despite LLMs sending some traffic, it’s minimal compared to what’s been lost from traditional search.
Bing’s AI-powered search summaries had limited impact due to a smaller market share.
Next, give a concise, data-driven picture of what’s changed for us and its impact. If organic traffic has dropped by 30% and revenue dipped, be upfront about it.
Anchor the talks in measurable results and their alignment with our goals. Ensure accuracy with your analytics team.
Here’s the data we need to present.
Share revenue, leads (or key actions), and organic traffic data over time, ideally with year-over-year figures.
These figures ground the discussion in business impact, not mere ranking metrics. Comparing data yearly helps separate seasonality from actual declines.
Export keyword data you’ve been tracking, as it’s valuable for Google and Bing. LLM tracking adds further context.
Rankings shouldn’t be a standalone performance metric. However, in times like these, understanding rankings is crucial for identifying lost demand or search shifts.
Analyze click/impression and CTR data in Google Search Console and Bing Webmaster Tools. Identify if SERPs with decreased CTR showcase AIOs.
This showcases real performance slides or industry-wide impacts. If pages losing clicks also show AI overviews, competitors are likely in the same boat — another crucial piece of the puzzle.
Once you share the business’s current state, brace for questions. Don’t wait for them; steer the narrative. Describe the broader shifts, industry trends, and emerging tech driving these changes. Possible action steps include:
Fetch traffic estimates and keyword rankings for top competitors. Are they experiencing similar downsides?
Use Google Trends and Exploding Topics to observe growing or waning interest in topics/products in our industry.
Utilize AI visibility reports to demonstrate brand presence in active conversation platforms (LLMs).
This isn’t about placing blame. It’s about showing comprehension and adapting to landscape shifts impacting performance.
What we’ve learned so far and where we’re going
Now’s the time to prove that we’re not just diagnosing problems but devising solutions. Leadership might not favor all answers, but they’ll respect your forward-thinking mindset.
Make it clear that, although the rules are changing, our team is swiftly adapting for upcoming search challenges. Then specify your needs, whether it’s budget, headcount, data support, or cross-functional alignment, to execute rather than merely presenting a problem.
Here are strategies to progress:
We’re enhancing our brand’s visibility beyond traditional search, focusing on AI-generated answers and new discovery platforms.
This involves tracking essential buyer queries and understanding our brand’s current position to prioritize content, PR, and partnerships for optimal visibility.
The aim is straightforward: if answers don’t draw clicks, our brand must still appear in those solutions. Consistent mentions/citations across the web facilitate this.
We’re revamping content strategy to stress entities and topics, not just keywords and rankings.
LLMs favor brands with comprehensive, consistent topic coverage and expertise signals. This affects our publishing, content structuring, and PR/product collaborations to build authority. This is SEO content 2.0, demanding effort, but the rewards will be significant.
We’re investing in visibility measurement for both traditional and new search channels.
Google organic traffic isn’t the sole truth anymore. We’re developing reporting to include AI surfaces, social discovery, referrals, and offline demand for a comprehensive perspective.
AI Overviews represent a lasting shift.
This requires recalibrating traffic baselines, forecasts, and targets to account for fewer classic blue link clicks. We plan for a reality where this becomes normal.
“AI Mode” might become Google’s default by 2026.
If more searches receive direct answers from Google, fewer visitors reach us. This alters lead/sales expectations and demands a strategy overhaul, including budgeting.
How we’ll be proactive and adapt to the new search landscape
Having explained what’s happening and how we’re adapting, it’s essential to stress that success requires alignment, resources, and continuous support.
Use this chance to outline needs, making it easier for leadership to approve plans without overwhelming decisions.
Here are essential adjustments to consider.
Search success in the AI era is a new measure; optimization takes time.
Agree upfront on timelines, leading indicators, and reporting frequency. Rankings, traffic, and last-click revenue won’t always align, so patience in adapting is necessary.
Executive backing is crucial for prioritizing long-term brand building over quick wins.
Leadership must accept that essential SEO initiatives may not yield immediate results but are vital for sustained visibility in search and AI-driven spaces.
Flexible budgeting to experiment with channels, content formats, and AI tracking tools.
A part of the marketing budget must focus on trials — from AI tools and data implementation to interactive content and strategic partnerships.
Collaboration with other departments is key to altering organic growth measurement.
SEO can’t work solo. We need analytics for new dashboards and coordinated PR and content efforts to align with significant topics.
This is your moment to lead the AI visibility discussion
You’re not merely reacting. You’re guiding through change. AI and LLMs redefine search, discovery, and interaction. This isn’t panic time, nor a case for the “organic search is dead” mantra. It’s about adaptation.
A crucial step is constant monitoring. A one-time pitch is valuable, but marketing efforts always need measurement. Regularly set an AI visibility update metric alongside standard metrics.
As AI and LLMs progress, leverage measured data to update leadership on changes and adaptations.
By initiating discussions, grounding messages in data, and suggesting actionable plans, your strategic acumen becomes evident to executives.
This shift isn’t solely about SEO; it’s about securing future visibility, trust, and traffic across various environments. Whether it’s Google, ChatGPT, or elsewhere, your focus should be on being present where your customers engage.
In a world where Google’s AI Overviews address more queries instantly, I’ve found that vibe coding allows us to craft interactive experiences that AI simply can’t replace.
I’ve noticed that search marketers are now shifting their roles from merely optimizing to actually building. Tools like vibe coding, coupled with AI-powered development technologies, have significantly reduced the time from idea conception to execution—from weeks to just a few hours.
These tools don’t make developers obsolete, but they empower search teams to test and create interactive content on their own timelines. This is crucial, as Google’s AI Overviews increasingly pull answers directly into the SERP, reducing clicks to our brand websites.
For marketers, building unique, conversion-focused tools is becoming an indispensable tactic in this zero-click environment.
What is vibe coding?
Vibe coding is about creating software by guiding AI with natural language instead of traditional coding methods. This means focusing on the tool’s purpose, appearance, and response, while AI takes care of implementation.
This term gained popularity in early 2025, thanks to OpenAI co-founder Andrej Karpathy, who described it as a loose, exploratory building style. The appeal? Speed. The risk? Potential shortcuts that could lead to fragile systems.
Today, AI-powered development platforms extend this approach to non-engineering teams, with tools like Replit and Lovable, allowing everyone to build and iterate quickly.
Vibe coding vs. vibe marketing
It’s important to distinguish vibe coding from vibe marketing. Vibe coding involves AI tools designed to create applications and interactive experiences, whereas vibe marketing uses automation platforms to connect existing tools and systems.
Together, these approaches empower search teams to build and operationalize their creations efficiently.
Why vibe coding matters for search marketing
I believe that soon, AI-powered coding will be an essential part of any marketer’s toolkit. It allows us to create sophisticated interactive tools that Google’s AI can hardly mimic, enhancing our SEO and PPC strategies.
With vibe coding, my team can rapidly develop tools that boost conversion, like interactive content aimed to improve user engagement—a factor crucial for both SEO and PPC efforts.
Through vibe coding, I’ve created custom systems that help manage our operational needs efficiently, saving time and costs. For instance, a project quoted at $55,000 was completed in under a week using Replit for just $20 a month.
The opportunity to teach these skills to clients also adds significant value, emphasizing the transition from “we’ll do it for you” to “we’ll build it with you.”
Vibe coding offers a competitive edge, allowing us to navigate zero-click search environments while fortifying long-term relationships with our clients.
Top vibe coding platforms for search marketers
Several leading vibe coding platforms are making waves. My personal preference is Replit for its flexibility, though Figma Make is a great choice too, particularly as it integrates well with our existing workflows.
Testing different platforms will help find the best fit. Whether it’s Lovable for beginners or Cursor for advanced users, there’s a solution tailored to your needs.
Practical SEO and PPC applications: What you can build today
Vibe coding can create a variety of tools, from lead generation calculators to interactive content that increases website engagement. The key is to build tools that fill existing gaps, providing unique and useful solutions.
For instance, I developed an AI-powered accounting ROI calculator, a tool that couldn’t be easily replaced by Google’s direct answers. This not only helps the target audience but also boosts SEO efforts by encouraging repeat visits.
A 7-step vibe coding process for search marketers
I’ve found that following a structured workflow is crucial when using vibe coding. This includes thorough research, creating a content spec document, and iterating designs before functionality.
These steps ensure a comprehensive approach, allowing for prompt testing and deployment. Updating documentation at each milestone helps in managing future updates or revisions.
The dark side of vibe coding and important watchouts
While powerful, vibe coding tools come with risks. Security and compliance issues, price creep, and technical debt are concerns that require careful attention.
Always ensure security reviews and keep track of costs as projects evolve. Monitoring these risks can make vibe coding a reliable tool rather than a complicated headache.
Vibe coding is your competitive edge
In this evolving landscape, vibe coding gives us the ability to build unique digital experiences. It’s a skill set that empowers us to thrive, helping create meaningful, interactive content that stands out in the crowded search environment.
Embracing vibe coding not only promotes strong client partnerships but also equips us to adapt to new search realities, making it a pivotal skill for future success.
Hey there! I’ve been diving into ways to develop an effective AI-ready content strategy that’s perfect for large language models (LLMs) to parse, trust, and cite. It’s fascinating how the focus has shifted from just getting clicks to ensuring understanding through visibility. Let me walk you through my journey of crafting this strategy.
Imagine building a content framework where AI tools not only recognize but also rely on the information you provide. This is where content tailored for LLMs comes into play. It’s all about providing data that these models find credible and resourceful. Essentially, visibility is now measured by how well the content communicates rather than just its ability to attract clicks.
As I started building my strategy, I focused on ensuring that the content is structured and detailed enough for LLMs to easily process and extract valuable insights. This involves more than just surface-level content optimization but delves into creating comprehensive narratives that AI can effectively utilize.
I’ve been observing how AI is transforming search, yet the timeless principles of SEO still seem to bring in the majority of traffic. It’s fascinating to look at data that show which strategies really work.
Generative AI is a huge trend right now. It’s featured in every conference and is all over my LinkedIn. Businesses, mine included, are rethinking organic search.
We’re all in a race to optimize for AI Overviews, work on vector embeddings, and reconfigure content models around LLMs. But what’s less talked about is the simple truth: AI isn’t yet the primary driver of web traffic for most of us.
While AI-driven search is gaining momentum, the LLM platforms collectively account for just a tiny fraction, about 2-3%, of the organic traffic that Google alone provides.
However, I’ve noticed that many teams, maybe even yours, are investing more energy in AI strategies instead of reinforcing essential SEO fundamentals that still deliver tangible results. Focusing too much on the future means we’re not making the most of today’s opportunities.
In my experience, looking closely at proven SEO tactics and real-world data can highlight how they still effectively move the needle today.
Quick SEO Wins Still Deliver Substantial Gains
It’s easy to overlook minor updates when we’re caught up with trends like vector embeddings and semantic SEO. Yet, these small changes can have a significant impact.
Take title tags, for instance. They’re among the simplest and most effective SEO tools. I’ve seen many websites fail to use them effectively, often neglecting to target the right keywords, include key variations, or use any keywords at all.
Just recently, a simple change of adding “& [keyword]” to a client’s homepage title tag resulted in a surge in keyword rankings, clicks, and impressions. No other changes were made, yet the results were significant.
Combining this with other strategies like on-page copy edits, internal linking, and backlinks can lead to ongoing growth. It might sound basic, but these tactics continue to work wonders. Don’t let advanced GEO strategies blind you to simple, impactful tactics.
The Importance of Content Freshness and Authority
The rise of AI might have pushed some tactics like the skyscraper technique into the shadows.
This approach involves crafting superior content for keywords and topics that are already ranking, aiming to outperform existing results. While the internet is flooded with similar content, focusing on keyword authority and freshness can be incredibly effective.
I’ve witnessed this success multiple times. Recently, a client’s article on a well-established topic quickly climbed to the second spot, generating new clicks and impressions almost instantly.
The success was due to the site’s strong authority and because much of the competing content was outdated. Although this strategy may not suit every situation, ignoring it could mean missing out on clear wins.
User Experience: A Key Conversion Lever
Although there’s buzz around AI-driven shopping experiences, the core principles of website optimization remain irreplaceable. Some argue that AI will soon take over interactions and conversions, but this is far from the present reality.
Many websites still rely on traditional search-driven traffic and website-based conversions. Whether visitors come from organic search, paid ads, AI referrals, or direct, what matters is a fast site, an excellent user experience, and a well-defined conversion funnel.
Optimizing these aspects can lead to remarkable performance gains, as I’ve seen through a simple CTR test with a client, which yielded impressive results.
Brands prioritizing user experience and conversion rate optimization will continue to outperform those who don’t. This competitive advantage will only grow if teams delay waiting for AI to perfect conversion mechanisms.
AI’s Role in Search and the Power of Existing Strategies
AI is indeed reshaping search by altering user behavior, influencing SERP appearances, and complicating attribution. Yet, the real risk lies in overreacting to AI at the expense of proven strategies.
For most sites, traditional organic search continues to be the primary traffic source. When well-executed, SEO fundamentals still deliver results. Quick wins and high-quality content are rewarded, and optimizing user experience remains critical.
These efforts support each other, improving organic visibility and complementing paid search and LLM visibility. Staying updated on AI developments is vital but not at the cost of current growth-driving strategies.
Back in June 2025, I noticed an interesting infographic circulating widely. It highlighted the most-cited websites by AI models, according to a comprehensive SEMrush study of over 150,000 citations. Naturally, seeing Reddit at the top sparked a buzz among marketers, who began to believe that featuring on Reddit was key to their GEO strategy.
But, here’s the catch: most of these citations were research-oriented, not necessarily geared towards buying intents. For instance, Reddit was frequently mentioned in queries like “Where in Europe should I take a family vacation?” but not so much in “What are the best web design firms?”
This led to some misguided assumptions. Although Reddit does play a role in AI models like ChatGPT, Perplexity, and Gemini, it represents only about 11% of their commercial recommendation algorithms. So, placing too much emphasis on Reddit won’t really boost your product or service visibility in these AI models.
The Most Cited Websites by AI Models for Buying-Intent Queries
Our research team dug deeper into this in October 2025 and later updated it in December 2025. We conducted 36,127 buying-intent queries on ChatGPT and tallied the top-cited websites. Our “buying-intent query” was defined on a scale measuring how close a query was to a purchase decision. A simplified version of this scale is captured in the infographic below:
A query scoring higher than 1.35 was marked as “buying-intent.”
Top Website Types Cited by AI Models for Buying-Intent Queries
We meticulously categorized the types of websites AI models prefer for such queries. Understanding the types helped us unravel which channels are more effective at GEO—essential in influencing AI chatbots to nominate certain companies.
Top Website Types Cited by AI Models for Buying-Intent Queries
#
Website Type
Description
# of Citations
1
Product Recommendation Media
“Best of” and “Top 10” review sites largely monetized via affiliate links (e.g., Wirecutter, Tom’s Guide, TechRadar).
7,642
2
Consumer Review Platforms
User-generated review aggregators like Trustpilot, BBB, and Google Reviews.
5,983
3
Traditional Media
Established publishers including product roundups or consumer coverage (Forbes, NYT, Wired).
4,581
4
New Media
Digital-native outlets that frequently review or endorse products (TechCrunch, The Verge).
3,826
5
YouTube / Video Review Channels
Video-based reviews and product comparisons often transcribed or summarized by AI models.
Regulatory or authoritative institutional content (FDA.gov, FTC.gov).
159
20
Standards & Certification Bodies
Official verification or compliance organizations (UL, ISO, Energy Star).
119
The major takeaway from parsing this data? Websites offering list-based product recommendations feature heavily in AI rankings. Being listed on these commercial publications can greatly enhance a product’s visibility in AI recommendations like ChatGPT, Perplexity, and others.
Industry Breakdown: Websites Most Cited by AI Models for Buying-Intent Queries
Next, our analysis focused on the top three websites each industry traditionally relies on. This provided a glimpse into which platforms AI models commonly heed within specific verticals, giving GEO marketers a decisive edge in targeting their media placement efforts.
Top Websites Cited by AI Models in Buying-Intent Queries, by Industry
Industry
Top-Cited Websites by AI for Buying-Intent Queries
eCommerce
Wirecutter, Forbes, Tom’s Guide
Managed Services
Clutch, G2, UpCity
Healthcare
Forbes Health, Verywell Health, Medical News Today
A key insight here is the fragmented nature of website citations. Trade journals contributed more than the top three sites in any category. As with website types, the predominance of review sites and product recommendation platforms was notable.
Questions, Media Inquiries, or Other Requests
Curious about our study? Have a media request, or want a PDF copy? Reach out to us here.
