Stop Playing One Game When the 2026 Buyer Journey Demands Two

The 2026 Buyer Journey Demands Two Games: How AI Visibility and SEO Serve to Answer Two Different Moments in the Journey

TL;DR

• 68.01% of Google searches in the first four months of 2026 ended with zero clicks, according to SparkToro's clickstream analysis.
• 8% of the click-through rate on traditional results is when an AI summary appears in search results as opposed to 15% without an AI summary (Pew Research, March 2025 data).
• 1.13 billion AI referral visits to the top 1,000 websites in June 2025, up 357% YoY (Similarweb, 2025 Generative AI Report).
• A BusySeed healthcare client saw 65%+ engagement on AI referral traffic after BusySeed ran a generative optimization strategy for them.
• Being cited in an AI Overview increases organic clicks by 35% compared to not being cited, based on Seer Interactive’s study of 3,119 terms across 42 organizations (Study: The AIO impact on Google CTR — September 2025 update).

What Actually Changed — And Why Most Teams Are Still Fighting the Last War

Most digital marketing teams in 2026 are organized around a single objective: get higher up in the rankings, get more clicks, get more traffic. It’s a sensible strategy when you think about it, because it worked for so long. In fact, it worked for so long that we tended to forget that the buyer’s journey is not one constant linear process, but rather it has gone through several different iterations over the years. And now there are two different moments in time, and you are optimizing for only one of them.

Understanding GEO vs SEO is not a matter of abstract discussion; it is the working difference between entering a buyer’s consideration set early on and arriving at the short list after other brands have been considered. As with so much else in 2026, SEO has changed. Its function in the buyer’s journey is different now than it was three years ago. It is not the primary objective of SEO and digital marketing to drive traffic, but that is the starting point for most teams. And that’s the problem.

For instance, the user types in “how to manage patient intake for a multi-location healthcare practice” into the Google search bar and the AI summary appears listing the different ways to manage patient intake for a multi-location healthcare practice. The user would then click on a BusySeed healthcare client’s website only 8% of the time versus 15% without the AI summary.

That’s the problem. And it’s more urgent than most teams realize. The decision making process has fundamentally shifted, requiring brands to adapt their strategies to account for both traditional search and AI-driven discovery.

GEO vs SEO — Are These Actually Two Different Jobs Now?

Yes. They are. And pretending otherwise is costing brands real pipeline.

The GEO vs SEO debate has reached a new level of maturity. Instead of only speculating on what could happen, we now have hard data that describes what happens at every level of visibility. In the end, it’s up to each organization to decide what they want to achieve with their SEO efforts. Blue-link organic rankings are where people who already know what they are looking for go to find pricing, specs, comparison pages, documentation, and reviews. They are close to making a decision and are looking to validate their thinking. Don’t throw the baby out with the bath water and abandon traditional SEO.

The kind of visibility from AI that opens up for websites is upstream from the typical points of visibility that websites can get buyers to. When a buyer opens up ChatGPT, Perplexity or Google’s AI Mode and does a search for something like “what’s the best way to manage patient intake for a multi-location healthcare practice”, they are forming an opinion about what good patient intake management for a multi-location healthcare practice looks like before even naming any single brand. They are figuring out a category and making a shortlist of potential solutions. Your website could get 100 sessions from a buyer searching for the patient intake management of a multi-location healthcare practice and get none of them from the kind of search above.

The Pew Research study of 68,879 Google searches for example found that AI summaries appeared in 8% of 1-2 word searches, but 53% of searches that consisted of ten or more words. These are top-of-funnel, exploratory searches where the buyer is trying to understand a category and form an opinion of what good might look like. The long, conversational search query is likely to be answered by an AI summary before the user even sees your organization’s listing in the organic results. Thus GEO vs SEO are two very different disciplines and most organizations are poorly served by treating them as if they were the same.

Understanding user intent SEO in this context is critical. Brands must now consider how their content appears in AI-driven summaries, not just traditional search results. This shift requires a fundamental rethinking of how to optimize content for Google AI overviews.

User Intent SEO — Has the Definition Actually Changed?

It has, and not in a minor way.

When the term user intent SEO was first released to the SEO community, the typical explanation for the term would refer to categorizing keywords into information intent, navigational intent, transactional intent and commercial intent and writing corresponding content to match the intended use of a search query by a user conducting a search for that keyword. In 2026, all of that is still correct; however, SEO practitioners must now add an additional layer of visibility to how a search query will be answered by AI prior to a user’s consideration of clicking to go to a web page to answer the user’s search query.

For years SEO marketing consultants have grouped terms by user intent SEO. Informational intent, Navigational intent, Transactional intent, and Commercial intent. Then matched content formats to the intent behind a term. Such as a definitive guide for terms with Informational intent. The above search term for “how does generative AI affect healthcare compliance” would be a very good opportunity for content marketing. The SEO would write the content to rank for the term, and then people would click on the link to the brand’s site and earn the conversion for the brand. However, with the current setup of AI the AI can answer the question before the user even considers clicking on a link to the brand’s site to find the answer to their question.

So, the re-framing of the term user intent SEO as it pertains to 2026 needs to be around the following basic query: Where will this person encounter the answer to their query and what must you do to get included in the answer that they encounter. This is where the need to optimize content for Google AI overviews becomes paramount. Brands must ensure their content is structured in a way that AI systems can easily extract and cite it.

The decision making process now begins in AI interfaces, making it essential for brands to adapt their content strategies accordingly. This means creating content that not only ranks well in traditional search but also appears in AI-driven summaries.

Ecosystem 2026 - SEO and Digital Marketing?

SEO and digital marketing — Where Does the Ecosystem Actually Stand? (Pew, SEO, and AI) Seo or digital marketing, how do the two fit together? From the outside, it appears that those practicing Seo generally exist in their own world and that of paid media, content, and brand, yet they are highly interconnected. This complicated relationship has, historically, made sense given that earlier forms of Seo practice consisted mainly of highly technical work (as well as keyword research) that differed from that of other areas of SEO and digital marketing. But today, things are quite different.

Converging all channels into one large Visibility strategy is the new direction of all SEO and digital marketing in 2026. All forms of online marketing are to be executed as one process in order to reach the one big goal: Visibility. In a recently updated study by Seer Interactive (Seer Interactive - The massive influence of the AIO (AI Overview) on the Google CTR of organic results, 3,119 AIO’s, 42 websites, 25.1 million organic impressions for 24 months, June 2024 - September 2025) the AIO’s (artificially generated search results) that Google is using in the search results to enhance user experience, in a huge study have been analyzed as part of Google’s search results. The study proves that the visibility of a brand in AI-Generated Search Results has a huge influence on the CTR of organic results. It states that when a brand is NOT mentioned in an AI-Generated Overview the CTR of organic results declines with a massive 65.2% YoY, whereas when a brand is mentioned in the AI-Generated Overview the CTR of organic results declines with 49.4% YoY. Furthermore the study states that 35% of total organic clicks were generated by those cited queries in the AI Overview.

For example, for the buyer with informational intent of “how does generative AI affect healthcare compliance”, you could still utilize this opportunity for wonderful content marketing. But now, the way your buyer will encounter that information, read that information and click on it to learn more will be dramatically different than before. Before, your content marketing efforts would lead to a click from the buyer after they had read a definitive guide to how the generative AI is affecting compliance in the healthcare. Now, the buyer would read the answer to their question first within an AI interface (e.g. Google Search results page Overview), and then potentially click on other links for more information.

While there is considerable evidence to support the contention that improving the content to earn more AI citations will also improve traditional organic rankings, it is not 100% clear how SEO and digital marketing will change as a result of this new form of Search Engine Optimization. After all, the Seer Interactive study that provided all the evidence cited above only looked at a number of variables and it would be foolish to assume that all situations would be the same.

To optimize content for Google AI overviews, brands must focus on creating content that is easily extractable by AI systems. This involves structuring content in a way that AI can understand and cite, such as using clear definitions, step-by-step processes, and comparison tables. This approach aligns with the evolving decision making process, where buyers increasingly rely on AI-driven summaries to inform their choices.

How to Optimizing Content for Google AI Overviews

There is no GEO markup or special schema that can be added to a website to suddenly have all Google’s AI features activated. There is no “llms.txt” file that can be added to a root directory and suddenly a website will have all the AI enabled features of Google Search turned on. In fact, according to Google’s AI optimization documentation, SEO fundamentals still apply, that no special optimization is required beyond what good SEO already demands, and that llms.txt has no effect on Google Search. If you've been sold a "GEO framework" that claims to require entirely new technical infrastructure outside of standard SEO practice, be skeptical.

Google’s AI Optimization Guide lists the fundamentals for Google’s AI Search Optimization which will improve a brand’s visibility within search results generated by AI. Thus, there is no additional required optimization, a so-called ‘GEO framework’ that requires additional structure etc. does NOT improve the visibility in Search and is just hooey. Google explicitly states that llms.txt has NO EFFECT on Google Search. Thus, beware of anybody who’s trying to sell you a ‘GEO framework’ or anything similar as additional required optimization on top of regular SEO – it’s just junk.

SEO and digital marketing strategies must now account for how to optimize content for Google AI overviews. This involves creating content that is easily extractable by AI systems, such as using clear definitions, step-by-step guides, and comparison tables. These formats help AI systems understand and cite your content effectively, which is crucial for visibility in AI-driven search results.

SEO practices for Google’s Al overviews are real and matter for now. But this is going to fall squarely within the remit of content strategy and information architecture. So, for now, anyway, we can write up a piece of content in order to ensure that a language model is able to pull out a specific, citable and most importantly, trustworthy answer from said content. Again, that’s not to say that this is not related to writing a page in order to rank for a particular keyword – but it’s not the same thing either.

There is no secret GEO markup or special schema to Google’s Search Engine and other Google’s products and services and therefore no special llms.txt hack which unlocks Google’s Search Engine AI features and therefore no special Google’s Search Engine AI optimization for Visibility and therefore no separate or in addition to the usual SEO visibility work with Google’s Search Engine and therefore no “GEO framework” requiring entirely new technical infrastructure outside of standard SEO practice to Google’s Search Engine and therefore none of that pseudo SEO stuff. But on the other hand, creating so-called Citation-Ready Content Blocks represents a best practice to optimize content for Google AI overviews. Such blocks of content are, for instance, a short definition or a list of steps with a result of each step, a comparison of A vs B or even better: A vs C, where A, B and C are options to achieve something. A table with clearly labeled columns and within each column data that doesn’t need additional context outside the table itself. And finally a summary of a page’s content that is 100% identical to the content on said page. Such a summary is used for the structured data (schema) on said page. Therefore such a summary is also used for the structured data of said page’s, once such a summary is created for a page.

Google’s success guide for AI search outlines four areas where brands will see greatest success with the new search interface: information architecture, entity structures, authority and distribution. The new AI-powered search results will favor the brands that have created the greatest and most clear information architecture on their website, have defined entities well and have the greatest credibility and most distribution of their content where humans and models would look for authoritative information on a subject. Examples of this would be industry publications, research papers, expert roundups and reviews of products and services by third parties.

One last thing, for those creating content that will appear in Google Al overviews: there are going to be certain authority signals that matter far, far more to you than others. For example, Pew Research Center recently released a short read looking at Google users, links, and how we interact with search results that have an AI summary. They report that .gov sites are 6% of the sources that get linked to in AI Overviews (as opposed to 2% of sources that get linked to in regular results). So, to gain visibility in the AI Overviews for healthcare, finance, and legal brands, you’re going to need to create content of similar rigor with similarly strong authority signals. This means primary citations, the published credentials of the author, a clear methodology for how the content was created, a clear and up to date timestamp for when the content was last updated, and so on. If you’re creating content intended for use in Al overviews, it should have the same level of quality as content created by the big, institutional sources that already appear in your results.

Understanding user intent SEO is crucial in this context. Brands must ensure their content aligns with the decision making process of modern buyers, who increasingly rely on AI-driven summaries to inform their choices. This requires a strategic approach to SEO and digital marketing that accounts for both traditional search and AI-driven discovery.

The decision making process — Where Does AI Visibility Actually Intervene?

Here is a hypothetical for a hospital administrator that every brand strategist should read and think about.

Imagine a hospital administrator who’s been tasked with finding a better patient communication platform. She doesn’t start with Google. She opens an AI assistant and types: “What are the most important features to evaluate when selecting a patient messaging system for a mid-size hospital?” The AI gives her a thoughtful, multi-point answer. It names two or three vendors as examples of platforms that address these criteria well. It doesn’t name your brand. She takes notes, builds a rough evaluation framework, and two days later starts searching Google for specific vendors. Your brand ranks well for “patient messaging platform.” She finds you. But you’re already playing catch-up — because the decision making process formed a shortlist before you entered the picture.

This is the 2026 buyer journey in a nutshell. The early stage of the decision making process now occurs within AI interfaces. Therefore AI visibility and the decision making process are two things that as a growth strategist you need to think about hand in hand.

It is also very important to note that the process of the buyer researching, evaluating, comparing and deciding has not changed; only the location of the beginning of the process has. The influence on the buyer’s search for information now begins within the AI interfaces. For the vast majority of search queries this is where the first chapter of the decision making process unfolds for the buyer.

All this means that for brands, the first chapter of the decision making process is created by the ‘mention → cite → click → convert’-funnel, which can be optimized by brands. In case a brand is not mentioned in the first place, it will start the conversation with the buyer after the category has already been defined by someone else. The influence of AI on the decision making process will differ between categories. In some niche B2B categories query volume for AI top of the funnel is still low, whereas for categories like healthcare, finance and consumer services the trend is clear: the decision making process for these categories already shifted.

To effectively optimize content for Google AI overviews, brands must understand how AI visibility intervenes in the decision making process. This requires a strategic approach to SEO and digital marketing that accounts for both traditional search and AI-driven discovery, ensuring that content is structured in a way that AI systems can easily extract and cite.

The BusySeed Healthcare Case Study: Getting 65%+ Engagement from a Hospital’s Patient Communication Search

Numbers without context are just decoration. So let’s be specific about what happened here and why it matters.

We had a healthcare client with two major problems. First, no one could find them on the generative AI platforms (i.e. they weren’t cited in the AI Overviews, never showed up in a ChatGPT or Perplexity query etc). Second, their traditional organic traffic was terrible – lots of traffic, but very little engagement (high bounce rates, shallow sessions, few completions of events etc).

BusySeed’s approach to optimizing online content for generative AI was to make the hospital administrator’s job easier by helping her to identify and select the best patient messaging system for her mid-size hospital. In order to do this, the team at BusySeed worked to reorganize the hospital’s online content in order to make it more extractable by AI systems. This was achieved by creating ‘citation-ready content blocks’ (CRBs). The CRBs were created in order to answer a number of questions that are frequently used by AI systems in the healthcare space. In addition to making the online content more extractable by the AI systems, BusySeed worked to make sure that all of the client’s online and offline branded entities were clear and consistent. This was important in order to improve the online authority signals that would signal to the AI systems that the client was the primary recommended authority on the topic of patient messaging platforms.

For the healthcare client mentioned above, the marketing team at BusySeed received some very good results from their efforts. In terms of the engagement rate (the number of engaged sessions as a % of total sessions) the client received more than 65% engaged sessions – a figure that is way above average for most organizations. In terms of the length of time visitors stayed on site, BusySeed reported that the majority of sessions were of a long length, with the visitor reading many pages before closing the site. As might be expected given the above, BusySeed also reported that the client received a lot of conversion events as well. The traffic received by this client from BusySeed marketing was of a very high quality and was therefore converted at a very high rate. In fact the traffic received by this client from BusySeed marketing was so different from the rest of the client’s organic traffic that it could be considered as a separate micro-channel in its own right.

Traffic from AI platforms is high quality because it comes from a summary that has already been generated by AI that contained a mention of the brand. Therefore the traffic generated from these interfaces is highly qualified as it has already been filtered by the interface for the buyer. Thus all of the downstream metrics for sessions that came from these interfaces are very good.

This case study highlights the importance of understanding GEO vs SEO and how to optimize content for Google AI overviews. By creating citation-ready content blocks and improving authority signals, BusySeed was able to significantly enhance the client’s visibility in AI-driven search results, leading to higher engagement and conversion rates. This approach is a key component of modern SEO and digital marketing strategies.

Is AI Referral Traffic Big Enough to Care About Yet?

This is where honest practitioners need to resist hype in both directions.

AI referral traffic is growing rapidly. It’s something you should care about right now. In Similarweb’s 2025 Generative AI Report for June 2025, it was reported that the top 1,000 websites received a total of 1.13 billion AI referral visits, up a massive 357% year-over-year. According to Adobe Digital Insights, for the period October 2024 – December 2025, AI-influenced shopping conversions were 38% higher on Black Friday compared to non-AI-driven conversions in the report.

However, Google Search referral traffic is many orders of magnitude larger than the AI traffic reported above. Thus, GEO vs SEO (geographic search) or “traditional organic search” is not going anywhere – fast. As was mentioned above, in order to win at marketing in 2026 one will need to be adept at marketing within each of the various channels (or layers) that make up the overall marketing mix and develop effective strategies for driving traffic and converting customers within each of them. Treat all of these channels as if they were one (i.e. GEO) and that marketing professional would be making a monumental mistake.

Don’t however confuse SEO for traditional organic search with the new GEO (Generative Output) that’s being developed in AI systems. The two systems are interlinked and the ranking and quality signals for organic search in Google are the same as for the source ranking in AI systems. Thus, until you have done a complete SEO audit and have fixed any problems with your site’s authority, content etc, you should not also be spending time trying to optimize for GEO.

In summary, AI Referral Traffic is a large and growing channel that merits the attention of practitioners and researchers alike. As can be seen in the figures above, Similarweb reported 1.13 billion AI Referral Visits to the top 1,000 websites in June 2025, a 357% year-over-the-year increase. These visits form high-intent traffic and as such, are a channel worthy of your time. Make sure to set up your source/medium channels for Referrals from AI interfaces such as ChatGPT, Perplexity, and Gemini and measure engagement, such as engagement rate, average engagement, average session length, and conversion rates for sessions that originated from AI Referral Traffic.

Understanding the nuances of GEO vs SEO is essential for modern SEO and digital marketing strategies. Brands must learn to optimize content for Google AI overviews while maintaining strong traditional SEO practices to ensure visibility across all stages of the decision making process.

The Crawl-to-Click Gap — A Technical Problem You Might Be Ignoring

While the press continues to debate “GEO” (Generative Enterprise Outputs) — marketing in AI — on the technical side of the house there is far more interesting material to discuss, for example the interface of AI “bots” with web content.

Cloudflare’s recent article on AI ‘Bots’ covers a number of topics that are also relevant to the area of Search. In particular it looks at the growing ‘Crawl-to-Click Gap’ – or in simple terms the amount of content that AI ‘Bots’ are now reading vs the amount of referral traffic that they generate as a result. In a recent analysis covering the period from January to the end of July 2025 the company found that the largest proportion of activity by AI ‘Bots’ was now training – currently standing at 78% (up from 72% in the previous year). In practical terms, this means that most of the activity from AI ‘Bots’ that crawl a website are not actually referring to that site in the analytics package. As a result, those involved in Search need to carefully consider the trade-offs involved here. Allowing uncontrolled access by ‘Bots’ in order to allow for the possibility of content being used in AI generated answers in search, could have negative effects on a websites performance in terms of server load etc. While blocking all ‘Bots’ could mean that a site is never cited in AI generated answers in search. Those involved in Search therefore need to consider these types of trade-offs and make a decision based on their goals and then instrument accordingly.

There are new challenges for brands to allow access to their content whilst wanting to try and get included in the AI generated answers. As well as distinguishing between human sessions that have come via AI referral and pure AI bot crawling activity. This can cause problems if not instrumented correctly and could cause the engagement rate to be skewed.

Imperva's 2026 Bad Bot Report outlines in more detail how automated traffic is dominating the majority of total web traffic. So it is crucial to distinguish the numbers for your AI referral performance from those of your AI bot traffic. For example, BusySeed reported a very successful case study for the generation of healthcare leads by way of AI referrals in which the engagement rate for all of the human sessions that were referred by means of AI was 65% and above.

Understanding the crawl-to-click gap is essential for brands looking to optimize content for Google AI overviews. This technical challenge highlights the importance of balancing AI bot access with server performance to ensure that content remains visible in AI-driven search results. This is a key consideration in modern SEO and digital marketing strategies.

Traditional SEO vs. AI Visibility: A Direct Comparison

This comparison highlights the key differences between GEO vs SEO and the importance of understanding both to effectively optimize content for Google AI overviews. Brands must adapt their SEO and digital marketing strategies to account for these differences, ensuring visibility across all stages of the decision making process.

2026 Dual-Visibility Action Plan for Your Business

1. Audit your current AI citation status. Run your brand's core topic areas through ChatGPT, Perplexity, and Google AI Mode. Document where you appear, where competitors appear, and what sources the AI is citing. This is your gap analysis.
2. Restructure your most important content pages for extractability. If you have information that is going to remain relevant for a year or more, you will want to ensure that your content can be extracted properly. This means adding a number of features including: definition-based blocks of content; step-by-step process descriptions; and comparison information organized in tables with clear column headings. The models are able to extract and use information that is found in these formats best of all, so you should make sure that every important page of content on your site has at least one section that a model can use directly to answer questions that you have not even asked yet.
3. Strengthen your author and entity signals. While you can’t control how a buyer discovers you, you can control what they see when they do discover you. The author bios on your website should list out the credentials of the author of the piece of content that the buyer found. This is especially important if you have contractors or freelancers writing for your company. Including methodology behind research-based content, including update timestamps and change logs on pages that have been updated, will also show AI systems the rigor of .gov and .edu sites that are over-represented in AI Overviews.
4. Map your content to early-funnel conversational queries. Work with your top SEO keywords and then expand them into long-tail multi-word questions that a language model would summarize for you. 53% of searches for 10+ words triggered an AI Overview, according to Pew Research Center. Create content that addresses the longer queries that are triggered for summaries by early-funnel conversational queries.
5. Track your AI referrals in GA4 before you start optimizing for them. Set up your GA4 property and create a filter in the Sessions report for Session Source/Medium equals “AI & Chat” (this will include traffic from ChatGPT, Perplexity, Gemini, etc. as well as other generative AI services). You can then add a secondary dimension to the report (such as Engagement Rate) and create a comparison between the pre-optimization performance of your AI referring site(s) and their post-optimization performance. This will give you a much clearer sense of whether your efforts to make your content more citation-ready are having any actual impact on how that traffic behaves on your site.
6. Align SEO and content teams around citation-readiness as a shared KPI. This is the biggest disconnect in the industry today. The typical divide between SEO technicians and content strategists does not work when the goal of both teams is to create AI-citation- ready content.
7. Build trust signals for search quality and AI reliability, information that search engines consider to be of high quality and that AI systems can verify to be accurate and reliable. NIST’s GenAI Risk Management Framework provides a framework for assessing risks for GenAI and developing strategies for mitigating those risks. A primary strategy for mitigating risks is to ensure that information is of high quality and that a clear audit trail exists for how information was gathered and verified. One way to build such trust signals is to publish verifiable information that has been reviewed by an expert, such that the information is of high quality and the brand is a “safe source” for the AI system to cite.
8. Separate AI bot crawling from human AI referrals in your analytics and server logs while you monitor for instances of AI bot crawling such as to protect your data integrity during high crawl rates, ensure that your analytics and server logs can correctly identify bot traffic and, in the case of high levels of referral traffic from AI models, track levels of engagement from human users who have been referred from a AI model.

This action plan provides a comprehensive approach to navigating the complexities of GEO vs SEO and effectively optimizing content for both traditional search and AI-driven discovery. By following these steps, brands can enhance their visibility across all stages of the decision making process and improve their SEO and digital marketing strategies.

Frequently Asked Questions

How to optimize a website for AI search without abandoning traditional SEO?

One example for optimizing a website for search in AI search engines (like ChatGPT etc) would be to restructure the most important information on a website to make it more extractable for AI models. For instance, adding a definition for a term that is explained on a page with high ranking in search engines, a step by step explanation for processes that are described on that page, a comparison table for items that are compared on that page, etc. The restructured content should have a section that a language model can quote directly in order to answer a longer query that the model would typically summarize in an AI Overview in order to trigger a click on a link to that page in order to read more. This approach ensures that your content remains effective for both traditional SEO and AI-driven search, aligning with the principles of user intent SEO and the need to optimize content for Google AI overviews.

What makes a digital marketing agency in New York City worth hiring for AI visibility in 2026?

Be very wary of SEO companies calling themselves “AI SEO companies” and promise to optimize for GEO in order to get you higher visibility. While GEO optimization is basically SEO speak for “optimizing for generative AI to list you out” there is a huge difference between GEO vs SEO. If an agency can’t explain how to track referrals from AI in GA4 (separate from organic referrals), how to even find all the places that you’re being cited for in AI in the first place, and most importantly how to modify a page to increase extractability of information then what they are really selling you is standard SEO and nothing more. This is why we put together a digital marketing services page that goes over in great detail our approach at BusySeed to drive massive amounts of results for our clients. In order to drive massive amounts of results, we have to understand how to measure things in the first place. And in terms of AI generated Search Engine Results Pages, we have a very good understanding of what makes them tick after recently completing a health care SEO case study in which we not only created a lot of AI citations, but also engendered 65%+ or more engagement per channel pre and post for the client.

When evaluating marketing agencies in New York City, it’s essential to look for those that understand the nuances of SEO and digital marketing in the context of AI-driven search. The best digital marketing agency in NYC will have a proven track record of helping clients optimize content for Google AI overviews while maintaining strong traditional SEO practices.

How do AI Overviews affect organic click-through rates, and should I be worried?

Seer studied the effect of AI Overviews on Google Organic Click-Through-Rates in September 2025. They discovered that when an AI Overview is present in search results and a brand is not cited in the AI Overview summary, organic click-through-rates fall to 0.52% or a decline of 65.2% year-over-year. They also found that when a brand is cited in an AI Overview summary, organic click-through-rates fall to 0.70% or a decline of 49.4% year-over-year. But there’s also good news here: Brands that are cited in AI Overviews for a given search query earn 35% more organic clicks than brands that are not cited in AI Overviews for the same search query. Thus, the biggest problem that a brand needs to solve is getting cited in AI Overviews in the first place.

This data underscores the importance of understanding GEO vs SEO and the need to optimize content for Google AI overviews. Brands must adapt their SEO and digital marketing strategies to ensure visibility in AI-driven search results, which can significantly impact organic click-through rates and the overall decision making process of buyers.

What's the real difference between GEO vs SEO — aren't they the same thing?

Although the methodologies to achieving visibility are similar, GEO vs SEO have many differences. GEO and SEO can be approached from two different perspectives. For one, SEO focuses on optimizing content for rankings and Click-Through-Rates (CTRs) of organic listings in search results. The type of queries that are typically used for such searches are usually long-tail queries that relate to the information of a buyer who is already in the middle to late stages of a research process into information to compare vendors, prices, and products and services related to a problem that the buyer is trying to solve. On the other hand, GEO focuses on getting a brand to be visible for a buyer in the early stages of a research process for information related to a problem that the buyer is trying to solve. The type of queries that are typically used for such searches are usually short-tail queries. A brand’s content that is optimized for GEO purposes is therefore focused on extractability. For this reason, a brand’s content that is optimized for GEO purposes can also be used for SEO, but the opposite is not necessarily true. In order to measure the success of a brand’s SEO efforts, rankings and CTRs can be used as indicators. In order to measure the success of a brand’s GEO efforts, the frequency with which a brand’s content is cited as well as the engagement rate of referrals from AI to traditional web pages can be used as indicators.

Understanding the differences between GEO vs SEO is crucial for modern SEO and digital marketing strategies. Brands must learn to optimize content for Google AI overviews while maintaining strong traditional SEO practices to ensure visibility across all stages of the decision making process.

How do marketing agencies in New York City approach the 2026 SEO shift for competitive industries like healthcare?

The most competitive industries such as finance, healthcare and law have the biggest opportunity to reach people through the AI visibility shift. The reason is simple: these types of sources are trusted by people the most. According to a Pew Research Center report from July 2025, published online summaries or AI Overviews in Google results contain .gov sources 6% of the time. This is up from 2% of the time in regular Google results. For .edu sources, the frequency rose to 3% from 2%. For hospitals and health systems that are publishing large amounts of high quality content, the biggest source of trust signals is content that has visible author credentials and is primarily sourced. Other items to consider for trust signals are a clear methodology or explanation of how the content was developed and updated regularly. These are the types of signals that can be leveraged by agencies in competitive verticals to increase the chances that a brand will be cited in AI generated answers.

When looking to hire digital marketing agency New York 2026, it’s essential to choose one that understands the unique challenges and opportunities of competitive industries like healthcare. The best marketing agencies in New York City will have a proven track record of helping clients in these industries optimize content for Google AI overviews and navigate the complexities of GEO vs SEO. This expertise is crucial for enhancing visibility and driving results in the evolving landscape of SEO and digital marketing.

Works Cited

Adobe Digital Insights. "AI-Influenced Shopping Conversions Report." October 2024 – December 2025.

Cloudflare. "AI Bots and the Crawl-to-Click Gap." 2025.

Google. "AI Optimization Guide." https://developers.google.com/search/docs/fundamentals/ai-optimization-guide. 2025.

Google. "Succeeding in AI Search." https://developers.google.com/search/blog/2025/05/succeeding-in-ai-search. May 2025.

Imperva. "Bad Bot Report 2026: Bots in the Agentic Age." https://www.imperva.com/blog/bad-bot-report-2026-bots-agentic-age/. 2026.

Pew Research Center. "Google Users, Links, and AI Summaries." March 2025.

Pew Research Center. "Search Query Length and AI Overviews." 2025.

Seer Interactive. "The Massive Influence of the AIO (AI Overview) on the Google CTR of Organic Results." June 2024 – September 2025.

Similarweb. "2025 Generative AI Report." June 2025.

SparkToro. "In 2026, Less Than One-Third of Google Searches Still Send a Click." https://sparktoro.com/blog/in-2026-less-than-one-third-of-google-searches-still-send-a-click/. 2026.