Some search marketers have been declaring SEO dead for over a decade. Yet every year, search keeps driving brand discovery and revenue.
What has changed is how visibility works. Google’s AI Overviews summarize answers before users click, and generative engines talk about the brand inside responses. Search behavior now also spreads across YouTube, LinkedIn, marketplaces, and AI platforms.
Now, we aren’t gaslighting you—we are also seeing the declining click-through rates and unstable traffic that were so different just five years ago. When people ask, “Is SEO dead?” they’re reacting to something very real, and it’s affecting industries across the board.
But SEO is not dead or even dying. Like most things being affected by technology and digital initiatives, SEO is simply changing. Technical excellence, authoritative content, and visibility across systems is still essential. Now, you just need to optimize for AI systems and search platforms, too.
The biggest shift is the rise of AI-generated answers directly in search results. Google’s AI Overviews and generative engines can summarize information before a user ever clicks a page. In many cases, the search experience ends right there on the results page. When teams see traffic dip even though rankings remain strong, it naturally sparks concern about the long-term value of SEO.
At the same time, search itself is no longer confined to Google. People discover products on Amazon, research ideas on YouTube, ask questions inside AI tools, and follow recommendations from LinkedIn or Reddit threads. That fragmentation means visibility is happening across a wider ecosystem than traditional search analytics tools were built to track. For a lot of businesses, it can feel like you have no control over so many channels.
Those two forces together have created real volatility in organic traffic. If you have historically measured SEO success only through clicks and sessions, these changes can feel like the ground moving underneath your entire strategy.
For brands willing to adapt, the opportunity is still massive. Strong search visibility now depends on building authority, technical clarity, and content that AI systems trust as a source. That kind of SEO strategy sits at the center of modern search growth.
The phrase “is SEO dead” is what marketers are saying when they see declining organic clicks and evolving search interfaces that don’t seem as compatible with classic SEO. AI-generated summaries, knowledge panels, and expanded SERP features often deliver answers before users reach a website, so why should businesses bother with SEO?
But this evolution of search optimization has not necessarily lost its relevance. In fact, all it really means is that the role of SEO has expanded. Instead of focusing exclusively on ranking individual pages, your strategy should heavily focus on building authority and structured visibility across search and AI ecosystems.
A few patterns tend to fuel the idea that SEO is disappearing:
Remember that, ultimately, organic search remains one of the strongest discovery channels on the internet. High-intent queries flood search engines every day that drive your revenue. People still rely on search to solve problems and evaluate options, and your brand needs to show up in those results.
Enterprise organizations still invest heavily in search because it contributes directly to their pipeline growth. As you become an authority in your space (rather than focusing so heavily on ranking), and have technical, structured content performance, your visibility will increase.
For years, SEO success looked fairly straightforward, but there are a couple of other players on the field.
Traditional SEO says that success looks like top rankings and organic traffic. If your page appeared near the top of search results, the assumption was that clicks and engagement would follow.
Meanwhile, AI Overviews and generative systems increasingly pull answers from multiple sources. When that happens, business influence shows up through citations, summaries, and brand mentions inside those responses.
In other words, when AI search systems generate answers, they rely on sources they trust. If your content becomes one of those sources, your brand shows up in the answer itself—even when the user doesn’t click.
“SEO” is also one slice of a much larger pie, where AEO and GEO are a part of a well-rounded strategy.
Answer Engine Optimization, or AEO, focuses on structuring content so search systems can extract clear answers. Generative Engine Optimization, commonly referred to as GEO, looks at how AI platforms summarize and reference sources. Both ideas reflect the same larger trend: search engines are becoming answer engines.
Modern SEO strategies bring these concepts together. Instead of separating them, organizations combine traditional ranking strategies with content structures designed for AI summarization and entity clarity. This approach is how you can be at the top of your game with AI search and how to optimize for the future of search engines.
Another major change is where discovery happens. Search behavior no longer lives inside a single engine.
Someone researching a product might start with a Google query, watch comparison videos on YouTube, scan reviews on marketplaces, and read thought leadership on LinkedIn. Users also ask questions inside AI assistants before visiting a website.
Brands that want consistent visibility build authority across multiple ecosystems where search intent appears. So yes, you need to optimize for Google—that’s not going anywhere. But you also need to show up where people compare products or services and ask questions. That might mean:
That broader presence strengthens the signals search engines and AI systems rely on when deciding which sources to surface. Over time, those signals reinforce brand authority in ways that pure keyword targeting never could.
Featured snippets started this trend years ago: search engines want to answer the question in the search bar without ever even visiting a website. Now, AI Overviews are taking it a step further.
Because more queries are answered directly in SERPs, AI Overviews have reduced the reliance on blue links for consumers—your audience.
So why are you pouring money into producing so much content for people to not even enter your website?
Because traffic declining does not necessarily mean your influence declines, too.
When your brand appears inside an AI Overview, a featured snippet, or a cited source within a generated answer, users still see your expertise. They may not click in that moment, but the exposure shapes awareness and credibility. Later, when they search again with a stronger intent, your brand is already familiar.
Instead of focusing exclusively on traffic, many organizations now look at a broader set of indicators:
The zero-click environment also forces some strategic decisions.
Chasing raw traffic can lead teams to prioritize high-volume informational queries that rarely convert. Meanwhile, focusing on authority and expertise often produces fewer visits but better downstream impact.
Enterprise organizations increasingly balance both sides of that equation. They invest in content that builds authority within a category while also strengthening owned channels like email, communities, and product education hubs.
Building authority earlier in the research process also helps teams connect search visibility to revenue attribution models, which track how organic discovery contributes to pipeline and closed deals.
We know that the technical side of SEO especially matters, but more than ever before, so does the human element of your content. Generic or recycled material just doesn’t quite cut it anymore. It’s your expertise and credibility that the AI models are going to trust.
Google describes these signals through E-E-A-T: experience, expertise, authority, and trust. This is exactly what it sounds like: search systems try to surface information that comes from knowledgeable sources.
AI-generated answers rely on the same signals. When models summarize content, they still look for sources that demonstrate real-world expertise and established authority within a topic area.
That’s why enterprise brands with recognizable subject matter experts, credible research, and original, real-world insights tend to perform well over time. They give search engines and AI systems a clear signal that their content is worth referencing.
Keywords do still matter, but even more important is writing for readers. Answer the search intent before you optimize for the algorithm to give yourself the best chance in AI search and future search strategies. This looks like having clearer explanations on the topic and practical solutions that actually help consumers make their decisions. Remember to:
Human-first content thrives when it’s supported by broader SEO principles. Successful organizations treat search visibility as a combination of these 6 disciplines of SEO working together.
If a site is difficult to crawl, poorly structured, or confusing to interpret, even great content struggles to appear consistently in search results. Think of it like building a library. You could fill it with incredible books, but if the shelves are disorganized and the catalog is missing, people will have a hard time finding anything.
Before a page can rank or appear inside an AI-generated answer, search engines have to find it and understand how it fits with the rest of your site.
That usually comes down to a few practical things:
When those fundamentals are in place, search engines have a clearer picture of what a site covers and which pages provide valuable answers.
Search engines are good at reading pages, but they still appreciate a little help.
Structured data acts like labels on a library shelf. It tells search systems exactly what they’re looking at. Product schema can identify price and availability. FAQ schema highlights clear question-and-answer sections. Review schema points to customer feedback.
Those labels help search engines surface the right information in rich results and AI-generated answers.
Entity relationships add another layer. When your brand consistently appears alongside certain topics across trusted sites, search engines begin to connect the dots. Over time, your brand becomes associated with that subject area, which makes it more likely to appear when people search for related information.
For enterprise organizations, technical SEO becomes even more interesting. Large websites often contain thousands or even millions of pages across different products, regions, and content hubs.
At that scale, small issues multiply quickly. Duplicate pages compete with each other. Important sections become buried several clicks deep. Old pages stick around long after they stop providing value.
That’s why enterprise SEO often requires governance systems and technical enterprise SEO playbooks that keep large sites organized. Without that structure, even strong content can struggle to gain traction in search.
You see a lot of the trending “SEO solutions” on your LinkedIn feed, but what is really going to move the needle? Let’s talk about it.
One of the biggest changes in modern SEO is the move away from pure volume. Today, that approach rarely produces lasting results. Search systems have become much better at identifying which sources actually demonstrate expertise within a topic.
That’s why many organizations now focus on building strong topic clusters around high-intent themes. Instead of publishing dozens of loosely related pages, they develop deeper resources that connect logically and answer related questions across the research journey.
The goal of these evolving SEO strategies is simple: become one of the sources search engines consistently associate with a category. That kind of authority tends to hold up far better than isolated rankings.
AI-generated answers have added another layer to modern AI SEO strategy.
Content now needs to be clear enough for AI systems to extract and summarize. Pages that explain ideas directly, use structured formatting, and answer questions clearly are more likely to appear in generated responses.
This often means writing in a more conversational, question-driven format. When a page mirrors the way people naturally ask questions, it becomes easier for AI systems to recognize and reference the information.
Ecommerce brands face a slightly different set of priorities.
Product pages need structured data that clearly communicates details like price, availability, reviews, and product attributes. Category pages often carry the responsibility of establishing topical authority for entire product groups.
At the same time, ecommerce SEO must compete within crowded SERPs filled with product listings, reviews, and comparison content. Brands that succeed often combine strong technical optimization with helpful buying guides, comparison pages, and educational resources that support the purchasing journey.
There are a lot of moving pieces to SEO now, and many organizations reach a point when their internal teams need help. This often happens when:
Working with a specialized team focused on AI-driven search can help organizations move faster while maintaining a clear strategic direction, which is why many brands explore working with an AI SEO agency.
By this point, one thing should be clear: modern SEO isn’t a checklist, but an entire system of connected strategies that all influence one another. When those elements operate in isolation, results tend to plateau. When they work together, search becomes a much more durable growth channel. 97th Floor is here to make sure every move you make is contributing to a healthy and modern SEO strategy.
97th Floor approaches SEO as a growth system rather than a content production engine. The strategy connects traditional search optimization with authority building, digital PR, and AI search visibility.
We can help you rank for keywords, but we also help your brand become a leading resource in your industry. Instead of chasing short-term ranking spikes, the focus moves toward durable visibility that supports sustained growth.
97th Floor focuses on building content systems and authority frameworks that continue performing even as search interfaces change. Search will keep evolving. How will your team keep up? Every algorithm update can work to your benefit as we help you master long-term authority and move beyond obsessive keyword ranking.
Let’s assess where your organization currently stands and see where you can start making changes for today’s SEO environment.
Start by looking at how your organization defines SEO success. The way performance is measured often shapes the entire strategy.
Next, take a close look at the technical foundation of your site:
Finally, consider how your brand appears compared to others in your category. Visibility gaps often become obvious when you look at where competitors show up in search and AI answers:
If these questions highlight opportunities for improvement, it may be time to revisit your SEO strategy. The search landscape is evolving quickly, and adapting early can make a significant difference in long-term visibility. Learn more about how our team approaches search strategy through our SEO services.
A few years ago, ranking on page one felt like the finish line. If your page showed up near the top, traffic followed.
Now, being at the top of SERPs is valuable, but it doesn’t pack the same punch. When you ask a complicated question, the search engine often answers it immediately. AI Overviews summarize sources, or generative engines simply write explanations. In many cases, the user never clicks a link at all.
As a brand trying to gain visibility with your consumers, this change in search results affects how you approach. Pages still matter, but the real opportunity now is becoming one of the sources AI systems rely on when they generate answers.
Answer engine optimization is a large piece of that puzzle, which focuses on how content gets extracted and referenced inside AI responses. In this guide, we’ll show you how answer engine optimization fits into your overall AI search strategy and how to show up in relevant online spaces.
When AI systems generate a response, they choose a handful of sources to build that answer. If your brand is one of those sources, your expertise shows up immediately. If it isn’t, competitors shape the narrative instead.
Decision-makers are asking longer, more contextual questions than they used to. It’s less short phrases like “CRM tools,” and more questions about how a CRM integrates with existing systems or which platforms work best for a specific business model. These often appear during real evaluation cycles, which means the answers influence purchasing decisions.
Because of that shift, the goal of search strategy is expanding. Ranking still matters, but influence now depends on whether AI systems trust your content enough to extract it as a direct answer.
Answer engine optimization is one of the ways you can make your content more visible under these new search conditions. AEO focuses on structuring expertise so AI systems can interpret it clearly and reference it when generating responses. Many teams now integrate AEO alongside traditional optimization, authority development, and technical SEO as part of a largerAI search strategy.
Over time, brands that consistently appear in AI answers gain an advantage that rankings alone cannot provide. Their expertise shapes the information buyers see at the very beginning of research.
That advantage starts earlier than most brands realize — at the moment a buyer types their very first query. SEO expert Eli Schwartz reveals what today's AI-aware searchers are actually typing into Google, and why those queries look nothing like what most content teams are optimizing for. This short video breaks down the search behavior shift that determines whether your brand shows up at the start of the research cycle — or gets skipped entirely.
When someone asks an AI system a question, it doesn’t search the web the same way a person does. It analyzes sources, pulls relevant information, and generates a response.
Answer engine optimization focuses on influencing which sources that response comes from.
Answer engine optimization is the practice of structuring and validating content so AI systems recognize it as a reliable answer to a specific question.
Instead of optimizing only for rankings, AEO focuses on how information is interpreted by AI systems. That includes how clearly a concept is defined, how expertise is demonstrated, and how easily an answer can be extracted.
The objective is representation. When AI systems summarize a topic, the brands cited in that answer help shape how buyers understand the category.
Traditional SEO and answer engine optimization address different layers of search visibility.
| SEO | AEO |
| Focuses on ranking pages in search results | Focuses on being extracted, summarized, or cited in AI responses |
| Optimizes for keywords and backlinks | Optimizes for questions, structured answers, authority signals, and machine-readable clarity |
| Performance is measured in clicks | Performance includes visibility within AI answers, brand mentions, and authoritative citations |
For most organizations, AEO complements traditional SEO since you still need SEO to rank—now, you are more deeply considering how your brand appears in AI-generated explanations.
Content optimized for answer engines typically follows a simple structure.
Start with a question that reflects how people actually search. Place a concise explanation directly beneath it, usually 40 to 60 words. Then expand with supporting context, examples, or strategic insights, especially when you can back up your ideas and claims with real experience. You also need to cut back on ambiguity wherever possible.
That format makes it easier for AI systems to identify the core explanation quickly while still giving readers the deeper context they need.
AEO works best when it’s built into how content is planned and structured from the beginning. Teams that try to retrofit answer visibility after publishing usually find the results inconsistent. Meanwhile, when you have a solid architecture from the beginning, you can design pages around the kinds of questions buyers actually ask and make it work for the digital world.
AEO content planning usually begins with mapping the questions buyers actually ask during research. These are usually the “what is,” “how does,” and “why does” questions.
For example, a software company might map queries like:
Each of those questions becomes a distinct section with a clear answer followed by deeper explanation. You can make sure you are covering topics with enough depth by using semantic clusters, which are groups of closely related questions and subtopics that help search systems understand the full scope of a topic.
This structure does two important things. First, it mirrors how buyers research a topic. Second, it gives AI systems clearly defined answers they can extract without needing to interpret a long block of text.
Answer engines rely heavily on structured information to interpret content. Structured data provides that clarity by labeling important elements on a page so machines can understand them more easily.
Schema markup helps identify things like the organization publishing the content, the author responsible for the expertise, frequently asked questions within the page, and relationships between related topics. This added context helps search systems interpret who is providing the information and what the page is about.
For example, a consulting firm publishing a guide about marketing attribution could use schema to define the organization, the author’s professional role, and the FAQ sections within the article.
When those elements are clearly labeled, AI systems have a much easier time interpreting the page and connecting the expertise behind it to the topic being discussed.
Answer engines prioritize sources that demonstrate credible expertise. Google refers to these credibility indicators as E-E-A-T: experience, expertise, authority, and trust.
In practice, this means content should reflect real knowledge of the subject. Generic definitions only get you so far — strong AEO content includes insights drawn from actual work, industry experience, or original analysis.
For example, a cybersecurity firm writing about threat detection might reference internal research or share examples from real client engagements.
These types of details signal that the organization understands the topic in practice. Over time, consistent publication of this kind of expertise helps AI systems associate the brand with authority in that subject area.
Answer engines interpret questions the way people naturally ask them. That means content often performs better when it reflects natural language instead of rigid keyword phrasing.
For example, someone researching marketing attribution might ask:
Structuring sections around questions like these helps AI systems match your content with real user queries.
Strong AEO content also anticipates follow-up questions. A page explaining marketing attribution might include sections about data accuracy, implementation complexity, or how attribution influences budget decisions.
Connecting those related ideas helps search systems understand the topic more completely and reduces fragmentation across multiple pages.
Clear hierarchy also matters. Question-based headings followed by concise explanations make it easier for AI systems to summarize or extract specific sections when generating answers.
Answer engine optimization focuses on preparing content for the process of assembling responses from credible sources and summarizing it for the user. When information is structured clearly and supported by credible expertise, AI systems have an easier time referencing it while generating answers.
Content that appears inside AI-generated responses usually follows a predictable structure. It explains a concept clearly, avoids filler, and provides enough supporting context for the system to validate the information.
If you want to understand how to optimize content for generative AI, begin sections with a concise explanation of the topic, followed by examples, data, or deeper analysis that reinforces the credibility of the answer.
For example, a page explaining marketing attribution might begin with a definition, then expand into implementation considerations, measurement challenges, and how attribution influences budget decisions. Structuring content this way makes it easier for AI systems to extract the core explanation while still giving readers useful context.
Let us say it again: answer engine optimization works best when it supports a broader search strategy. It’s a core pillar, but it isn’t the whole coliseum of AI search SEO.
AEO focuses on how answers are structured and interpreted. Traditional SEO still influences how pages are discovered and how authority develops around a topic. When both approaches work together, brands are more likely to appear during the research stages where buyers gather information.
A company building authority around marketing analytics might publish in-depth resources on attribution models and data integration strategies. Over time, that connected coverage strengthens the brand’s association with marketing measurement.
Generative search does not exist on a single platform, either. AI Overviews, Perplexity, and other answer engines each generate responses differently.
Because of that variation, it helps to monitor how your brand appears across these environments. Some platforms may reference your research frequently, while others rely on different sources when generating answers.
A company might discover that its insights appear regularly in one AI platform but rarely in another—maybe they need to improve visibility on Perplexity. Observations like that can reveal gaps in how expertise is structured or referenced across the web, which becomes clearer when examining how brands appear in systems like Perplexity’s search engine and browser.
So, how do you actually evaluate whether your content is positioned to appear in AI answers? This is where the right tools can make all the difference.
AEO tools typically analyze how well content aligns with the structures AI systems rely on when generating answers.
One common area is entity clarity. Tools look at how consistently a brand, topic, or product appears across pages and whether the relationships between those entities are clearly defined. If your company publishes content about multiple services, for example, these tools help determine whether those services are clearly connected to your brand and expertise.
Another area is semantic coverage. Platforms often evaluate whether a topic includes the related questions and supporting explanations that give AI systems enough context to understand the subject. A page explaining marketing attribution might also need sections about attribution models, implementation challenges, and reporting accuracy for the topic to feel complete.
Many tools also examine question-to-answer structure. This includes identifying whether pages contain clearly defined explanations that AI systems can extract without needing to interpret long paragraphs.
Finally, platforms often review authority indicators such as citations, references, and how often your content appears across relevant sources on the web.
Not every platform labeled as an AEO tool is built for enterprise teams. Many focus on content analysis alone, which can leave large organizations without visibility into the broader search ecosystem.
When evaluating answer engine optimization platforms, look out for these capabilities especially.
The best platforms provide actual, actionable information on how AI systems interpret your expertise rather than simply pointing out missing keywords.
Tools can show you important gaps, but they rarely solve the strategic challenge on their own.
Answer engine optimization requires coordination across several departments. Content teams shape the explanations AI systems extract. Technical teams manage structured data and site architecture. Digital PR and communications teams strengthen authority across the web.
Without that coordination, even the best tooling will only surface problems rather than help solve them.
Over time, the organizations that succeed with AEO treat tools as diagnostic support while focusing most of their effort on building authority and expertise.
By the time most organizations start exploring answer engine optimization, they’ve already noticed something unusual in their search data since AI systems are taking the lead.
At 97th Floor, answer engine optimization isn’t treated as a standalone tactic. It’s integrated into a broader shift toward AI-driven search, where content structure, authority, and technical clarity all influence how a brand shows up online.
Enterprise organizations rarely struggle with producing content. The challenge is aligning that content so it reinforces expertise across a category.
That alignment requires several moving parts working together. Content needs to answer the right questions. Technical teams need to support structured data and site architecture. Digital PR helps strengthen authority signals across the web. We make sure all of your best people and AEO efforts actually work together and make progress.
AEO should never be measured by visibility alone. What matters is whether that visibility influences the conversations buyers are having when they research a category.
At 97th Floor, answer visibility is connected to the areas that actually drive revenue. Content is structured so AI-generated answers reference the topics that matter most to the organization’s services and solutions.
Over time, this approach shifts the goal of AEO from general awareness to category influence. When buyers encounter explanations that consistently reference your expertise, your brand becomes part of how they understand the problem itself.
Search will continue evolving as AI platforms mature. New answer engines will emerge, and existing platforms will refine how they interpret and summarize information. That’s why strong AEO strategies focus on building durable authority rather than chasing short-term optimization tactics.
Are you ready to shift into a new gear with answer engine optimization? Here are some questions you can ask yourself to know if it’s time.
Answer engine optimization often requires teams to rethink how search visibility is measured and managed.
Start by looking at how your organization currently approaches search.
These conversations usually surface quickly whether AEO can be implemented smoothly or whether internal alignment still needs work.
The next step is examining whether your existing content can actually support answer visibility. Key questions to review include:
Finally, it helps to look outward.
In many industries, answer engines already reference certain organizations repeatedly when explaining a topic. Those brands effectively shape how buyers learn about the category. Ask yourself:
These observations often reveal whether your brand is currently influencing the conversation or watching it happen from the sidelines.
If these questions surface opportunities, it may be time to develop a structured AEO strategy.
At 97th Floor, answer engine optimization is approached as part of a broader AI search transformation that connects technical SEO, authority development, and content strategy. Organizations exploring how to improve their answer visibility often begin by examining how their content aligns with modern search strategies.Discover how we can help you in the new age of AI search!
SEO is changing.
Oh, you’ve heard that one before? It’s true; SEO has been many things in the twenty or so years that it’s been around, but static has never been one of them. What began with simple keyword stuffing and quantity-over-quality link building has evolved into a deeply strategic and data-centric discipline — one that prioritizes intent over tricks, clarity over cleverness, and exploration over exploitation. So, yeah SEO is changing and always has been. But 2026 hits a little differently.
This new year is the dawn of a new era. Search is no longer just a list of links politely waiting for users to click them. It’s answers, summaries, recommendations, and increasingly confident machines stepping in as intermediaries to decide whether your content deserves to exist at all. AI-driven search is adding a new and somewhat unforgiving layer to SEO. It’s not an entirely new game; traditional ranking factors still matter, it’s just that they don’t carry the same weight they once did. And that changes what it means to be visible.
Simply put, the rules of SEO have evolved, and the brands that adapt to meet these changes will come out on top.
The biggest shift is in where and how those changes are showing up:
Which brings us to the inevitable question: If SEO now depends on how content is interpreted (rather than simply ranked), where does that leave the growing pile of labels we use to describe it?
The SEO lexicon is growing: Generative engine optimization (GEO), Search Everywhere, AI Search Optimization (AIO)... It’s a whole new world of terminology. And don’t you dare close your eyes, because these terms are symptomatic of how search itself now operates across more systems than a traditional SERP ever could.
Modern visibility includes rankings, citations, summaries, and recommendations that appear across AI tools, discovery platforms, and search-adjacent environments. Evolving SEO strategies account for all of these surfaces by focusing on interpretability, credibility, and usefulness at scale.
So, whether we’re talking about SEO or GEO, we’re ultimately describing the same responsibility: ensuring that your content can be found, understood, trusted, and reused wherever search behavior shows up.
And wouldn’t you know it? In 2026, that responsibility extends beyond ranking signals and into how information is structured, contextualized, and validated across systems that are increasingly taking on the role of interpreters. Strategy lives in the connective tissue — how ideas relate, how authority is demonstrated, and how consistently value is delivered across touchpoints.
Labels will keep changing. The underlying work remains focused on building visibility that travels well and earns its place wherever discovery happens.
But "wherever discovery happens" increasingly includes systems that surface answers very differently than a traditional SERP — and those differences aren't cosmetic. Blake, Account Director at 97th Floor, takes on the question every SEO team is quietly wrestling with: is AI search a meaningful shift or just the next version of the same game? His answer cuts through the noise with a practical lens on what actually changes and what stays the same. This short video breaks down the real distinction between traditional search and AI search — and what it means for how you build visibility today.
Have we belaboured the point enough? If not, let’s just come right out and say it. 2026 isn’t being defined by a single update, tool, or announcement. What’s changing is the environment in which search operates and the expectations placed on the content that moves through it. Search marketers now operate in a space where content gets evaluated repeatedly — by users, by traditional search systems, and by AI-driven interfaces that summarize, filter, and recommend information at scale. That layered evaluation changes where effort pays off and where shortcuts tend to collapse.
Let’s take a look at the most consistent pressure points shaping evolving SEO strategies this year:
When it comes to AI search, generative systems interact with content very differently than traditional crawlers. Instead of indexing pages and ranking them in isolation, they ingest large volumes of information, identify relationships between concepts, and reconstruct answers dynamically.
That process places real weight on how content is constructed. Definitions that arrive early, terminology that stays consistent, and sections that stay focused all influence how information survives interpretation. When ideas are clearly framed and logically ordered, they remain intact even after being separated from their original page.
This changes how teams need to approach content creation. Planning now includes AI-search considerations and thinking about how information might be extracted, summarized, or recombined elsewhere. Content that holds together under that pressure tends to surface more often and persist longer across AI-driven environments.
Authority now grows through accumulation.
Search engines and AI systems pay close attention to how thoroughly a site explores a subject, how consistently it answers related questions, and how naturally its content interconnects. And yes, individual pages obviously still matter. It’s just that their performance increasingly reflects the strength of the entire surrounding ecosystem. Topic clusters support this by creating continuity. Internal links guide readers through related ideas while giving machines a clear sense of scope and relevance. Over time, this builds a reputation for depth that benefits new content as soon as it enters the system.
For organizations publishing at scale, this approach also introduces stability. Authority spreads across related assets instead of concentrating on a single page. And as authority accumulates, new content enters the conversation with momentum already behind it.
Experience shapes perception long before rankings enter the picture. In practical terms, this is where user experience (UX) and search experience optimization (SXO) converge, shaping how people interact with content and how search systems interpret those interactions.
When content loads quickly, reads clearly, and flows logically, users engage with confidence. Those behaviors generate signals that ripple outward across search systems. Structure plays a central role here. Clear headings support scanning. Thoughtful spacing reduces cognitive load. Consistent formatting helps readers orient themselves as they move through complex topics. And this is just as true for LLMs as it is for human readers.
It may seem strange to suggest that AI would care about design, but it absolutely does. Or, to put it another way, content structure is often among the first signals a system uses to understand the navigability and coherency of the information on the page (even before it evaluates overall subject matter).
As search surfaces continue to prioritize usability, experience becomes inseparable from visibility.
Credibility rarely announces itself directly. It accumulates quietly, through patterns that repeat over time. Readers, on the other hand, pick up on those patterns almost immediately. They notice when content reflects lived experience instead of abstract advice. They notice when examples feel earned, when sources make sense, and when a brand sounds like the same brand from one page to the next. That familiarity builds confidence, even if the reader can’t quite articulate why.
AI systems likewise pay attention to many of the same cues. Authorship, sourcing, topical consistency, and historical performance all influence which information gets prioritized. Content that demonstrates experience and expertise in small, repeatable ways tends to travel even farther in 2026.
This is what Google refers to as E-E-A-T: Experience, Expertise, Authoritativeness, and Trustworthiness — the signals that help determine what content earns visibility. For teams working on evolving SEO strategies, this realigns the focus from chasing isolated wins to building a reputation. Clear authorship, transparent sourcing, and original insight all contribute to that reputation.
Just be aware that this credibility is both cumulative and fragile. Each accurate, useful interaction reinforces the next, creating credibility that’s difficult to fake. But at the same time, when content gets stale or expert advice gives way to generic advice, that credibility quickly and quietly starts to erode.
Discovery rarely happens in a straight line. People don’t sit down, type a query, read one page, and call it a day. They skim an article, review an AI overview, glance at an image, save something for later, and circle back when the timing feels right. Some of those moments happen in long-form content, where depth and detail matter. Others happen through visuals, short videos, structured summaries, or quick references designed to help ideas click faster. Each platform shapes how information is absorbed and remembered, even when the underlying message stays the same.
This shifts how content earns longevity. Ideas that translate across formats tend to stay visible longer because they meet people in different states of attention and curiosity.
For evolving SEO strategies, this flexibility supports consistent presence across a widening ecosystem. Content that travels remains discoverable, recognizable, and useful as platforms and behaviors continue to evolve. Alternatively, non-traveling content puts all its eggs (visibility) into one basket (surface), losing relevance everywhere else as discovery habits shift around it.
Site visitors show up carrying context: how much they already know, how urgent the problem feels, how close they are to making a decision, etc. Sometimes they’re trying to understand a concept for the first time. Other times they’re pressure-testing an option, looking for reassurance, or even just sanity-checking a choice they’ve mostly already made.
Content that works acknowledges those mental states explicitly. It anticipates the questions that naturally follow and answers them in an order that feels intuitive. When that happens, the content feels relevant almost immediately, because it meets readers where they already are instead of asking them to recalibrate.
Early-stage content helps people understand what problem they’re dealing with. Mid-stage content helps them sort through their options. Later-stage content helps them decide what to do next. Together, these pieces form a throughline that reflects how real decisions unfold over time. When intent is baked into structure, it’s easier to read, easier to trust, and easier to decide whether it’s actually useful — both for readers and the systems evaluating how that content performs.
Measurement has gotten messier. Why? Because influence now shows up in more places than a traffic report can easily capture. Modern SEO metrics now include:
When measurement evolves alongside strategy, SEO becomes easier to defend, easier to scale, and easier to integrate with the rest of the business.
So, where are the mistakes happening? As with many roads to hell, these ones are paved in good intentions applied a little too narrowly.
They say that the journey of a thousand miles starts with a single step. We’d suggest that it starts before that step, by taking a look at where you’re standing right now.
At 97th Floor, SEO and AI search solutions are built around how search actually works today, and how it continues to change.
Our SEO services integrate AI search considerations, technical SEO, and content strategy into a unified framework built for modern discovery. The focus stays on building durable authority, improving interpretability across platforms, and aligning search visibility with meaningful business outcomes, all while ensuring that the human element doesn’t get lost along the way.
That work is supported by proprietary frameworks, deep analytics, and close collaboration across SEO, paid media, and measurement teams. The result is a strategy designed to hold up across platforms and continue performing well even as search behavior evolves, making 97th Floor one of the best AI SEO agencies available today.
SEO is changing… and it will keep changing. Our role is to help brands stay visible through that change by building strategies rooted in clarity and adaptability, optimizing for the future of AI search even as we keep sight of those fundamentals that will always remain relevant.
Paid media has grown up.
Does this mean it’s simpler, calmer, or easier to manage? Hahaha. No. Quite the opposite, in fact.
In 2026, paid media lives at the intersection of automation, creative strategy, data interpretation, and business accountability. Platforms move quickly. Interfaces change often. AI touches almost every layer of execution. And budgets feel heavier than they used to, because expectations are heavier too.This is where the role of a PPC agency starts to look very different from what it did even a few years ago. What used to be about keyword bids and ad copy now looks much more like systems thinking, forecasting, and cross-channel coordination. Which is exactly why businesses continue to turn to PPC agencies: for guidance.
At its most basic, a PPC agency manages paid advertising across platforms like Google, Microsoft, Meta, LinkedIn, and emerging discovery environments (such as AI-driven search and retail media networks). That part hasn’t changed.
What has changed is how success gets defined and how work gets organized around it. A modern PPC management agency centers on business outcomes: qualified demand, revenue contribution, and scalable growth. Traffic still matters; it’s just not the only voice in the conversation anymore.Today’s PPC agency operates as a strategic partner. Campaign execution is supported by planning, forecasting, testing frameworks, and measurement models that extend beyond individual platforms. Heading into 2026, PPC agency models reflect this shift. Strategy, interpretation, and optimization layers now carry as much weight as execution itself.
Maybe not a huge surprise in this new era of autonomous, intelligent machines, but the most visible change is automation.
Bidding, targeting, and creative testing increasingly rely on machine learning systems that operate faster than any human team could. That reality shapes how a modern PPC agency adds value. Manual campaign management alone doesn’t always hold up well anymore. The real leverage comes from setting the right guardrails for automation and evaluating its impact. As such, PPC agencies now spend more time interpreting data, defining testing priorities, and connecting performance signals back to business goals.
Data integration plays a major role here. Performance spans analytics tools, CRM systems, lifecycle data, and attribution models rather than living in a single dashboard. A capable PPC agency knows how to connect those inputs so optimization decisions reflect actual business conditions.
No two PPC agencies present their services in exactly the same way. Still, the strongest ones tend to share a common foundation. Each capability reinforces the next, forming an approach designed to work cohesively as campaigns grow and evolve.
The impact of working with a PPC agency is rarely expressed as a single metric. It reveals itself over time, in how efficiently teams operate, how confidently decisions get made, and how resilient paid programs become as complexity increases.
Most teams tend to notice the value of a PPC agency when they suddenly realize that they have a moment to catch their collective breath. Budgets start to feel intentional instead of reactive. Testing moves forward with a clearer sense of purpose. Performance reviews become less about chasing fluctuations and more about understanding patterns. And as campaigns expand across platforms and audiences, that steadiness creates room to scale thoughtfully, without the anxiety-inducing feeling that everything needs to be fixed at once.
Paid platforms are in a constant state of motion, and keeping up with that change is practically a job in itself. Policies update, automation behaves differently, targeting options come and go, and none of it waits for anyone. A PPC agency lives in that reality every day so you don’t have to, tracking changes, pressure-testing assumptions, and making adjustments before small issues turn into expensive ones. That buffer matters most when budgets increase and leadership expects stability along with performance.
For leadership teams, the real value often shows up in how conversations change. Performance stops feeling abstract and starts making sense in the context of revenue targets, pipeline health, and growth plans. A strong PPC agency helps translate what’s happening in the platforms into signals leaders can actually use, whether that’s deciding where to invest next, when to pull back, or how aggressive to be with growth goals. That shared understanding tends to ripple outward, making planning smoother and decisions easier to stand behind.
Competitive markets have a way of exposing weak strategy very quickly. Costs rise, attention fragments, and small inefficiencies stop being small. This is where a modern PPC agency earns trust by bringing discipline, judgment, and a long view to every decision:
In crowded spaces, broad targeting gets expensive fast. Strong PPC agencies spend real time understanding who’s actually worth reaching and what signals indicate readiness. That work goes beyond basic audience definitions and into intent modeling, behavior patterns, and demand quality. Clarity makes budget decisions easier. Spend gets directed toward people who are actually nearing a decision, keeping efficiency from eroding even when competition gets fierce.
Most buying journeys don’t move in a straight line, and competitive markets certainly don’t change that fact. Effective agencies account for that complexity from the start. Awareness, consideration, and conversion campaigns are designed to work together, each playing a role at the right moment instead of fighting for credit. Messaging shifts as people learn more, pause, compare options, and return when the timing feels right.
In competitive auctions, creative fatigue sets in quickly. Ads that worked last quarter start blending into the noise. Strong PPC agencies counter this by treating creative as an ongoing system. Clear messaging frameworks shape what gets tested and why, while performance data guides what gets refined next. Over time, patterns become visible — which ideas consistently resonate, which formats hold attention, and which angles stall out early. That ongoing rhythm keeps accounts healthy and responsive, without forcing teams into constant, exhausting reinvention.
Maybe it goes without saying, but forecasting works best when it reflects how businesses actually operate. The best PPC agencies approach projections by looking at what has happened, what’s changing in the market, and how leadership defines growth. That framing helps teams understand what different budget levels are likely to support and where expectations should sit. This approach makes it easier to have honest conversations about tradeoffs, timing, and risk.
Clicks don’t tell the whole story, especially in competitive markets. But knowing what comes after the click? That’s where things start to get interesting. Context-driven optimization pulls insight from sales feedback, lifecycle data, analytics, and post-click behavior to show how paid traffic actually performs once it leaves the ad platform. That broader view changes decision-making. Keywords get evaluated based on lead quality. Creative gets refined using downstream signals, budgets shift according to what converts, and optimization reflects the kinds of real outcomes that matter.
Now, be aware that at some point, every paid media program hits a crossroads. Performance plateaus, complexity increases, and what once felt manageable starts to feel harder to steer. Choosing a PPC agency at that stage becomes less about day-to-day execution and more about finding a partner who understands how paid media fits into a broader growth system — one that connects strategy, data, and long-term direction.With that in mind, a few criteria tend to separate agencies that simply manage campaigns from those that help businesses grow:
| Strategic depth | Look for teams that can explain why they’re making decisions, not just what they’re doing. Strong strategy shows up in how campaigns are structured, how tradeoffs are discussed, and how priorities get set over time. |
| Transparent, outcome-driven reporting | Clear reporting connects spend to performance in ways leadership can actually use. That means fewer vanity metrics and more insight into efficiency, demand quality, and business impact. |
| Experience across industries and growth stages | Markets behave differently at different scales. Agencies that have seen multiple growth phases tend to anticipate challenges instead of reacting to them. |
| Responsible use of AI and automation | Automation plays a role, but judgment still matters. The right PPC agency knows how to guide and evaluate automated systems so performance stays intentional rather than opaque. |
| Alignment with internal teams | Paid media works best when it doesn’t operate in a silo. Agencies that collaborate closely with analytics, CRO, SEO, and internal stakeholders tend to drive more consistent results and clearer accountability. |
There probably isn’t a single moment when a business suddenly “needs” a PPC advertising agency. It usually shows up as a pattern. A few small frictions pile up. Questions take longer to answer. Confidence in decisions starts to wobble. Often, this is precipitated by symptoms that are worth keeping an eye out for:
At 97th Floor, PPC advertising strategy starts with a simple acknowledgment: paid media lives inside a much bigger system than it once did. Revenue targets, pipeline realities, internal constraints — all of that shapes what paid media can and should do. We take the time to understand those inputs early, because everything downstream works better when the destination is clear.
Paid search and paid social operate within shared frameworks, not separate silos. Insights move between channels, and performance signals actually get used instead of parked in dashboards. AI and automation play their part, but always with human direction. Our teams set guardrails, interpret results, and test assumptions so optimization stays intentional and grounded in outcomes that matter.But let’s be clear about one thing: That work only holds up when collaboration is real. That’s why our PPC teams partner closely with analytics, SEO, and CRO specialists to reflect how users actually move through the journey. Consider our work with JK Moving, where reshaping paid media around demand quality and intent alignment led to more qualified leads and better efficiency in a crowded market. This is what happens when strategy, testing, and cross-team coordination pull in the same direction.
Planning a PPC investment in 2026 requires more than setting a budget and choosing platforms. It starts with understanding where you are today and where paid media fits within your broader growth plans. As you get started, be sure to:
For more than 20 years, 97th Floor has helped enterprise brands grow through constant shifts in how media works — by staying curious, experimental, and deeply invested in what’s changing next. Our PPC management approach blends strategy, data, and execution into systems designed for modern platforms, AI-driven optimization, and the realities of today’s paid media landscape.
So, if you’re ready to build a PPC strategy that supports long-term growth and adapts as paid media continues to evolve, we’re ready to help. After all, paid media has grown up. And with our help, your business can continue to grow right alongside it.
You’ve probably noticed it already: traffic behaves differently than it did a year ago. Pages that used to rank predictably now earn visibility one week and vanish the next. Meanwhile, AI Overviews, ChatGPT answers, and Perplexity summaries are shaping what people see before they ever reach your site.
That shift is exactly why marketers are rethinking their AI SEO strategy for 2026. How do you get the right consumers to actually engage with your brand, not just the search engine? Your brand needs to be more trustworthy and recognizable, not only to your audience but to search engines themselves.
We’ve spent the last two years running experiments across generative engines, structured data setups, and entity-driven content frameworks. What’s working now is brands that pair technical precision with human expertise. This AI SEO guide breaks down how to build that kind of strategy step-by-step so that your brand is referenced more and seen by the people that matter the most to your business.
An AI SEO strategy is simply a plan for helping both search engines and generative models understand who you are and why your content should be referenced. Instead of worrying only about where a page ranks, you’re thinking about how clearly your brand shows up across topics, how well your expertise is represented, and whether AI systems can confidently pull from your work.
As search shifts toward AI search optimization, engines rely more on clean structure, consistent language, and content that makes your perspective easy to identify. The same applies to generative engine optimization, where models look for reliable patterns, strong entity definitions, and authors who actually know their subject. We have to present our knowledge in a way machines can recognize while still writing for real people.
AI rewired how information gets pulled together. Generative engines break your content into smaller pieces, look for patterns across topics you cover, and compare your explanations against other credible sources. They’re not scanning the page the way a crawler would, but actually interpreting it.
That shift puts more weight on things that used to feel “nice to have.” Topical depth—how thoroughly you cover a subject across multiple pieces—helps models understand your expertise beyond a single URL. Since AI can interpret it now alongside your audience, it matters just as much on the technical side.
If you know how SEO works, it’s time to revise your playbook with AI in mind. Some teams have strong technical foundations but haven’t mapped their content in a way AI can follow. Others have great material but no clear structure tying their expertise together. These five steps outline the patterns we’ve seen produce meaningful gains as we have learned how to optimize AI SEO.
The first step to your SEO strategy with AI is getting an idea of how your content ecosystem performs when a model tries to interpret it. A standard audit won’t surface everything you need, so an AI-focused review looks at things like entity coverage, schema accuracy, internal connections between pages, and whether your explanations stay consistent across topics.
Ask yourself:
Once you know where things stand, set goals that track both search performance and AI visibility. Rankings matter, of course, but push beyond them, too. You want to see how often your content shows up in AI Overviews and if you’re keeping up with your competitors, especially if they are showing up in the search engine optimizations.
From there, map where your expertise naturally fits within broader topical clusters. This helps you see where you already have momentum and where the gaps are. AI tools can support the analysis, but choosing what to deepen or retire still depends on your priorities, not just what a model suggests. It also helps to take a quick look at how competitors show up in generative engines to spot topics models already associate with others in your space.
Generative engines are trying to decide whose explanation is dependable enough to reuse, and they look for signals that reinforce your expertise across multiple touchpoints and content pushes. As you look at your own content, a few signals often determine whether a model treats your work as dependable:
Make sure your best thinking shows up in places where AI can recognize it: expert-led articles, well-structured pages, digital PR that puts your name in the right conversations, and formatting choices that make your expertise easier to parse.
AI fits naturally into most SEO workflows once you know where it adds real lift. Traditional SEO still does the heavy lifting like crawling, indexing, and information architecture, but AI gives you a faster way to understand how topics connect from a model’s perspective.
Here are the areas where teams tend to see the biggest gains:
AI sharpens what you already do well and reveals opportunities you’d otherwise miss. Your strategy stays intact; your visibility grows because your decisions get better inputs.
Strategy matters, but execution is where most teams either gain leverage or fall behind. The difference often comes down to how you work with AI day-to-day — not just the tools you use, but the way you interact with them. Here’s a quick example of what that collaborative mindset looks like in practice.
AI sharpens what you already do well and reveals opportunities you’d otherwise miss. Your strategy stays intact; your visibility grows because your decisions get better inputs.
Generative tools don’t read your pages front to back. They jump around, grab pieces that answer specific questions, and stitch them together. When your content is organized in a way that gives them strong pieces to pull from, you show up more often and with better representation.
Here are a few patterns we’ve consistently seen help:
When you’re writing and producing an article, ultimately remember that you are giving models well-labeled building blocks that AI wants to use.
However tempting it is to hand everything off to the bots, the human touch really is irreplaceable and still important when it comes to rankings. Original thinking creates ideas and patterns that don’t appear anywhere else, which gives engines something completely unique and distinct to work with.
Here are a few simple things you can do to stay competitive if you do use AI.
When your content reflects the way your team actually thinks, generative engines pick up on that brand and reliability—and your audience does, too.
You need a mix of signals that show how people interact with your pages and how often AI systems lean on your work. Most teams end up watching a handful of KPIs that capture both sides of the picture:
Make sure to review your data so you can spot emerging trends and identify the content that is earning your citations.
The cool part about AI is that it is designed to work with you. You don’t have to throw everything you know and do out of the window. Don’t lose the traction you have gained. Instead, try to show up in generative results by overlapping with strong existing campaigns, PR, and content marketing strategies.
A few areas benefit the most from tighter alignment:
If this seems like a daunting task, an AI SEO agency can help your team bring all this into focus so that you are uniform across the board.
If we’ve learned anything in the past few years, it’s that search won’t settle into one format. Over the next few years, we anticipate that AI summaries, traditional SERPs, voice interfaces, and image-based queries will exist side by side, and brands will need to show up consistently across all of them. Conversations around the future of search already point to a mix of text, visuals, and conversational interfaces shaping how people find information. Teams that adapt early influence how models interpret their space, and those impressions tend to last longer than a single ranking shift.
It’s a new world we’re navigating in AI search, and the brands gaining traction are the ones treating this as an opportunity and not a barrier. Tighten up your messaging, crystallize your structure, and be the voice online that models can learn from. That’s the simple version.
The long version takes a lot of time, analysis, trial and error, and tracking. If you want a partner that can help you get right to the impactful steps, 97th Floor helps teams get a better read on how they appear in generative search and where the strongest opportunities sit. Our AI SEO services give you a practical path to better visibility without overhauling the work you already trust.
Use these free tools to unburden your site of low-value content that prevents an LLM from understanding your brand. Watch your SEO performance skyrocket.
When’s the last time that Google sent you search results that weren’t at all what you were looking for? It’s rare, but it’s happened to all of us.
Maybe you searched for a recipe and ended up with a 1500-word blog post instead.
Perhaps you were looking for a list of the best blenders with product reviews but got an in-depth piece on “how to choose a blender” instead.
Maybe you were looking for broadcast details for a sporting event and landed on a product page for a streaming service.
Each of these are examples of a misalignment of page type when compared to user intent for each search query. And because of that frustration that you and countless other users feel in those situations, a main priority for Google’s algorithm is to correctly decipher user intent and align results and associated page types accordingly.
This is why page types matter so much in SEO strategy. Let’s dive into it, and how you can shore up your strategy to incorporate this key piece.
So, what do we mean when we say “page type”? Generally speaking, most written content online falls into a certain format based on user intent and where they are in the funnel. For example, some of the main page types include:
Depending on what a user is expecting to see, an appropriate page type can make all the difference to their experience — and by extension, your ability to capture their attention and prevent them from bouncing.
In the early days of SEO, less-sophisticated algorithms didn’t consider page type. It was not uncommon to see a bottom-of-the-funnel product page turned into a Frankenstein’s monster of a blog post in order to stuff in as many keywords as possible.
Today, user intent and experience are more important than ever, and that includes selecting the appropriate page type for each keyword and optimizing accordingly within that format.
You know that page type matters. And you know you need to match it to user intent. But how do you do that? Let’s break down the most common page types.
Users searching a specific brand or service name are typically looking to go directly to branded pages with essential information and straightforward navigation. This might include existing customers looking to log into their accounts, or those who are already familiar with the brand through other demand generation or nurture strategies.
If your keyword starts with “how,” “what,” or “why,” then your best bet is blog or similar informational content. Even if those words are not included, however, most higher-funnel keywords will also fall into this category—as well as a significant chunk of mid-funnel queries. If intent is not immediately obvious, it typically only takes a quick Google search to identify the main intent of users searching for these keywords.
When users are in the consideration or mid-funnel stage of the buyer’s journey, they are likely to be actively researching and comparing various solutions to their problem. As such, case studies and comparison-type content is most appropriate for these queries. Mid-funnel blog content or category pages may also be appropriate for some topics. Keywords including “best” or “reviews” are good candidates for this page type.
At the bottom of the funnel, when users are ready to buy, it only makes sense to serve them with landing or product pages. In these cases, conversion should be the priority, but there are still ways to optimize for the SERP.
Over the years, Google has attempted to prioritize user intent as much as possible. The type of page that shows up in a SERP is determined by what Google thinks the user is looking for.
Sometimes, Google will test different page types, or show a mix of page types in order to meet varying needs of different users searching for the same keyword. In these cases, SERPs may be broken up by page type and thus limit the quantity of that page type that will show on page one.
For example, only two of the spots on a certain SERP may be reserved for product pages. , If you have a product page that you want to rank for that SERP, you will have just two chances, rather than the full 10, to get it to rank. This makes understanding the correct page type for your strategy even more essential.
Do I Have the Right Page Type for my Keyword?
Ensuring that your page type matches the keyword for which you want to rank will be much easier if you start with a full understanding of your audience and customer journey. Audience insights should inform your keyword selection, help you group keywords into audience-focused topic clusters, and provide a check that you have keywords across every stage of the funnel.
From there, you can derive search intent through keyword and SERP analysis, identifying which page types dominate the top results in each case.
Building a Balanced Site Architecture
Customer journey insights are also essential in organizing your site content into a structure that is easy for both Google and users to understand. Each funnel stage should contain corresponding content, with internal linking between them, to craft the user journeys that make the most sense in order to nurture customers towards final conversion.
Now that we have established that not all pages are built for the same purpose, it should be clear why optimization must be tailored accordingly. Each page type has its own goals, layout, and optimization priorities, all designed to serve user intent while sending the right signals to search engines.
Homepage and Brand Pages
Focus: Discoverability and crawl depth.
These pages act as gateways, helping both users and search engines navigate related sets of products or topics.
Best practices: Ensure proper internal linking to and from subcategories or product pages. Use canonical tags and pagination control to avoid duplicate content.
Pro tips: Metadata should be optimized for clarity and click-through-rate (CTR). Site structure and navigation should match content topic clusters and optimal user experience.
KPIs:
Blog and Resource Articles
Focus: Education, authority, and shareability.
Blog content should build topical authority and provide genuine value to readers. These pages often target informational or mid-funnel queries and play a crucial role in internal linking and audience nurturing.
Best practices: Use clear heading hierarchies, optimized images, and schema markup for articles. Include strategic internal links to guide users (and crawlers) toward related content and next steps.
Pro tips: Blog keywords should fit into a cohesive topical authority strategy. Just because a blog article is not intended to convert right away, does not mean that you cannot guide the user to eventual conversion. Mapping out cohesive topic clusters and customer journeys with your content will not help Google and users understand your business
KPIs:
Landing and Product Pages
Focus: Conversions, minimal distractions.
Landing and product pages exist to drive a single action, such as a form fill, demo request or purchase. The key is to minimize friction and distraction on these pages so the user has a clear path to conversion.
Best practices: Keep navigation limited to maintain focus. Align target keywords with ad or campaign messaging for consistency and relevance. Prioritize mobile performance and fast load times to support both user experience and Quality Score.
Pro tips: Metadata can almost be thought of in the same way as you would a search ad at this stage — the goal is to capture as many of these high-intent users as possible, and click-through-rate optimization is essential.
KPIs:
Comparison and Case Study Pages
Focus: Clarity, rich product info, and trust signals.
These pages are built for decision-making. Users arriving here want to understand features, pricing, and proof points before they buy.
Best practices: Implement structured data and FAQs to enhance SERP and LLM visibility. Use unique, detailed descriptions and user reviews to strengthen credibility and avoid duplicate content issues.
Pro Tips: Proper content hierarchy will aid in ranking for research queries, as well as improving user experience and engagement metrics. Formatted elements such as lists, FAQ sections, and comparison tables will aid your chances of showing in AIO.
KPIs:
No matter how badly you may want to get a certain page ranking for a specific keyword, it won’t happen if Google does not believe it matches user intent correctly.
One of the most common mistakes is trying to force it anyways, attempting to rank a blog post for a transactional keyword, or using a product page to target an informational query. Google quickly identifies the mismatch, and users do too. This results in poor rankings, low engagement, and wasted investment on content that fits neither the user’s needs nor your own goals.
Page type dictates how both Google and users interpret your content. A balanced SEO strategy ensures you have the right mix of page types across the funnel — aligning intent and format throughout, and giving you the best chance of boosting both rankings and conversions.
If you’ve ever Googled something in the last year, you’ve likely seen an AI summary pop up at the top of the SERP page. Whether you read that answer or not, having those AI summaries on search engine results has changed the way users interact with websites and the way SEOs are approaching optimization.
Even though SEO is shifting, there’s no reason to worry about its future. SEO is around to stay—and so is AI. The key is learning how to use both together in an effective way to get your content to your audience and to help you reap the benefits of online visibility. Read on to learn all about AI and SEO, best practices for adjusting your strategy, and where the future of search is going.
SEO is what helps your page show up on search engines to meet user queries. However, recently, the top slots are going to an AI summary, and the AI tool will search across pages to find information to fuel its responses. AI SEO also includes using AI like machine learning (ML), natural language processing (NLP), and predictive analytics as a tool in your own SEO process. It’s all about getting your website to display in AI searches as well as using it to help you improve your own work.
Unlike traditional search optimization, which largely focused on keyword placement, backlinks, and static algorithmic signals, AI-enabled SEO adds several new dimensions:
Here are some concrete examples of how AI capabilities are already being applied in search and SEO:
AI is reshaping the SEO landscape by powering smarter search engine results pages (SERPs) and fueling the rise of AI-driven answer engines. Instead of delivering a list of ranked blue links, modern SERPs often feature AI-generated summaries and at the top of a SERP to answer questions directly—reducing the need to click through to websites.
This shift moves the focus of SEO from traditional rankings to retrieval and representation. It's no longer just about being on page one—it's about being cited or summarized by AI models that interpret and surface the most relevant content from across the web. As a result, user behavior is evolving. Click-through rates (CTRs) on traditional organic listings are declining in some categories, while zero-click searches are increasing.
The goal now is to curate your content in a way that makes it easy for an AI tool to retrieve and summarize it.
Understanding which AI platform your content needs to perform in just got a lot clearer. SEO expert Eli Schwartz breaks down what Apple's partnership with Google Gemini means for the future of search — and why it cements Google as the dominant AI search platform you need to be optimizing for. This short video captures exactly how Google won the AI search war, and what that means for the strategy you're building right now.
As generative AI becomes more integrated into search engines and digital assistants, SEO strategies need to evolve to make sure your pages are staying on top and showing up in the right searches. AI usually considers these three key factors when choosing content to cite:
Certain formats tend to perform better in AI summaries, including:
AI can also help you work smarter, not harder. AI tools can automate keyword research, detect content gaps, and personalize experiences across channels to help you find the right areas to create content.
Integrating AI into your SEO strategy doesn’t need to be overwhelming. As SEO experts, we’ve worked hands-on with AI search optimization across many industries, and we’ve identified four best practices that can help your team adopt AI.
The best way to begin is with low-risk, high-visibility pilot tests. Try AI tools on smaller tasks—like keyword clustering, meta tag suggestions, or content outline generation—and track performance over time. Use these early experiments to measure output quality, workflow impact, and time savings. Once you understand where the tech shines (and where it doesn’t), you can scale up confidently.
Choose AI tools that work well within your existing SEO stack. You’re likely using CMS platforms like WordPress and Webflow or analytics tools like GA4, Looker Studio, or Search Console, and you want AI tools that work with those. Don’t just chase “shiny” AI features. Make sure they fit into your real-world systems.
AI is a powerful assistant but not a decision-maker. Use it to automate repetitive tasks, surface insights, and speed up processes, but keep humans in the loop for critical thinking and decision making. Humans need to make big decisions, look over AI content, and check for brand consistency.
AI in SEO is not a static playbook—it’s an ongoing evolution. Keep your team learning with hands-on training and encourage experimentation with new tools and techniques. Look for ways to bring real value into daily workflows: faster content ideation, smarter optimization, better insights. All of this will help you optimize for AI search SEO.
While AI gives you a wide range of advantages with SEO, there are some new challenges to prepare for, including:
As AI transforms how search works, the role of SEO professionals is evolving just as quickly. Instead of spending time on purely manual tasks—like keyword tagging, metadata updates, or technical audits—SEO pros are stepping into more strategic roles. Their job isn’t just to optimize for algorithms, but to understand how people and machines interact.
AI is a powerful tool, but it complements—not replaces—human expertise. Machines can generate content, identify trends, and automate repetitive tasks, but they can’t replicate human creativity. SEO teams must now balance automation with context, voice, and long-term vision.
At 97th Floor, we’ve embraced this shift by changing the name of our SEO department to the Search Department. This rebrand reflects a broader mandate: we’re no longer optimizing only for search engines—we’re optimizing for how people experience search across AI chat, answer engines, smart devices, and traditional SERPs.
As AI reshapes how people discover and consume content, the way we measure SEO success must also evolve. Here are our tips for measuring success.
The future of SEO is about aligning with how AI understands, retrieves, and delivers information. Several key trends are shaping what’s next:
To stay competitive, SEOs must prepare for ongoing shifts by adopting agile processes, investing in AI literacy, and building systems that track visibility across traditional and AI-powered platforms.
If you want to see what can be done with AI SEO strategy, look no further than 97th Floor’s campaign with Princess Cruises. We helped Princess Cruises move beyond siloed pages toward a tightly interlinked topical cluster model. The aim was to layout content in a way that signals topical authority, which helps AI systems find more contextually rich responses and increases the chance that Princess content is cited or summarized in AI-driven overviews.
The results were dramatic:
By marrying strategic direction with hands-on execution, we turned AI‑centric theory into concrete gains—while proving that human judgment, agility, and domain knowledge remain indispensable.
If your SEO team is wondering whether AI‑driven search is already rewriting the rules—this case shows it is, and early wins are possible. The shift is not hypothetical. It's real, and the rewards go to teams that think differently about content structure, authority, and AI visibility.
If you'd like to explore how generative search can work for your brand—or see how 97th Floor can help you architect a strategy and workflow—learn more about our AI SEO services.
Your content might already rank well in Google, but what happens when users never click through? With AI Overviews, Bing Copilot, Perplexity, and chat-based search, answers are being generated instantly, and often without the need for a typical site visit. That shift means the old playbook of targeting blue links and optimizing for CTR doesn’t cut it anymore.
AI search engine optimization (AI SEO) is the next frontier. Instead of chasing positions, brands now compete for visibility inside summaries, citations, and answer boxes. This guide breaks down how AI SEO works, the strategies that matter most in 2025, and which metrics to track as you future-proof your search presence in our AI-first world.
As SEO continues to evolve beyond clicks and rankings, the real question becomes: did you genuinely satisfy your audience with relevant content? This short video captures why engagement and user value now matter more than ever.
AI search engine optimization is about making your content answer-ready for systems powered by large language models (LLMs). Instead of just aiming for the “10 blue links” on a results page, AI SEO helps your content show up inside AI Overviews, generative snippets, and even chat-based answers.
Think of how these engines work. First, they retrieve documents that look relevant. Then, the model generates a response by summarizing those documents — and, if you’re doing something right, citing the ones it trusts. That citation is the new click-through.
So, do keywords and backlinks still matter?
Yes.
Are they enough on their own?
Not quite.
To get cited, your content has to speak the same language as the machine. Entity-rich writing, clear definitions, structured data, and clean metadata. The easier you make it for a model to sift through your content, the more likely it is to select your content as a reliable source.
Structured data and content have always been one of the primary answers for how to optimize for search engines, so a lot of what you naturally do is already helping. So, traditional SEO isn’t dead. Fast load times, strong technical health, and mobile readiness are still table stakes. What’s changed is the layer on top: your brand now has to prove it’s a trusted authority for both humans and algorithms.
We always talk about Google, but that isn’t the only search engine or resource for results. They show up across an expanding ecosystem, including:
The message for marketers is clear: you’re not just optimizing for Google anymore. AI SEO means building content that can be selected, summarized, and cited across multiple surfaces — and more importantly, wherever your audience is asking questions.
Structure. Writing quality. Authority signals. That’s what large language models (LLMs) are looking for when deciding which content to trust. Instead of optimizing for a ranking, you’re optimizing for selection inside an AI-generated answer. That process leans on a few core elements:
When these pieces come together, your content becomes easier for AI to interpret, summarize, and cite. It shifts the goal from driving clicks to earning visibility inside the answers people already see. So, the more quote-ready your content is, the more visible your content and brand will be.
Traditional SEO rewarded visibility. AI SEO rewards credibility. Instead of just climbing search rankings, the goal is to become the source that AI systems trust enough to cite.
Getting to page one used to be the win. Now, the real prize is being quoted inside an AI Overview or chat result. That means structuring passages so they can be pulled directly into answers. For instance, a product comparison table or a one-sentence definition has a better shot of being cited than a long block of copy. Rankings still matter, but citations are what earn attention in AI search.
Stuffing in the right keyword variation won’t convince a model that your page is the best fit. What does? Entities and their relationships. Imagine writing about “running shoes.” Instead of just repeating the phrase, you’d define cushioning types, list popular brands, and connect those details to activities like marathon training or trail running. That context helps AI systems map how your content answers more specific queries.
Click-through rate once measured success, but if users get their answer from an AI summary, no click happens. AI share of voice tracks how often your brand is cited across Google AI Overviews, Bing Copilot, or Perplexity. For marketers, this metric reveals whether your expertise is showing up where people are now spending their attention: inside the generated response itself.
If your pages aren’t being cited in AI answers, they might as well be invisible. The fix isn’t complicated, but there are a couple of specifics you need to incorporate.
Think about how an AI model scans a page: it’s looking for clear, digestible chunks. Start sections with one-sentence definitions, then expand. Use lists, tables, and step-by-step breakdowns, formats that can be lifted directly into generated responses. Adding FAQs within a topic cluster also improves your odds of citation because the content is already shaped like an answer.
If you’re writing about “how to refinance a mortgage,” opening with a single-sentence definition followed by a step-by-step list gives the model exactly what it needs. FAQs work the same way—they mirror the Q&A style AI results are built on.
Schema is like a cheat sheet for machines — it provides the machine-readable signals AI models rely on. A recipe site using FAQPage, HowTo, Article, Product, Organization, and Person schema makes it far easier for AI to parse instructions, videos, and timings than one with plain text alone. The difference? One gets cited as a trusted source in a generated answer, the other is overlooked. Don’t just add markup, but test it with validation tools and keep metadata (author, date, org) clean.
Search engines still look for authority signals; AI just weighs them differently. Include expert bylines, clear author bios, and cite credible sources. Backlinks and third-party mentions reinforce authority beyond your own site. A medical site with content written by an MD, backed by references from the Mayo Clinic, is much more likely to be quoted than a generic health blog.
Featured snippets are often the training ground — and the live data source — for generative answers. Write concise answers at the top of a section, then elaborate. Use bullet lists for processes, definition tables for comparisons, and direct phrasing that AI can easily quote. If you run an e-commerce site, turning your “best laptops for students” blog into a bulleted comparison chart increases the odds of winning a snippet today and being cited in an AI Overview tomorrow.
Even the best content gets skipped if it’s slow or messy, and AI search won’t cite a page that’s hard to access. Keep Core Web Vitals healthy, mobile UX smooth, and HTTPS standard. Maintain clean sitemaps and crawl budget hygiene so nothing gets missed. Don’t forget multimodal signals: alt text, transcripts, and captions increase the chance of your images, videos, or audio being pulled into AI responses.
Stale pages rarely get cited. Regularly update stats, examples, and dates to show relevance. Mark content with “last updated on” fields, and consolidate thin pages into authoritative hubs.
Take a cybersecurity blog that updates its “2023 phishing attack statistics” post with 2025 numbers. This signals relevance, while an outdated competitor page fades into the background. Adding “last updated” tags and consolidating thin content into a hub reinforces freshness, and that freshness helps your content stay visible when AI systems scan for the most current, reliable answers.
AI models cite what they can clearly identify. Use straightforward, factual phrasing. Reference reputable sources and include statements that stand on their own — short enough to be lifted directly into a generated summary. For example, writing “The average email open rate in 2025 is 21% (Statista)” gives AI a clean, source-backed fact it can lift directly. Compare that to burying the same stat inside a paragraph of fluff — harder to cite, easier to skip.
AI SEO relies on platforms that help with entity research, content optimization, technical checks, and — new to 2025 — tracking citations. Here’s where to focus when it comes to finding the right tools.
Tools like SEMrush Topic Research, Ahrefs Keywords Explorer, and AlsoAsked help uncover not just keywords, but the entities and questions AI models associate with them. For example, if you’re targeting “electric vehicles,” you’ll also see related entities like charging infrastructure, battery types, and federal tax credits — relationships you’ll want reflected in your content.
Platforms such as SurferSEO, Clearscope, and MarketMuse score your content against NLP models to highlight coverage gaps. Writing a guide on “remote team collaboration”? These tools surface semantically related phrases like project management software, asynchronous communication, and time zone overlap. This is how you make sure that your copy speaks the same language as AI search.
This is the newest tool category. New features from Sistrix, Ahrefs, and specialized platforms like Perplexity Pro Reports show how often your site is mentioned in AI Overviews, chat answers, or other generative surfaces. Instead of treating “AI share of voice” as an abstract idea, these tools quantify it.
Technical SEO underpins everything. Crawling and audit tools like Screaming Frog, OnCrawl, and Sitebulb keep Core Web Vitals, sitemaps, and log files clean, factors that directly influence whether AI systems can access and parse your content. Paired with ContentKing for continuous monitoring, you’ll know the moment a broken link, schema error, or slow load threatens your visibility.
For more context, Search Engine Journal’s roundup of AI SEO tools highlights how quickly this space is evolving.
Single pages being optimized are helpful, but you need them to come together with an entire optimized system, where every piece of content reinforces the rest. These three elements set that system up for success.
The hub-and-spoke model works especially well in AI search. A pillar page anchors the topic (say, “employee wellness programs”), while supporting articles dive into subtopics like fitness stipends, mental health benefits, or VTO policies. Interlinking signals topical authority and gives LLMs a clear map of how your content covers the space.
Think about outlines as blueprints for AI answers. Instead of writing a full draft and hoping it works for snippets later, design the structure up front. That might mean planning where a definition box goes, outlining a process as numbered steps, or slotting in a pros-and-cons table.
Treat expert input as a built-in stage of content design, not a final polish. Publishing with bylines, credentials, and references reinforces authority, but the real gain comes from weaving SME insights directly into the structure. That way, your content carries unique expertise that AI models can’t find in generic sources.
Click rates and rankings are still worth tracking, but when it comes to tracking AI SEO, there are some new (or reframed) metrics to monitor to see if your efforts are paying off.
Citation frequency is the new visibility metric. Track how often your site is referenced in Google AI Overviews, Bing Copilot, Perplexity, and other chat-based results. Some SEO platforms — Ahrefs among them — are rolling out features that quantify AI share of voice.
If you’re already tracking AI share of voice, the next step is to use that data strategically. Benchmark citation frequency against competitors to understand relative visibility, and watch for shifts in the types of queries where you’re cited. For example, an increase in citations around product-comparison queries might signal growing authority at the consideration stage of the funnel.
Organic metrics don’t disappear. Rankings, reach, impressions, and engagement still matter, especially when paired with assisted conversions and pipeline attribution. For example, if a product guide is cited in an AI Overview but also sees rising organic traffic and contributes to demo requests, you’ve got evidence that AI visibility is feeding the funnel, not just awareness.
AI search results evolve quickly, which means measurement has to be ongoing. Build quarterly checkpoints into your workflow: update schema, refresh content, and test snippet formats against key queries. A/B testing definitions, tables, or list structures can be especially helpful in determining what AI systems are most likely to pull into generated answers.
AI systems look for clear, scannable data when summarizing offerings. Product pages with benefits tables, comparison blocks, and FAQs are more likely to surface in AI Overviews.
One example comes from Princess Cruises, which needed to dominate Alaskan cruise searches. Instead of chasing keywords, they built topic clusters around their service pages: 70 new pieces of content, 23 optimized port landing pages, and a web of internal links pointing back to core pillars.
Within three months, this strategy drove a 261% increase in AI Overview mentions, capturing 66.2% of competitive mentions and 88.4% of impressions in AI-driven search. This 97th Floor case study shows how structuring content this way proves far more effective than traditional keyword targeting.
Guides and blog posts often answer early- or mid-funnel questions, which makes them prime candidates for AI answers. Starting with concise definitions, layering in structured summaries, and adding original charts or visuals helps these assets stand out. For example, a blog explaining “what is zero trust security” that opens with a crisp definition and includes a diagram will likely be favored over one with only dense paragraphs.
Glossaries and resource libraries are tailor-made for AI SEO. Short, canonical definitions backed by internal links to related topics create a knowledge graph effect that language models can navigate. For example, a glossary page might define an industry term in two or three sentences, then connect readers to deeper resources across your site. Even though the content is brief, its clarity and structure make it highly attractive for AI-generated summaries.
Optimizing for AI search raises new responsibilities. Accuracy and trustworthiness are even more important today to protect your brand. Here’s how to make sure your organization stays out of hot water.
Generative answers can spread errors if the sources feeding them are flawed. That makes it vital to maintain rigorous sourcing practices: cite reputable references, conduct boas checks, log updates, and monitor pages for outdated claims. Treat every page as if it could be quoted directly — because it might.
Generative AI has blurred the lines between original and machine-written material. To protect both your brand and your users, adopt clear policies on how AI is used in content creation. Human review and quality assurance should always be the last step before publishing. Where AI assistance is part of the process, disclosure fosters transparency and helps build trust.
Most teams start strong — refreshing content, adding schema, tracking AI citations. But if traffic plateaus, citations remain sparse, or entity coverage feels incomplete, it may signal the limits of internal bandwidth. What works this quarter may look different six months from now, and the brands winning citations are the ones adapting fastest. We can help with that.
We’ve built systems that scale with change: topic clusters that expand as industries shift, schema frameworks that grow with new content types, and measurement models that capture how AI surfaces your brand across platforms. The result is momentum, increasing visibility that keeps clients ahead while competitors scramble to catch up.
If your goal is to lead in an AI-first search landscape, our team has the playbook and the proof to make it happen. Let’s talk.
Running an ecommerce brand in 2025 is like hauling feral cats out of a burning building — noble work, but try it alone and you’ll come out with more scars than survivors. That’s because ecommerce isn’t a single challenge; it’s dozens of moving, clawing parts that demand your attention all at once. Scaling an online store goes way beyond having great products. Visibility, customer experience, and platform mastery all play a role in turning browsers into buyers.
Ecommerce agencies step in as that extra set of hands. They handle the heavy lifting across SEO, paid ads, conversion rate optimization, design, and retention so you can focus on keeping your business upright and your capital from bleeding dry.
In this guide, we’ll cover what ecommerce agencies actually do, how to know if it’s time to hire one, what makes a ‘best’ agency stand out, and seven agencies in the U.S. worth your attention in 2025 — including ours (because, full disclosure, we’re really good at what we do).
If you’re reading this, you probably already have a sense of what an ecommerce agency does. Still, let’s not skip the basics.
An ecommerce agency is a specialized partner built to help online stores grow faster, smarter, and with fewer headaches. Unlike general digital agencies, ecommerce agencies focus specifically on the unique demands of online retail.
That means:
They’re measured by commerce-specific metrics like average order value (AOV), lifetime value (LTV), return on ad spend (ROAS), and retention — not just traffic or impressions. All of this is to say an ecommerce agency’s job isn’t finished once visitors land on your site. Their role is encouraging those visitors to stick around and actually buy something.
We’re not going to sugarcoat it: Hiring an ecommerce agency isn’t cheap. But the right one can more than pay for itself by uncovering growth opportunities you didn’t even know existed. It’s like figuring out which wire to cut on a ticking bomb after watching one YouTube tutorial. Technically possible, but maybe bringing in a professional would be safer?
In other words, the benefits go way beyond saving time (though that’s nice, too). Here’s why brands turn to ecommerce agencies in 2025:
Without checking any listings, we’re pretty confident in telling you that there are thousands of agencies out there ready to take your call. But what separates the good from the genuinely great? Flashy websites and slick pitch decks are nice, but results are what actually matter. The best ecommerce agencies prove their worth by showing exactly how they’ve helped brands move the needle.
Not every agency that slaps ‘ecommerce’ on its homepage is worth your budget. The best agencies share a few traits:
Statista projects that worldwide ecommerce sales will hit roughly $3.66tn by the end of 2025. And, if you’re like me and don’t immediately recognize ‘tn’ as a unit of measurement, it stands for trillion (12 zeroes). That’s a lot of potential growth; having a dependable agency by your side can help your business carve out its share instead of getting buried under everyone else’s.
You made it. This is the list you came here for. These seven agencies stand out in 2025 not only for their services, but for their ability to deliver measurable, platform-specific results. We’ll cover who they’re best for, what services they offer, and what makes them different in a crowded space.
Best for: Integrated growth across SEO, paid, and conversion optimization
Most agencies promise growth. 97th Floor has made a business of proving it. With deep roots in content, SEO, and analytics, 97th Floor doesn’t just help ecommerce brands ‘get more traffic’ — they work with you to align every marketing channel to generate more sales, more efficiently.
97th Floor is a full-service growth agency with a knack for turning ecommerce complexity into measurable outcomes. Their bread and butter includes:
If you want a partner that doesn’t just tweak one channel but instead pulls the whole system into alignment, 97th Floor is a top choice.
Best for: Content-driven ecommerce growth
Content is king, but only if it ranks — otherwise it’s just some obnoxious court jester that capers around the digital courtyard juggling outdated keywords (don’t mind me; just stress testing a metaphor). Siege Media built its reputation on creating research-backed, SEO-optimized content that ecommerce brands can use to win organic visibility. If you’re tired of writing blog posts that nobody reads, this is an agency that can change the story.
Strengths include:
If organic growth is your north star, Siege is the kind of agency that can help you outrank competitors without relying solely on ad spend.
Best for: Platform migrations and storefront optimization
Technology can be a brand’s biggest advantage — or its biggest bottleneck. 1Digital® Agency specializes in fixing that problem by making sure your storefront is fast, functional, and scalable, no matter which platform you’re on. Whether you’re moving from Magento to Shopify, need a WooCommerce overhaul, or want to unify your BigCommerce setup, they’ve been there.
They offer:
Overall, 1Digital® Agency is a good fit for brands with growing pains tied to their tech stack.
Best for: ecommerce SEO at scale
SEO may not be flashy, but it’s the backbone of sustainable ecommerce growth. WebFX has built a reputation on measurable outcomes, particularly around SEO. They’re a fit for ecommerce brands that want more organic traffic and are ready to invest in long-term visibility.
Services include:
They’ve worked with thousands of clients and have the scale to match complex ecommerce needs.
Best for: Amazon and marketplace strategy
For many brands, Amazon is both an opportunity and an obstacle — massive reach, sure, but also high fees, fierce competition, and limited control over the customer relationship. Nuanced Media helps navigate that complexity by giving you a strategy not only for your own storefront, but also for Amazon, Walmart, and other marketplaces where your customers are already shopping.
Highlights:
Great for brands that want to diversify beyond their own dot-com.
Best for: Conversion rate optimization and UX
If you’ve ever looked at your analytics and thought, Why aren’t more people buying? Inflow is the agency built to answer that question. They specialize in conversion rate optimization and user experience, making sure the traffic you already have does more heavy lifting.
Core strengths:
Traffic is great. Conversions are better. If your store has healthy traffic but underwhelming conversions, Inflow is a CRO partner to look at.
Best for: Performance marketing and paid growth
Growth often comes down to how well you spend your ad dollars. Upgrow focuses on performance marketing — paid search, paid social, and scaling strategies — so ecommerce brands can grow quickly without throwing money into the void.
They offer:
For ecommerce brands ready to put budget into scaling, Upgrow brings the paid expertise to do it properly and profitably.
This has been fun, hasn’t it? I mean who doesn’t love a good listicle. But it's worth recognizing that knowing who the top agencies are is only the first step. The real challenge is figuring out which one you actually want a long-term relationship with. You’re not swiping for a quick fling here — you’re looking for a partner who won’t ghost you when the budget conversation gets awkward.
Not every agency offers every service, but most ecommerce specialists fall into one or more of these categories. Think of it like a restaurant menu — you don’t have to order Ultimate Feast, but it’s good to know whether crab is available and if the lobster is fresh.
The service menu is broad, but most ecommerce agencies will cover some or all of these areas:
Do you need all of that? Maybe not. But if you’re building a working relationship with an ecommerce agency, then it might be a good idea to find one that can do everything in case your needs evolve somewhere down the line.
We sell ecommerce services, so maybe we’re not the most objective source to be asking. But we also get it: in an economy like this one, it doesn’t make sense to invest in something you might not need. If that’s you, and you’re wondering if ecommerce is the next step for your business, consider asking yourself the following questions:
In the ‘in-house vs. agency’ debate, the tipping point usually comes when you realize a single marketing hire can’t cover the breadth of expertise you need. Agencies provide a full team of specialists for the cost of one or two more employees.
At this point, you know what ecommerce agencies do, you know what makes a great one, and you know which names stand out in 2025. So why should you consider 97th Floor? The short answer: because we choose not to focus on optimizing channels and instead put our expertise to work optimizing outcomes.
97th Floor has helped ecommerce brands grow by aligning creative, technical, and analytical expertise into a single strategy. Our teams handle everything end-to-end:
At 97th Floor, the goal isn’t isolated channel wins. The goal is connecting those wins so they push the whole business forward (metaphorical cats and all).Ready to scale smarter? Let’s talk. Contact 97th Floor today to see how we can help your ecommerce brand grow in 2025 and beyond.
You’re busy running a business, and you shouldn’t have to spend so much effort figuring out the ins and outs of the marketing industry. When you partner with a marketing agency, they can handle understanding complex buying cycles, nurturing leads, SEO, content marketing, and ultimately delivering measurable results. A B2B marketing agency can specifically help companies that make products for other companies, instead of for the general public.
Whether your goal is to accelerate pipeline growth, expand into new markets, or enhance customer engagement, partnering with the right B2B marketing agency can turn your marketing investment into tangible, revenue-generating outcomes. Read on to learn more about working with a B2B marketing agency and how to find the right one.
A B2B marketing agency is a specialized firm focused on helping businesses market their products and services to other businesses rather than individual consumers. Unlike B2C agencies, which often prioritize mass reach and broad engagement to help you find customers, B2B agencies are designed to reach companies and target top decision-makers in order to draw clients to your company. The agency will work on generating high-quality leads and strengthening your brand in the spaces where your potential clients are.
A B2B marketing agency usually covers a wide spectrum of services, including content marketing, digital campaigns, marketing automation, analytics, and account-based marketing (ABM). At the core of their work is brand positioning—helping companies articulate their value proposition, differentiate from competitors, and establish authority in their markets.
Below are industry-recognized agencies, each with a unique strength to help you compare and choose.
Best for Full-Funnel Strategy & ROI-Driven Growth
97th Floor specializes in full-funnel marketing strategies, combining SEO, paid media, content marketing, and design services. We generate sustainable growth for B2B companies from startups up to the Fortune 500 list—including Salesforce, AT&T, LG, Google, and Celebrity Cruises. Our in-house proprietary tool, Palomar, also helps inform strategy with real-time market intelligence and competitive insights.
Best for SEO + Content Marketing
Siege Media is known for high-quality, keyword-driven content that improves rankings and conversions in SaaS, fintech, and e-commerce sectors. They focus on creating content that drives organic traffic and builds brand authority.
Best for Performance Marketing
Directive Consulting is an expert in paid media, SEO, lifecycle marketing, and demand generation within complex SaaS and enterprise markets. They elevate the focus of B2B marketers from MQLs to qualified pipelines.
Best for Agile Tech Company Marketing
New North excels in multi-channel strategies tailored for tech firms, combining agility with long-term strategic planning. They help B2B technology companies grow with better marketing and offer personalized strategies and dynamic campaigns.
Best for Lead Generation & ABM Strategy
Ironpaper focuses on data-driven demand generation, content sprints, ABM, and conversion optimization for tech clients. They align marketing and sales to drive measurable outcomes.
Best for AI-Enhanced Growth Marketing
Avenue Z combines narrative clarity, AI visibility strategies, and CRM-integrated campaigns for enterprise and professional services. They position brands at the top of their category by turning complex offerings into digestible thought leadership.
Best for Research-Driven Campaign Design
Elevation B2B delivers omnichannel campaigns rooted in strategic insights for brand awareness, lead generation, and growth. They focus on providing full-service, data-driven marketing solutions specifically for B2B companies in tech.
Best for Professional Services Thought Leadership
Hinge Marketing specializes in branding and marketing strategies tailored to professional services firms. Their research-driven approach and emphasis on thought leadership help build authority and pipeline impact.
Best for Holistic Digital Campaigns
Power Digital delivers SEO, PPC, content marketing, and social media with data-driven precision and proven lead-gen results. They offer a comprehensive suite of services to drive growth and optimize marketing ROI.
Best for Visual Brand Storytelling
Column Five are experts in brand strategy, content, data visualization, and multimedia—especially for SaaS and tech brands wanting engaging storytelling assets. They focus on creating compelling narratives that resonate with target audiences.
A B2B marketing agency offers specialized services designed to address the unique challenges of marketing products and services to other businesses. At the heart of effective B2B marketing is creating a marketing strategy that aligns with your business objectives. Agencies collaborate with you to develop comprehensive plans that encompass market research, competitive analysis, and customer insights to create this strategy and help you achieve your goals.
B2B marketing agencies provide a suite of services tailored to the intricate needs of business-to-business marketing, usually including:
B2B marketing agencies can help your company grow thanks to a combination of strategic planning, technology, and data-driven execution. Their focus is attracting great and promising leads and also nurturing those relationships. Below are three ways working with a B2B marketing agency can help your company find the growth you’re looking for.
A core function of B2B marketing agencies is identifying and nurturing high-quality leads. They focus on marketing qualified leads (MQLs)—prospects who have shown interest or engagement with your brand—and work to convert them into sales qualified leads (SQLs), who are ready for direct sales engagement. By aligning marketing and sales efforts, agencies ensure a smoother handoff and higher conversion rates.
B2B marketing agencies often use automation and CRM tools like HubSpot, Marketo, and Salesforce to manage campaigns, track prospect interactions, and deliver personalized messaging at scale. Automation allows agencies to nurture leads while also reducing manual work, so you can see results.
To demonstrate impact and optimize strategies, agencies employ marketing attribution models that track performance across all touchpoints your company needs. These models help your business understand which campaigns, channels, and messaging strategies contribute the most to revenue generation. By analyzing ROI and attribution data, agencies can continuously refine their tactics and help you create a great budget that leads to measurable growth.
Selecting the right B2B marketing agency is the first step to getting the results you want to see. The best partnerships are built on expertise, alignment, and trust, so it’s important to ask the right questions and look for key indicators of reliability. Here are some tips to help you pick out the right fit for you.
Before committing, consider asking potential agencies questions that reveal their capabilities, approach, and fit with your business:
A trustworthy agency demonstrates transparency, flexibility, and proven results. Look for clear reporting practices, adaptable engagement models, and a track record of delivering measurable growth for clients. Ask for case studies and see if this agency’s strategies and efforts would work for your company.
When choosing an agency, avoid making decisions based solely on cost. Sometimes it’s worth paying more for a higher quality B2B agency where you’ll see results. Also consider whether or not the agency will be a cultural fit for your company—just as you would for an employee. Taking the time to vet agencies thoroughly ensures a partnership that drives real results.
For more guidance, read our full Agency Success Playbook for in-depth tips on selecting a high-performing B2B marketing agency.
B2B marketing agencies can help a wide range of industries grow, but certain sectors see especially strong results.
For technology and SaaS companies, marketing agencies focus on subscription models, reducing churn, and increasing customer lifetime value—all of which can help your company grow. They implement targeted campaigns, content strategies, and ABM approaches to engage decision-makers and accelerate adoption.
Learn more about SaaS industry marketing
Learn more about cybersecurity marketing
Manufacturing and industrial businesses often face long sales cycles and niche target audiences. B2B marketing agencies help these companies identify and engage the right buyers, craft tailored messaging, and build campaigns that support complex buying decisions.
Learn more about construction equipment marketing
Learn more about industrial sector marketing
Professional services and healthcare organizations rely heavily on authority and trust. Agencies in these sectors focus on thought leadership, content marketing, and reputation-building strategies that demonstrate expertise and credibility to prospective clients.
Learn more about financial services marketing
Learn more about health and wellness marketing
Want to see how B2B marketing can transform your company? Here are a few case studies to get you started:
See more success stories to get an idea of how a B2B marketing agency can help you.
Measuring success is critical to understanding the impact of your B2B marketing efforts and optimizing for growth. Agencies use a combination of quantitative and qualitative metrics to track performance, inform decisions, and maximize ROI.
97th Floor is a trusted partner for B2B companies looking to drive measurable growth through strategic, data-driven marketing. With proven expertise across digital marketing disciplines—including content, SEO, paid advertising, design, and emerging AI-powered SEO tactics—our team helps businesses generate leads, accelerate pipeline growth, and maximize ROI.
We prioritize transparent communication and consistently deliver results backed by analytics, so that every campaign is aligned with your business objectives. What sets 97th Floor apart is our deep industry experience combined with flexible engagement models. We tailor strategies to your unique needs and scale as your business grows.
See how an audience-first approach translates to bottom-line results.
Curious about how to get your brand noticed on Perplexity Search? You’re not alone. With Apple’s rumored acquisition of Comet making headlines, marketers everywhere are wondering if this AI-powered browser might be the next big thing in search. Whether you’re here to stay ahead of the curve or simply want your site to pop up in more AI-driven answers, you’ve come to the right place. Let’s dive into what makes Perplexity tick—and how you can use it to your advantage.
More than 2-thirds of smartphone users in the United States use an iPhone as their smartphone of choice. About 50% of all internet traffic starts on a mobile device in the United States. Being the default browser and search engine for 68% of half of all internet usage in the United States sounds pretty great right? That might be the reality for Perplexity and their new browser, Comet, as Apple is currently determining if they will go through with the 14 billion dollar acquisition. That is an eye popping amount of money for an acquisition of a company that has never turned a profit (actually lost $65 million in 2024). However it could be a leap forward in AI development for Apple who is severely behind its big tech competitors.It would also mean a real threat to Chrome and less reliance on using Google products on Apple devices. A true threat to Google Search is something that Google has not experienced in decades. The threat is given even more credibility by the fact that Comet is actually quite good and those who have tested it rave about the AI-enhanced browser with built in perplexity search engine. Even if the acquisition from Apple does not go through, it is interesting enough of a search product to look into ranking organically on the Perplexity search and optimizing web content for LLMs in general as the jump in AI-search queries has increased from 250m to 1.1 billion in the last year alone!
In one of our tests, we found that the top ranking page on Google, for non-branded terms, was never the same as the top result in Perplexity. Even more alarming was that each 1:1 query resulted in 85% unique results across Google and Perplexity. While there will be some principles of Search Engine Optimization that remain the same, the results are different enough that a close examination of the top ranking factors for perplexity was necessary. After analyzing SERPs using queries and prompts from multiple industries on Perplexity, we have compiled our top ranking factors for Comet, and the Perplexity search engine here.
The best way to strategize for Perplexity Search is to like traditional SEO, break it out into on site, or on domain optimizations and off page or off domain optimizations. Only off page and on page optimizations don't mean quite the same thing for LLM optimizations as they do for traditional SEO. Below are the most impactful on page and off page optimizations for perplexity search.
From tests we have been running with our clients, we found that the first place that an LLM bot will go to find information about your brand and how it fits into the market, is by analyzing the brand’s own domain. The home page, about us page, any solutions, services or product descriptions, are all very common sources of information for the Perplexitybot and other LLMs. Which is great news for marketers and website managers, that is owned content that is generally very easy to optimize. The LLM will go to your brand’s domain for information about what you do and who you serve, then look to external sources in your industry to back up the claims you made on your own domain. The following are off page optimizations that will boost your presence when your audience is searching on Comet.
Perplexity user experience is much different than OpenAI GPT, Google’s Gemini, or Claude, primarily in its use of source cited and clickable elements in the generative responses. If traffic is still a metric SEOs and website managers are interested in increasing, Perplexity winning the AI race seems to be the best chance website owners have at seeing increases in referral traffic. So how is optimizing for Perplexity Search? Here are a few things to consider:
The team at 97th Floor is doing the work to find every opportunity to increase brand awareness on new and tried and true platforms. Perplexity’s new browser, Comet, has real potential to be a widely used search engine and make a dent into Google's Search market share dominance. When and if that happens, we will be fully prepared to optimize for Comet. Lets connect, our team will do an AI-search competitive analysis for your brand free of charge, to identify opportunities in AI search and if your audience is already adopting Perplexity Search and using the Comet Browser.
Use these free tools to unburden your site of low-value content that prevents an LLM from understanding your brand. Watch your SEO performance skyrocket.
If you have Googled anything in the last few years, you’ve likely come across an AI overview that summarizes some of the ranking pages to answer your query. Or maybe you wondered about the history of the Ottoman Empire or needed instructions to refill your car’s oil and turned to ChatGPT. AI is taking online search by a storm.
For search engine users, the rise of AI has made getting synthesized summaries of all the top internet easy. For companies and SEO experts, it involves figuring out how to adjust your content strategy to keep your content visible and to reach your customers. That’s why we’ve put together this guide on the future of AI search SEO to help you figure out where and how to tweak your content strategy to be ready for the growth of AI SEO.
Unlike traditional search engines that rely on keyword matching and indexed pages, AI-powered systems use large language models (LLMs) to interpret natural language in an attempt to deliver nuanced, conversational results.
Some of the leading AI search tools you may have used or heard of include:
Search is undergoing a fundamental shift that’s only getting started. In May 2023, Google began rolling out Search Generative Experience (SGE), now rebranded as AI Overviews, which places AI-generated responses above standard results. Microsoft integrated AI mode into Bing in early 2023 using ChatGPT-4, while platforms like You.com and Perplexity launched AI-first search tools that prioritize summarization and citations. Search engines now are prioritizing their own AI summaries at the top of the SERP in what used to be prime real estate for SEOs.
These AI tools are changing the way people interact with SERPs. In fact, a study from the Pew Research Center in May 2025 notes that people are significantly less likely to click on web pages listed in Google search results if there’s an AI summary present. They also only rarely click on the sources listed by the AI summary.
With the shift in how users interact with search engines, SEO is going to shift too.
Traditional SEO is built around optimizing for search engine crawlers and ranking within standard SERPs. This includes tactics you’re likely very familiar with, such as:
GEO—Generative Engine Optimization—targets AI searches. Large Language Models don’t crawl; they try to interpret the context and evaluate:
Because LLMs respond to context and credibility, not just ranking signals, you want to optimize content for semantic relevance, not just visibility. Adding GEO to your content strategy is another way to make your content visible in those AI-generated summaries—though traditional SEO still matters as well.
So if AI is going to change the way people search (and already is starting to do so), you need a content strategy designed to fit in that landscape. These are our four top tips for creating content that your readers will love and that works with AI.
Content these days has to walk a very fine line: being written for humans and for AI accessibility all at the same time. You don’t want to write a brilliant piece of long-form content only for it to be lost in the ether of Google, but you definitely don’t want to end up with AI slop. Some ways you want to cater your content for your readers and for AI include:
The goal here is to write content for your human audience but to make sure it’s fully AI accessible afterward. At the end of the day, good content is still king, so prioritize having well-written content and avoid losing that human touch while optimizing for AI search SEO.
AI works like any other search engine: it will rank your pages higher if they’re correctly set up with appropriate metadata. While AI tools don’t crawl the web like traditional bots, they still rely on structured, well-maintained websites. Technical SEO helps ensure your content is indexed by both search engines and used by AI models that reference top-ranking pages. Prioritize:
Just like with Google Search, AI systems reward content that’s well-structured and technically sound.
Optimizing for search engine results page (SERP) features can improve your visibility in both traditional and AI-generated summaries. Focus on:
Appearing in these SERP features improves your chances of being referenced by AI models—and therefore coming across your readers’ screens.
If you’re looking to build your pages in a way that makes it easy for AI tools to scan your content, focus on these five strategies:
By following these principles, your content becomes easier for AI models to recognize—which then helps you stay visible in the next era of online searches.
Even though it might feel like the search landscape is rapidly evolving, the core principles of technical SEO remain as important as ever. In fact, SEO hasn’t really changed—it’s only expanded to include AI searches. Staying on top of and implementing foundational technical best practices still pays dividends, both in traditional rankings and in AI-generated search results.
Structured data helps both traditional search engines and AI systems better understand the context of your content. Using it can help your content get featured in snippets and AI overview citations. To get the most out of your structured data:
Well-implemented schema makes it easier for AI systems to identify key facts and understand the relationships between ideas—boosting your content’s chances of being referenced in AI search results.
AI-powered search is no longer limited to just text, and your content strategy can capitalize on that. Many search engines and AI assistants now support multimodal inputs and outputs to blend text, images, and video to meet user needs. Make sure your site:
By incorporating diverse formats, you increase your visibility across a variety of SERP features. Your site could end up as the cited image in an AI overview or in an image carousel. That visibility will make your content more accessible and expand your reach.
All the general tips we’ve talked about so far are best practices for any type of AI search tool. While many core principles remain consistent, each model has its unique behaviors and ranking preferences. Some of the most prominent and widely used AI search engines—and the ones offering the most trackable performance insights today—include:
AI systems reward conversational content that mimics how people talk, so here are a few tips to optimize for conversational queries and natural language prompts:
By tailoring your content for the nuances of each platform—and optimizing for how people naturally ask questions—you’ll increase your visibility in both AI-driven and traditional search environments.
Traditional SEO tools may not yet offer complete coverage of AI-driven search experiences—but a new wave of reporting solutions is emerging to bridge the gap.
There are a lot of SEO metrics, but which ones matter for AI search SEO? Key metrics to focus on include:
Since AI search focuses more on credibility and relevance than on traditional rankings, visibility can come in the form of mentions and summaries rather than blue links.
While AI searches are still relatively new, there are tools that are adapting to help you keep track of your most important metrics:
As AI search adoption increases, expect more tracking solutions to emerge. Just like SEO matured with its own analytics stack, AI SEO reporting will become a core part of modern marketing analytics within the very near future. Start experimenting with these tools now to stay ahead of the curve and get a head start above your competitors.
Working with AI to produce AI-optimized content is increasingly essential. Modern AI systems—like ChatGPT, Gemini, and MarketMuse—can help you with identifying content gaps and topic clusters that you can write about, speed up the drafting process, and create content outlines for you.
Don’t think of AI replacing your content creators. Instead, pair AI with human experts to speed up the content creation process without losing what makes human-written content great.
Another way to AI-prep your content strategy is to apply the hub and spoke model. The hub and spoke model is a content architecture that creates a central “hub” page targeting a broad, high-value topic, supported by multiple “spoke” pages that address related subtopics in depth. Each spoke links back to the hub and to one another.
For example, when Maveneer came to 97th Floor in 2023, they wanted content that would rank, so we gave them a hub and spoke strategy with comprehensive overview hubs targeting keywords like “warehouse automation” and “order picking.” After establishing those hubs, we could expand to spokes with drill-down articles like “order picking technology” and “automated sorting systems” linked to and from the hub. This structure improves internal linking, site navigation, and topic authority to search engines and AI systems alike. In fact, for Maveneer, their domain authority R skyrocketed from 3 to 34, and they saw an 886% increase in search impressions YoY.
Search is evolving—and fast. More people are relying on AI to answer their questions and give them potential solutions. With AI browsers popping up, there are only going to be more AI search developments. These platforms don’t just display a list of blue links. Instead, they generate dynamic responses by pulling insights from multiple sources, often without traditional attribution or visible rankings.
For enterprise brands, this shift has major implications.
In this new paradigm, visibility isn’t just about ranking #1—it’s about being referenced, cited, or summarized by AI models at the moment a customer asks a question. Failing to adapt means losing organic visibility at critical touchpoints—especially early in the customer journey when buyers are still gathering information.
Enterprise brands that invest in AI search SEO now can make sure they’re ahead of the curve and stay visible. AI isn’t replacing internet searches—it’s reshaping it. And enterprise brands that evolve their strategies now will be best positioned to lead out in the next era of SEO.
If you're ready to show up in AI-generated results, let's build your strategy.
