Blue Ocean SEO / AEO: Original thinking wins
Stop investing in following the herd and be original
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In my book, I dedicated an entire chapter to Blue Ocean SEO, so I would recommend reading that for the longer version of this post. To best understand Blue Ocean SEO, you first need to know what it is not.
For years, most SEO followed a predictable pattern. You open Ahrefs or SEMrush, find keywords with high search volume, see what’s ranking, and try to write something better or longer. When it mattered, you copied your competitors’ backlinks too. This is Red Ocean SEO - you are in shark infested territory.
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Red Ocean SEO isn’t original
The problem is that everyone else with a browser, a credit card, and the budget for an SEO tool can do the same thing. You end up competing over the keywords, producing similar content, and targeting the same users. This creates a crowded space where differentiation is hard, and margins compress over time.
Blue Ocean SEO works differently. It starts with a hypothesis about what users need, not what keyword tools say people are searching for. There’s no existing search volume to validate your strategy upfront. Just customer research, pain points, and understanding of your users’ journey. You create content or build product experiences that solve real problems, trusting that users will find and appreciate them when they need them. This pairs well with product-led SEO in an AI world.
AI has accelerated this shift in meaningful ways.
Three years ago, I would have recommended building content around users exploring a topic for the first time. These are people who were just starting to understand a problem or discover options, aka TOP OF FUNNEL. You’d write “What is a bill pay tool” or “How to change a flat tire” and capture people at the beginning of their journey. Many are still doing that, but with AI slop.
The biggest impact of AI is that it changes where users start. When someone has a basic question, many turn to ChatGPT or Gemini first. If they Google it, AI Overviews often give them a synthesized answer. LLMs pull from dozens of sources and give users what they need without having to click through to your high-level guide.
This creates an opportunity if you understand what it means.
By the time users get to Google now, they’re often more informed. They’re no longer at the top of the funnel, since they’ve done basic AI research. Now they’re looking for something more specific that AI can’t easily synthesize. They want something that requires actual experience or a product that solves their particular problem.
The playbook of targeting high-volume informational keywords is becoming less effective. Those queries are increasingly answered by AI. The new opportunity is understanding what users need after they’ve been informed by AI, and even within this problem set, there is a Blue Ocean.
The content that works in this environment isn’t optimized primarily for search engines. It’s built around actual user experiences and pain points discovered through customer research and product usage data. It will have ideas that don’t show up in keyword tools yet because people haven’t figured out how to search for them, or because the search volume is diffused across long-tail variations that tools can’t capture. (Check out this past post on product-led AEO.)
This requires a hypothesis about user needs and the conviction to build for them anyway. While it might feel like a big risk, it’s no riskier than creating content like everyone else and hoping to outrank them.
AI only knows what exists
What makes this approach viable in an AI age is that AI models are trained on existing content. They’re good at synthesizing what already exists, but they can’t have the unique insight that comes from running a specific type of business or serving a specific type of customer. LLMs can’t share firsthand experiences about using a product or service in ways that haven’t been documented before.
If you create something genuinely novel that addresses a real user need not being met by existing content, AI can actually become your distribution mechanism. When users ask AI about that topic, the AI may reference your content because it’s one of the few sources. You become the canonical reference in that space.
The opportunity is to create new demand categories by solving problems users have but can’t yet fully articulate. By the time competitors realize there’s an opportunity, you’ve already established authority, and Google (and other LLMs) have learned your site answers that type of query well.
The mechanics of this strategy are not new, even if the AI context is. This is exactly what we did at SurveyMonkey years before LLMs were a factor. We didn’t just optimize for survey terms with intense competition. We built product-led SEO around every possible type of survey someone might want to create. We created new categories of demand by making it easy for people to find exactly what they needed, even if they didn’t know that’s what they were looking for when they started.
This approach isn’t easy, and it carries real risks.
You have to actually understand your users. Not in the surface way, but deeply. You need to talk to them to learn what problems they’re trying to solve and where they get stuck. Find the questions they ask that aren’t being answered well anywhere else.
This is customer research, not keyword research.
The challenge is that you’re building without validating search volume data. You might create something nobody searches for because the need isn’t as widespread as you thought. That’s a real risk. You need strong signals from customer conversations, support tickets, product analytics, and user behavior to guide you. You’re making an informed bet, not a guaranteed win.
Creating experiences that can’t be easily replicated by AI because they’re deeply embedded in specific products, services, or expertise. Then, making sure people can find them when they search.
AI has validated something many practitioners already knew. Keyword-stuffed content that exists just to rank is getting less effective, but content and product experiences that genuinely serve users remain valuable.
While some are trying to maintain the same SEO tactics in a world where AI is changing user behavior, there’s an alternative.
No one can give you the best Blue Ocean SEO ideas; you need to develop them yourself.
Stop competing in crowded spaces entirely.
Find underserved needs.
Create something new.
Build for users first.
Use the accompanying workbook to brainstorm ideas
If you’re worried that there’s no keyword data to support your strategy, that might actually be a good sign. This means you’re early and you have a chance to define the space before it becomes competitive. With this advantage, you might build something that compounds over time instead of constantly fighting to maintain rankings.
Be original
In the AI era, you don’t win by being better at SEO. You succeed by being the only one answering the questions that tools and algorithms haven’t figured out yet.
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Brilliant approach. I love it!
If you are truly early, you can validate demand with the right social media strategy.
Alternatively, you probably don't need a huge amount of content if no one is yet competing.