What is Search Everywhere Optimization?

Search used to happen in one place. You typed a query into Google, you scanned ten blue links, you clicked one. That was the whole journey. SEO, as a discipline, was built to win that moment.

That moment no longer exists in isolation. People now ask ChatGPT for a recommendation before they ever open a browser. They ask Perplexity to summarise an industry. They ask Gemini what to buy. They get an AI Overview at the top of Google before they see a single organic result. They ask Amazon Rufus which product to add to their cart. The search surface has fractured, and your brand has to be visible across all of it — or it isn't visible at all.

That's what Search Everywhere Optimization is. It's the work of making sure your brand shows up — accurately, authoritatively and consistently — across every surface where people now look for answers.

Why a new term?

You'll hear a lot of acronyms thrown around right now. GEO (Generative Engine Optimisation). AEO (Answer Engine Optimisation). LLMO. Each one captures a slice of the work, but each one also implies that the new thing has replaced the old thing. It hasn't.

Traditional SEO is still doing the heavy lifting. Google still drives most discovery. Schema markup, site architecture, internal linking, content quality — all of that still matters. What's changed is that the same foundations now feed multiple downstream systems. LLMs train on the open web. Retrieval systems pull from indexed pages. AI Overviews surface content based on the same authority signals Google has always rewarded. The work overlaps. The audiences don't.

Search Everywhere Optimization is the umbrella term that respects that overlap. It's not SEO versus GEO. It's SEO grown up — taking responsibility for visibility wherever people actually search, not just where Google sends a crawler.

The surfaces it covers

When we say "everywhere," we mean it literally. The surfaces a brand needs to be visible across now include:

• Google organic search and AI Overviews
• ChatGPT, Claude, Gemini, Perplexity and other consumer LLMs
• Agentic shopping assistants — Amazon Rufus, Google Shopping AI, Walmart Sparky, Sephora's assistant
• Voice assistants and embedded AI inside operating systems
• Retrieval-augmented enterprise tools and vertical search engines
• Community surfaces that LLMs draw from — Reddit, Quora, Wikipedia, Wikidata
• Traditional citations and digital PR — the press and industry mentions that build authority

None of those surfaces operate in isolation. LLMs train on Reddit. Google ranks Wikipedia near the top of almost every query. Perplexity cites the same publications Google promotes. Amazon Rufus pulls from product schema. The web is one ecosystem with many windows into it.

The disciplines that roll into it

Search Everywhere Optimization isn't a new tactic. It's an integration of disciplines that have historically lived in different teams or different agencies. Done properly, it pulls together:

• Content strategy and execution. The foundation. You can't be cited if you haven't published anything worth citing.
• Technical SEO and entity work. Schema, structured data, knowledge graph alignment, site architecture, crawl accessibility for both Google and AI crawlers.
• Answer engine optimisation. The detailed content work that gets your brand named, cited and recommended inside generative answers.
• Citations, mentions and digital PR. The third-party footprint that builds the authority LLMs trust.
• Measurement. Tracking where you appear, where you don't, and what's changing across AI surfaces.
• Agentic commerce optimisation. Product content built for the assistants now influencing what ends up in the cart.

Each of these used to be its own specialism. The brands winning right now are the ones treating them as one connected practice.

Who needs it

If your customers are asking AI questions you'd want your brand to answer — and they are — you need to be working on this. That's true for DTC brands, professional services firms, B2B SaaS, publishers, retailers and almost any business that historically relied on organic search to fill the funnel.

The brands most at risk are the ones treating AI visibility as something to think about later. LLMs are training on the web right now. They are forming opinions about who the credible names in your category are right now. Catching up later is significantly harder than showing up early.

Where to start

The real answer is that it starts with knowing what your brand actually is — clearly enough that an AI model can describe it the same way twice. That's an entity problem before it's a content problem. Most brands skip this step and wonder why their visibility work doesn't compound.

If you're at the start of this work, the cheapest, fastest thing you can do is define your entity. Get clear on who you are, who you serve, what you do, and what makes you credible. Everything else — content, schema, citations, measurement — gets easier once that's in place.

That's why we built the AI Search Entity Builder. It's a free tool that helps you clarify and solidify your entity description for better AI search visibility. It takes about 3 minutes. You'll get more clarity from it than from most paid audits.