Google isn’t going anywhere. But it’s no longer where your audience spends most of their search behavior.
They’re on TikTok looking for product recommendations. On Reddit hunting for honest reviews. On YouTube for how-tos. On ChatGPT and Perplexity for quick answers that skip the blue links entirely.
And when you factor in all those platforms, Google’s US market share drops closer to 70%, not the 90%+ figure that gets thrown around. That gap is where visibility is being won and lost right now.
Search Everywhere Optimization is the practice of building that visibility across every surface where your audience looks for answers, not just Google.
This guide covers what it is, which platforms actually matter, and how to build a strategy that works across them all. We’ve written it for agencies that need to understand, explain, and deliver it, and for brands that need to implement it.
Key Takeaways
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- Search has fragmented. Different queries now default to different platforms. Product discovery happens on TikTok, reviews on Reddit, quick answers via AI chatbots, and tutorials on YouTube.
- Google’s real market share is lower than you think. Factor in social, video, and AI search surfaces, and it drops closer to 70% in the US. One platform is not a strategy.
- Search Everywhere Optimization is about presence, not just rankings. It means showing up across every surface your audience uses to find answers.
- The AI/LLM layer is the fastest-growing search surface, and the one agencies are largely ignoring. ChatGPT, Perplexity, and Gemini are not a niche.
- A credible strategy has six steps: audit cross-platform visibility, map intent to platform, fix technical foundations, create adaptable content, build off-site authority, and track AI visibility separately.
- For agencies, this is both a risk and an opening. Clients are already asking about AI search and Reddit. The question is whether you can answer.
What Is Search Everywhere Optimization?
Search Everywhere Optimization is the practice of building brand and content visibility across every platform where people search for information, not just Google.
It’s the evolution of traditional SEO for a world where search behavior is spread across social platforms, video, AI-generated answers, app stores, and marketplaces.
Traditional SEO had one job: rank on Google. That was a reasonable approach when Google handled the vast majority of discovery. But search behavior has changed.
The same user who Googles a product comparison might discover it first on TikTok, verify it on Reddit, and ask ChatGPT to summarize their options before they ever click a link. Search Everywhere Optimization is built around that reality.
It’s worth being precise about what this isn’t.
Omnichannel marketing is about maintaining a paid and organic presence across multiple channels.
Search Everywhere Optimization is specifically about search and discovery, the moments when someone is actively looking for something.
The optimization approach is completely different depending on where and how that search happens. Same goal, different playbook on every platform.
The scope includes Google Search, AI Overviews, and Discover. But it also covers YouTube, TikTok, Reddit, Amazon, app stores, and AI tools like ChatGPT, Perplexity, Claude, and Gemini. Each surface has its own signals, formats, and ranking logic. A strategy that doesn’t account for that isn’t really a strategy. It’s just one channel with good intentions.
💡 Search Everywhere Optimization is the strategy of building visibility across every surface where your audience actively searches for answers, from Google and YouTube to AI chatbots, social platforms, and marketplaces. It goes beyond traditional SEO to treat search as a behavior, not a channel.
Why Search Has Fragmented
Search didn’t move to one new platform. It splintered across several, and the split follows intent.
The same person uses all of these. Maybe not in the same session, but across the same purchase journey. They find a product on TikTok, check Reddit for honest takes, ask Perplexity for a quick comparison, then navigate to the store on Google Maps.
That’s one customer, five platforms, zero of them optional, if you want to be present at every touchpoint.
And it’s not just younger users. The shift is broader than the Gen Z narrative suggests. Adobe’s 2026 search survey found that 29% of consumers now use Reddit for search, 26% use ChatGPT, and 24% use YouTube. These aren’t niche behaviors; they’re mainstream.
The intent split matters too. People don’t randomly pick a platform. They go where they expect the best answer for that type of question.
Nobody asks Reddit for driving directions. Nobody asks Google Maps for honest product reviews. The platform choice is deliberate, even when it’s instinctive. Which means a brand that only shows up on Google is only answering one type of question. Every other intent category is an open door for a competitor.
Agencies built their delivery around Google. AI tools went from novelty to daily habit faster than anyone predicted, and that model hasn’t kept pace. We broke down what that looks like in practice in AI Changing Search: Lessons from NY Tech Week.
If your reporting leads with keyword rankings and organic traffic from Google, you’re showing clients a partial picture.
Steve Cooper, Senior Content Specialist at SUSO
A competitor who ranks below you on Google but dominates Reddit discussions and gets cited in AI answers is taking a share of the journey you’re not even measuring.
Clients are starting to ask. Some are already being told by other agencies.
Where Search Actually Happens Now
| Platform | Primary intent | Key audience | Optimization levers |
| Google Search / AI Overviews / Discover | Information, comparison, navigation | Everyone | Technical SEO, E-E-A-T, structured content, schema |
| ChatGPT, Perplexity, Gemini, Claude | Quick answers, research, and summarization | All ages, growing fast | Authoritative content, citations, brand mentions, structured data |
| YouTube | How-to, tutorials, reviews | Broad, skews 18-45 | Titles, descriptions, chapters, transcripts |
| TikTok and Instagram | Product discovery, inspiration | Under 35 | Captions, on-screen text, engagement signals |
| Reddit and UGC platforms | Reviews, recommendations, community | Research-stage buyers | Authentic participation, brand mentions, and forum presence |
| Amazon and App Stores | Purchase, download | High commercial intent | Product copy, reviews, keyword-optimized listings |
Google (Search, AI Overviews, Discover)
Still the highest-volume search surface by a distance. But what it means to rank on Google has shifted.
AI Overviews now appear on roughly 50% of US searches. Getting cited in an AIO is the new position one. You can rank third organically and still lose the click to a competitor whose content gets pulled into the summary at the top of the page.
Traditional SEO signals still apply. But content structure, topical authority, and E-E-A-T signals are now the price of entry for AIO inclusion, not just nice-to-haves.
AI Search (ChatGPT, Perplexity, Gemini, Claude)
The fastest-growing search surface, and the one with the largest gap between its importance and how seriously agencies are treating it.
LLMs don’t crawl and rank the way Google does. They synthesize answers from content they’ve been trained on or can access, pulling from sources that are authoritative, well-structured, and widely cited. If your brand isn’t appearing in those answers, you’re invisible to a growing share of queries, and you probably don’t know it yet.
This is where Search Everywhere Optimization intersects most directly with Generative Engine Optimization. For a deeper look at optimizing across multiple LLMs specifically, see our piece on Multi-LLM Optimization.
YouTube
The second-largest search engine in the world, and the one brands most consistently treat as a social channel rather than a search one.
Video content ranks inside YouTube and inside Google. A well-optimized video can take a Google SERP position that a blog post never could. Titles, descriptions, chapter markers, and transcripts all function as indexable SEO signals. Ignore them, and the visibility layer stays closed.
There’s also a compounding effect worth understanding. Video content that ranks builds watch time, which builds channel authority, which improves ranking for future content. It’s a slower burn than blog SEO but tends to be more durable.
And with AI Overviews increasingly pulling from YouTube transcripts to answer how-to queries, the case for treating it as a search channel has never been stronger.
TikTok and Instagram
The primary product discovery surface for under-35 audiences. When someone that age wants to find a restaurant, a product, or a brand recommendation, TikTok or Instagram is often the first stop, not Google.
Optimization here works differently. It’s less about keywords and more about engagement signals, captions, on-screen text, and how the algorithm reads early interaction with a post. The content that gets found looks native, not produced.
Reddit and UGC Platforms
Reddit has quietly become one of the most influential search surfaces on the internet. It ranks heavily in Google for review-type and “best X” queries, and it’s one of the most frequently cited sources in AI Overviews.
Brands with no presence in community conversations are missing a visibility layer that’s hard to buy your way into. Mentions in subreddits and forums influence both Google rankings and LLM training data. Authentic participation matters more than any paid placement.
The other thing worth knowing: Reddit’s influence on AI answers is disproportionate to its size. LLMs treat community consensus as a form of social proof. If your brand is being discussed positively in relevant subreddits, that signal feeds into how models describe and recommend you. If it’s not being discussed at all, or discussed negatively, that feeds in too.
Amazon and App Stores
For product and software brands, platform-native search is often the primary discovery mechanism. Someone searching “wireless headphones” on Amazon isn’t going to Google first. If you sell on Amazon, Amazon SEO is the whole game on that surface. The same applies to app store optimization for software products.
How to Build a Search Everywhere Optimization Strategy
These are the best practices for Search Everywhere Optimization that hold up regardless of which platforms you prioritize. Work through them in order as the steps build on each other.
Step 1: Audit Where You’re Already Visible (And Where You’re Not)
Brands rarely have a clear picture of how they appear outside Google. That’s the first problem to fix.
Run a visibility audit across platforms. Search your brand name and core queries on YouTube, Reddit, TikTok, and Amazon.
Then do the same in the AI layer. Type your target queries into ChatGPT, Perplexity, and Gemini. Is your brand mentioned? Cited accurately? Missing entirely? Getting misrepresented?
That last one matters more than people think.
LLMs can confidently say wrong things about your brand, and you won’t know unless you check.
Steve Cooper, Senior Content Specialist at SUSO
For a practical framework on approaching this, see AI Search Visibility: You Can Measure It. Once you have a baseline, How to Track AI Traffic in GA4 covers the next step.
Step 2: Map Intent to Platform
Don’t try to be everywhere at once. You’ll spread effort thin and do nothing well.
Instead, identify which platforms your audience actually uses at each stage of the journey, then prioritize by three factors:
- Audience match: Are your buyers actually there?
- Commercial intent: Does search on this platform lead to decisions?
- Current gap: Where are you invisible that you shouldn’t be?
That stack tells you where to start. Build from there.
Step 3: Fix Technical Foundations First
There’s no point optimizing for additional surfaces if your site has fundamental issues. Crawl problems, slow load speed, and blocked AI bots will undermine everything else.
Structured data and schema markup are prerequisites, not optional extras, especially for LLM visibility. Models need clean, well-structured content they can parse and attribute. If your site is technically a mess, it won’t get cited.
One question that comes up constantly with clients is whether they should block AI bots or not. We covered that directly in our article Should You Block AI Bots from Your Website?
Step 4: Create Content That Works Across Surfaces
A single well-researched piece of content shouldn’t just live as a blog post. It can become a video script, a social short, a Reddit answer, or a podcast summary. The research is done once. Distribution is where the investment usually falls short.
For the AI layer specifically, content needs to be factual, clearly structured, and backed by authoritative sources. Write for the model as well as the human reader. That means clear definitions, cited claims, and logical structure. Not vague thought leadership.
How Digital PR and Technical SEO Impact AI Search Visibility goes deeper into how these two disciplines combine to drive LLM presence.
Step 5: Build Authority Off-Site
Backlinks still matter for Google. But for the AI layer, the signal is broader. Earned media coverage, expert commentary, and brand mentions (even unlinked ones) all feed into how LLMs perceive and represent your brand.
A brand that gets written about by credible publications, cited in industry discussions, and referenced in community forums builds the kind of footprint that AI models draw from. Digital PR isn’t just an SEO tactic anymore. It’s an LLM visibility tactic.
See Escape the Link Building Graveyard: Off-Site SEO for Brand Visibility for a practical take on this shift.
Step 6: Track, Measure, Iterate
Google Analytics, Search Console, and standard rank trackers don’t tell the whole story. They can’t show you whether you’re being cited in AI answers or how your brand appears in ChatGPT responses.
Set up GA4 source tracking to capture AI referral traffic. Run regular prompt tests in your target LLMs. Search your key queries and audit the results monthly. There are special AI visibility trackers that can help you automate this process. Treat AI visibility as a metric you report on, not a vague aspiration.
How to Track AI Traffic in GA4 is the practical starting point.
What This Means Specifically for Agencies
Client conversations have changed. Where briefs used to focus on rankings and organic traffic, they now include questions about ChatGPT visibility, Reddit presence, and why a competitor keeps showing up in AI-generated answers.
Clients are asking because they’re seeing the shift themselves. They want to know what you’re doing about it.
That’s pressure. And for agencies that built their entire delivery model around Google, it’s also exposure.
Search Everywhere Optimization doesn’t just expand the scope of what needs to be done. It makes visible the gap between what agencies have been delivering and what clients actually need. That gap was always there. It’s just harder to ignore now.
Steve Cooper, Senior Content Specialist at SUSO
Three Options
There’s no avoiding the decision. Agencies either:
- Build in-house. Hire and train for LLM optimization, social search, Reddit strategy, and platform-native content. Takes time, costs money, and the space is moving fast enough that staying current is a job in itself.
- Refer out. Tell clients this falls outside your scope and point them elsewhere. Honest, but it hands the relationship to someone else and leaves revenue on the table.
- Partner with a specialist. Offer Search Everywhere Optimization expertise under your own brand without building a new team from scratch. You keep the client, the specialist does the work.
SUSO operates as a white-label and co-branded partner for agencies that want to extend their offer without extending their headcount. That includes GEO, LLM visibility, and the technical and content work that underpins Search Everywhere Optimization across platforms.
The LLM Layer Is Where the Gap Is Widest
Even strong SEO teams often don’t have depth here yet. Generative Engine Optimization is new enough that in-house experience is thin across the industry. It’s a specialism, not a bolt-on to existing SEO practice.
For PR agencies in particular, the opportunity is big. PR-driven coverage and earned media are among the most powerful signals for LLM visibility.
If you’re running digital PR campaigns and not connecting them to AI search outcomes, you’re underselling the work. We covered exactly this in the PR Agency’s Tactical Playbook: AI Search Webinar.
The agencies that move on this now will have a clear answer when clients ask. The ones that don’t will be referred around them.
Common Mistakes to Avoid
- Treating it as a channel strategy, not a content strategy. Posting the same thing everywhere doesn’t work. TikTok, Reddit, and Google all have different intent signals, different formats, and different ranking logic.
- Showing up on every platform without adapting to each one isn’t Search Everywhere Optimization. It’s noise. The platform is the context, and context changes everything.
- Skipping the technical layer. Content work built on a broken foundation goes nowhere. Crawl issues, poor site speed, and blocked AI bots will undermine everything above them. Fix the infrastructure before you expand the surface area.
- Ignoring the LLM layer entirely. AI-generated answers are already a primary search surface for a significant share of queries, and that share is growing. Competitors who figure this out while you’re still focused on page-one rankings will be harder to displace later. The window to get ahead of this is open, but it won’t stay open.
- Not measuring AI visibility. If you’re not tracking how your brand appears in AI-generated answers, you can’t improve it or report on it. Clients who start asking about it will get a better answer from whoever is measuring it. That could be you, or it could be someone else pitching against you.
- Trying to do everything at once. You won’t win on every platform immediately. Start where the audience-intent-gap overlap is strongest, get traction, then scale. Spreading effort across six platforms with no depth on any of them is a fast way to produce results that justify cutting the budget.
Where to Start
Search has fragmented. The brands and agencies that treat it as a single-channel problem are handing visibility to competitors who don’t.
Building a Search Everywhere Optimization strategy isn’t about doing more of the same. It’s about showing up where decisions actually get made, across Google, AI tools, video, and community platforms.
If you want to see where you stand in the AI layer right now, SUSO’s free AI Search Visibility Checker gives you a scored breakdown across the signals that matter.
For agencies looking to offer this without building a new team, join the SUSO Partner Club for free access to training, support, and SEO resources built for agency teams. For brands looking to get started, book a call with the SUSO team.
FAQs
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What is search everywhere optimization?
Search Everywhere Optimization is the practice of building brand and content visibility across every platform where people search for information, not just Google. It covers social search, video, AI-generated answers, marketplaces, and app stores. The goal is to be present wherever your audience looks for answers, regardless of which platform they use.
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How is search everywhere optimization different from traditional SEO?
Traditional SEO focuses on ranking on Google. Search Everywhere Optimization treats search as a behavior that happens across multiple surfaces, each with its own signals, formats, and ranking logic. It includes Google but goes well beyond it.
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Which platforms should I prioritize?
It depends on your audience and where they search at each stage of the buying journey. The platform table in the Where Search Actually Happens Now section maps primary intent and key audiences for each surface. Start there, identify where your gap is biggest, and build from that.
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Do I need a search everywhere optimization agency?
If your team has depth across technical SEO, content, LLM optimization, and platform-native strategy, you can build this in-house. If not, a specialist partner lets you extend your offer without extending your headcount. SUSO works with agencies as a white-label and co-branded partner, and with brands directly on GEO and cross-platform visibility.
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How do I measure success across multiple platforms?
Standard rank trackers and Google Analytics don’t capture the full picture. You need platform-specific tracking alongside AI visibility monitoring. How to Track AI Traffic in GA4 is the practical starting point for getting AI referral data into your reporting.
