The truth about organic search, LLM traffic, GEO, AEO and why you need one integrated strategy—not two
SEO traffic is not declining. Data across thousands of websites shows organic search traffic is flat, varying only 1-3% year-over-year. Meanwhile, LLM usage is growing 100% annually—but it's still just 1/15th the size of Google search. The pie is getting bigger, not shifting. Savvy B2B marketers don't need to choose between SEO and Answer Engine Optimisation—they need a single, integrated strategy that serves both.
Is SEO Dead? What 2025 Data Actually Shows About Search vs AI
The "SEO is dead" narrative has created unnecessary panic across marketing teams. For B2B companies investing in HubSpot and inbound marketing, understanding the real relationship between traditional search and AI-generated answers helps determine where to focus their limited resources.
The good news? Most of what works for SEO already works for AEO. The differences are narrower than the hype suggests. This guide breaks down what the data actually shows, what's genuinely different about optimising for AI answers, and how to build one strategy that wins in both channels.
What the Data Actually Shows About SEO and LLM Traffic
The gap between perception and reality on this topic is striking. Early-stage founders—who typically lack substantial analytics data—tend to believe SEO is dying because that's the prevailing narrative online. Late-stage companies with years of traffic data see something entirely different: search remains their largest or second-largest acquisition channel, and it's not declining.
Here's what the numbers actually show:
| Channel | Current Status | Growth Rate | Relative Size |
|---|---|---|---|
| Traditional Search 10 blue links |
Stable | Flat (±3%) | Baseline |
| LLM Traffic ChatGPT, Gemini, etc. |
Growing Rapidly | +100% YoY | 1/15th of search |
| Combined Opportunity Total addressable |
Both growing | Largest ever |
🔑 Critical Insight
LLM growth is additive, not cannibalising. When someone uses ChatGPT to research a purchase, they're not necessarily doing fewer Google searches—they're doing more total research. The overall information-seeking behaviour is expanding.
For companies using HubSpot with proper attribution setup, this data is visible in your own dashboards. You can see exactly where traffic originates, which is why HubSpot users tend to be less panicked about supposed SEO decline—they have the receipts. If your attribution is murky or you're seeing concerning trends, that's a HubSpot configuration issue worth investigating, not proof that search is dying.
SEO and AEO Overlap More Than They Differ
Here's something that might surprise you: most companies winning in Answer Engine Optimisation aren't doing anything specifically for AEO. They're doing good SEO, and the AEO benefits come along for free.
The fundamental principles are nearly identical. Search engines and LLMs both need to:
- Find your content (crawlability)
- Understand what it's about (semantic clarity)
- Trust that it's authoritative (signals of expertise)
- Match it to user intent (relevance)
When you nail these for Google, you've done 80% of the work for ChatGPT and Gemini too.
The Myths You Can Ignore
Several "AEO tactics" have gained traction online despite having no evidence behind them:
lms.txt
This proposed standard would help LLMs understand your site structure—sensible in theory. In practice, Google's John Mueller has confirmed: "As far as I know, no one uses it. We don't use it." Save yourself the implementation time.
Markdown Conversion
The idea that you need to convert your HTML to Markdown because "LLMs prefer Markdown" fundamentally misunderstands these systems. Multi-billion-dollar AI companies have figured out how to parse web pages. You don't need to do their job for them.
Special Technical Requirements
Beyond standard SEO best practices (internal links, schema markup, server-rendered content), there's no evidence that special technical implementations improve AEO performance.
The technical foundation for both channels is the same: make sure your content is crawlable, your pages render properly, your internal linking is logical, and your schema markup is accurate. If you're working with a HubSpot website, most of this is handled by default—though a technical SEO audit can identify gaps specific to your setup.
What's Actually Different: On-Site Content Structure
While the technical requirements overlap, there's one meaningful on-site difference: the types of questions you need to answer.
Traditional search queries tend to be short—two to five words. LLM prompts average around 60 words. People ask AI complex, multi-criteria questions they'd never type into Google because Google can't handle them well.
The Query Difference
Traditional Search Query
"best CRM UK"
LLM Prompt
"I need a CRM that integrates with Sage accounting, handles GDPR compliance automatically, works for a 50-person professional services team, and won't require a full-time admin to manage. What would you recommend?"
If your content only answers the first query, you'll rank in Google but get skipped by ChatGPT. The AI needs content that addresses specific feature combinations, integration requirements, company size considerations, and use-case nuances.
Where This Content Should Live
Help centres and knowledge bases are disproportionately cited by LLMs. They're built to explain how products work, answer specific questions, and address edge cases—exactly what AI needs when someone asks "Can [product] do [specific thing]?"
Feature combination pages that explain how your offering serves specific scenarios. Not just "Our CRM Features" but "CRM Features for Professional Services Firms" or "How Our CRM Integrates with UK Accounting Software."
Integration directories that detail exactly what connects to what, and how. When someone asks an LLM about integration capabilities, it looks for specific, factual answers.
💡 For HubSpot Users
Your knowledge base isn't just a support tool—it's an AEO asset. Every article that clearly answers "Can HubSpot do X?" or "How does HubSpot handle Y?" is a citation opportunity. The same applies to your blog content: specific, question-answering posts outperform broad "ultimate guides" in AI recommendations.
What's Actually Different: Off-Site Strategy
This is where SEO and AEO genuinely diverge, and it's worth understanding precisely.
In traditional SEO, backlinks work like votes. A link from a high-authority site passes value to your site regardless of which specific page links to you. A backlink from the New York Times homepage helps your entire domain.
In AEO, only mentions on the specific URLs that appear in citations matter.
Let's say you want to win the prompt "What's the best HubSpot agency in the UK?" ChatGPT will generate an answer based on the sources it cites. If an article on a marketing blog gets cited for that question and mentions your agency positively, that helps you. If a different article on the same blog (one that doesn't get cited for this prompt) mentions you, it does nothing for this specific question.
This means your off-site strategy must be more targeted:
Transform your target keywords into natural questions that people would ask an AI.
Use AEO tracking tools or manual testing to find what sources appear for those prompts.
Outreach, guest contributions, and expert quotes on the pages that actually get cited.
The LLM just needs to find your brand name in the cited content—links aren't required.
The good news is that many of the tactics overlap with traditional digital PR and link building. The difference is targeting: you're not just chasing domain authority, you're pursuing presence on the specific pages that AI systems reference.
Reddit appears frequently in citations, as does YouTube. Industry blogs, comparison sites, and affiliate content also show up regularly. The specific mix depends on your sector—track what appears for your priority prompts and focus there.
Finding the Questions Your Audience Asks AI
Here's a practical challenge: there's no "Google Keyword Planner" for ChatGPT prompts. You can't pull a report showing prompt volume and competition.
Panel-based data exists (tools that track a sample of LLM usage), but it only shows the head—popular, common queries. The real opportunity lives in the long tail: specific, multi-criteria questions where there might be only one or two good answers. That's where early-stage companies can win despite lacking domain authority.
To find these questions, go where people actually ask them:
The process is straightforward: gather raw questions from these sources, use an LLM to categorise and deduplicate them, map them to buyer journey stages, then create content that directly answers each one. For HubSpot users, this data already lives in your CRM—it's a matter of extraction and strategy, not new data collection.
Why Your Company Stage Changes the Approach
The optimal balance between SEO and AEO investment depends on where your company sits.
Focus on AEO Quick Wins
Traditional SEO is hard without existing domain authority. You're competing against established sites with years of backlinks. AEO offers faster wins through off-site mentions (no authority needed) and answering long-tail questions where you might be the only answer.
Build Both in Parallel
Begin investing more seriously in SEO as your authority builds. Run both strategies in parallel—the content you create serves both channels. This is the stage where an integrated SEO + AEO approach delivers compounding returns.
SEO as Major Channel, AEO Additive
SEO should already be a major channel. You have the authority to compete for valuable keywords. AEO is additive—incremental investment captures a growing channel without cannibalising your search traffic.
For any company using HubSpot, the platform gives you infrastructure for all stages: content management, landing pages, blogs, knowledge base, analytics. The question isn't whether to use these tools—it's how to configure them for maximum visibility across both traditional and AI-driven search.
The Technical Requirements (They're Simpler Than You Think)
After cutting through the noise, here's what actually matters technically for both SEO and AEO:
- ↔️ Internal Linking
- {} Schema Markup
- ⚡ Server Rendering
Internal Linking: Logical connections between related content help both search crawlers and LLMs understand your site's structure and topic relationships. This hasn't changed.
Schema Markup: Structured data helps machines understand what your content represents. For AEO specifically, FAQ schema, HowTo schema, and Article schema with author information are particularly valuable. They provide clean, extractable answers.
Server-Side Rendering: If your content loads via JavaScript after the initial page render, some crawlers won't see it. This applies to both Googlebot and LLM crawlers. Ensure your key content appears in the initial HTML response.
As autonomous AI agents develop (systems that can take actions on your behalf—booking hotels, making purchases), structured markup for forms and interactive elements will matter. This isn't urgent today, but it's worth watching.
That's genuinely it. The elaborate "AEO technical requirements" floating around marketing blogs are either unverified theories or repackaged basic SEO principles with new labels.
The Three-Year Outlook: What to Expect by 2028
Based on current trajectories and the underlying technology, here's a reasonable forecast:
SEO Traffic
Flat to slightly declining, but still substantial. The "10 blue links" aren't disappearing—usage patterns are deeply ingrained, and certain query types are poorly suited to conversational AI.
LLM Traffic
Roughly tripling from current levels, eventually reaching perhaps half the size of traditional search. Still not replacing search, but becoming a major channel in its own right.
Additive and complementary. Different query types suit different interfaces. Someone researching "how do I evaluate CRM options" might use ChatGPT. The same person typing "HubSpot login" will use Google.
Emerging Developments Worth Tracking
Autonomous agents: AI systems that don't just answer questions but take actions. "Plan my trip to Barcelona" results in booked flights and hotels without leaving the chat interface. This changes how businesses need to be represented online.
Hyper-personalisation: LLMs that remember your preferences, context, and history. Recommendations will become increasingly tailored, which means generic content loses to specific, persona-matched content.
Video understanding: Gemini 3 can now watch and interpret video content. The information locked in your webinars, product demos, and YouTube content suddenly becomes extractable.
Unique content as competitive moat: As AI can synthesise existing content instantly, the premium shifts to original research, proprietary data, and genuine expertise that can't be replicated. Generic "ultimate guides" become worthless. Distinctive insights become invaluable.
What This Means for Your 2025 Marketing Strategy
Let's consolidate this into actionable priorities:
Frequently Asked Questions
Is SEO traffic actually declining in 2025?
No. Data across thousands of websites shows SEO traffic is flat, typically varying only 1-3% year-over-year. Companies with access to their own analytics can verify this directly. The "SEO is dead" narrative comes primarily from those without data or those conflating specific site declines with market-wide trends.
How big is LLM search compared to Google?
LLM traffic (ChatGPT, Gemini, Perplexity, Claude combined) is currently about 1/15th the size of Google search. It's growing approximately 100% year-over-year, but from a much smaller base. Both channels warrant investment for most B2B companies.
Do I need separate strategies for SEO and AEO?
No. The strategies overlap substantially—good SEO delivers AEO benefits automatically for most content. The main difference is off-site work: AEO focuses on getting mentioned on cited URLs rather than building backlinks broadly. Create one content strategy with slight tactical adjustments for each channel.
What's the biggest off-site difference between SEO and AEO?
For SEO, any high-authority backlink helps your domain overall. For AEO, only mentions on the specific URLs that appear in citations for your target prompts matter. This requires more targeted outreach—identifying which pages get cited for your priority questions and securing mentions there.
Should early-stage startups invest in SEO?
Not heavily—SEO is difficult without existing domain authority. However, AEO offers faster wins through off-site mentions (no authority needed) and answering long-tail questions where you might be the only relevant answer. Focus there first, then build SEO investment as your authority grows.
Is lms.txt something I need to implement?
No. Despite the concept making theoretical sense, Google's John Mueller has confirmed no one currently uses it. Implementation effort is better spent elsewhere until adoption becomes real.
How do I find what questions people ask AI about my industry?
Mine Reddit threads, sales call transcripts, support tickets, and customer success conversations. These contain real questions in natural language. Run them through an LLM to categorise and identify patterns, then create content that directly answers the most common and valuable questions.
What technical requirements are genuinely different for AEO?
Very few. The fundamentals are identical: strong internal linking, accurate schema markup, and server-side rendered content. LLM-specific technical requirements (like lms.txt or markdown conversion) either aren't adopted or aren't necessary. Focus on solid technical SEO foundations.
Find Out Where You Stand
If you're unsure whether your SEO and AEO foundations are solid, a diagnostic assessment identifies the gaps—and the quick wins.