GEO vs AEO vs SEO: What B2B SaaS Companies Need to Know About AI Search
If you’ve been in B2B marketing for more than a few months, your LinkedIn feed is probably drowning in acronyms. The geo vs aeo debate is everywhere. So is the question of whether traditional SEO is dying, evolving, or just getting a new wardrobe.
Here’s what we actually think, after working with B2B SaaS companies on organic growth across all three disciplines: they’re not competing frameworks. They’re layers of the same system. But the differences between them matter more than most people realize — especially if you’re allocating budget in 2026.
This post breaks down SEO, AEO, and GEO in plain terms, shows where they overlap and diverge, and gives you a practical framework for deciding where to invest. No hype. No fear-mongering about AI replacing organic search. Just what works.
The Alphabet Soup Problem: SEO, AEO, and GEO Defined
Let’s start with clean definitions. Most of the confusion around seo vs geo vs aeo comes from people treating them as interchangeable. They’re not.
SEO: Search Engine Optimization
SEO is the practice of optimizing your website and content to rank higher in traditional search engine results — primarily Google’s organic blue links. It’s been around for over two decades, and the fundamentals (relevant content, technical health, authoritative backlinks) still hold.
When someone Googles “b2b seo agency” and clicks one of the ten organic results on page one, that’s SEO at work.
What it optimizes for: Rankings in organic search results (SERPs).
AEO: Answer Engine Optimization
AEO is the practice of optimizing content to appear in direct-answer formats: featured snippets, People Also Ask boxes, knowledge panels, and voice search results. AEO has been a discipline since roughly 2015, when Google started pulling answers directly into the SERP instead of requiring a click.
When someone asks Alexa “what is programmatic SEO” and gets a spoken answer pulled from a web page, that’s AEO.
What it optimizes for: Featured snippets, voice search, zero-click answers in traditional search.
GEO: Generative Engine Optimization
GEO — or generative engine optimization — is the newest layer. It’s the practice of optimizing your content to be cited, referenced, or synthesized by AI-powered search tools: ChatGPT, Perplexity, Google AI Overviews, Claude, and Gemini. Unlike AEO, which targets structured answer boxes within a traditional SERP, GEO targets entirely new interfaces where an AI model generates a multi-source response.
When someone asks Perplexity “what are the best approaches to B2B SaaS content strategy” and your content is cited in the generated response, that’s GEO.
What it optimizes for: AI-generated responses and citations across ChatGPT, Perplexity, Google AI Overviews, and other generative search tools.
How AI Search Actually Works
To understand why GEO requires a different approach, you need to understand what happens behind the scenes when someone asks an AI search engine a question. The process has three distinct stages:
1. Retrieval. The system searches the web (or its index) for relevant source documents. This step still relies heavily on traditional signals — domain authority, content relevance, recency, topical depth. If your content doesn’t get retrieved, it can’t get cited. This is why SEO fundamentals still matter for GEO.
2. Generation. The AI model reads the retrieved sources and synthesizes a response. It’s not copying and pasting. It’s interpreting, summarizing, and combining information across multiple sources. Content that is clearly structured, factually dense, and easy to extract key claims from has a significant advantage here.
3. Citation. The model attributes specific claims to specific sources. Not every retrieved document earns a citation. The ones that do tend to share common traits: original data, clear definitions, authoritative positioning, and structured formatting that makes it easy for the model to point back to a specific passage.
This three-stage process explains why GEO overlaps with SEO (you need to be retrievable) but adds a distinct optimization layer (you need to be extractable and citable).
What’s Actually Different About GEO vs Traditional SEO
The geo vs aeo distinction matters, but the more consequential comparison for most B2B SaaS companies is GEO vs traditional SEO. Here’s where the approaches diverge:
No ranking positions. In traditional SEO, you aim for position 1-3 for a target keyword. In GEO, there are no ranked positions — either your content is cited in the AI response or it isn’t. This fundamentally changes how you measure success.
Multi-source synthesis. Traditional search sends users to one page. AI search synthesizes information from many sources into a single answer. Your content doesn’t need to be the single best result — it needs to contribute a unique, citable data point or perspective.
Structure over keyword density. Traditional SEO still rewards keyword relevance (in headers, body text, meta tags). GEO rewards structural clarity — definitions, comparisons, statistics, and claims that an AI model can confidently attribute. Keyword stuffing isn’t just unhelpful for GEO; content that reads like it was written for a search crawler is harder for AI models to extract cleanly.
Authority signals shift. In SEO, backlinks are the primary authority signal. In GEO, authority comes from being a recognized entity with consistent information across the web, original research that other sources reference, and domain expertise that the model has learned to associate with a topic.
Comparison Table: SEO vs AEO vs GEO
Here’s the full seo geo aeo comparison across the dimensions that matter for strategic planning:
| Dimension | SEO | AEO | GEO |
|---|---|---|---|
| Target channel | Google organic results (blue links) | Featured snippets, voice search, PAA boxes | ChatGPT, Perplexity, Google AI Overviews, Claude, Gemini |
| Optimization focus | Rankings, click-through rate | Direct answers, structured Q&A | AI citations, source synthesis |
| Content format | Long-form, keyword-targeted pages | Concise Q&A, list-style, definition blocks | Entity-rich, stat-heavy, clearly attributed claims |
| Measurement | Rankings, organic traffic, CTR | Featured snippet ownership, voice search share | Brand mentions in AI tools, citation frequency, referral traffic from AI |
| Primary signals | Backlinks, content relevance, technical health | Schema markup, direct answer formatting, content structure | Entity authority, content extractability, topical depth, original data |
| Timeline to results | 3-6 months (typical) | 1-3 months (for snippet capture) | Emerging — no established benchmarks yet |
| Maturity | 25+ years, highly established | 10+ years, well-understood | 2-3 years, rapidly evolving |
| B2B SaaS relevance | High — still drives majority of organic pipeline | Medium — useful for top-funnel visibility | High and growing — decision-makers increasingly use AI search |
Why B2B SaaS Companies Should Care Now
If you’re a VP of Marketing or Head of Growth at a Series A-D SaaS company, here’s why the geo vs aeo conversation isn’t just academic:
Your buyers are already using AI search. A 2025 Gartner survey found that over 70% of B2B buyers use AI tools as part of their research process. When a CTO asks ChatGPT “what are the best infrastructure monitoring tools for scaling startups,” that’s a pipeline-stage query. If your competitor shows up and you don’t, you’ve lost influence before the buyer even hits Google.
AI Overviews are expanding. Google’s AI Overviews now appear for roughly 30% of informational queries. For B2B SaaS categories, the coverage is even higher — product comparisons, “how to” queries, and “best tools for X” are prime AI Overview territory. Your existing SEO traffic is being siphoned by answers that appear above the fold.
Early movers have a compounding advantage. GEO is where SEO was in 2005. The companies that build topical authority and entity recognition now will be the ones AI models cite by default as the training data compounds. Waiting means catching up.
The cost of inaction is invisible. Unlike a traffic drop (which GA4 catches), losing AI search visibility doesn’t trigger any alert. There’s no “AI search impressions” metric in your current dashboard. The pipeline you’re losing to AI citations is silent — which makes it more dangerous, not less.
The Overlap: What SEO Work Also Helps GEO
This is the good news, and it’s substantial. A large portion of what makes content perform in traditional SEO also makes it performant for GEO. If you’re already doing good SEO, you’re not starting from zero.
Technical SEO foundations. Fast load times, clean crawlability, proper indexation, and structured site architecture all help AI search systems retrieve your content. SearchLever’s technical SEO practice is built on these engineering fundamentals — and they’re as critical for GEO retrieval as they are for Google rankings.
Quality content. Thorough, well-researched, accurate content gets cited by AI models and ranked by Google. Thin pages that exist purely for keyword targeting perform poorly in both systems.
Topical authority. Publishing depth on a topic (multiple related pages, interconnected content clusters) signals expertise to both Google’s algorithms and AI models. This is why content operations infrastructure matters for GEO — a single blog post won’t build the kind of topical depth that earns consistent AI citations.
Schema markup and structured data. JSON-LD markup (Organization, FAQ, HowTo, Product) helps Google understand your content and helps AI models parse your entities. This is table-stakes for both SEO and GEO.
E-E-A-T signals. Author credentials, source citations, original data, and brand reputation all factor into both Google’s ranking algorithms and AI models’ citation decisions.
GEO-Specific Tactics That Go Beyond SEO
Here’s where generative engine optimization requires work that traditional SEO doesn’t cover:
Entity-Rich Content
AI models understand the world through entities — people, companies, concepts, products. Content that clearly defines and connects entities is more extractable than content that relies on contextual inference.
What this means in practice:
– Use structured data (schema.org) to define your company, products, and key people
– Reference other known entities (tools, frameworks, standards) by their canonical names
– Build a consistent entity footprint across your website, social profiles, and third-party mentions
Citation-Worthy Writing
AI models cite sources that make specific, verifiable claims. Vague thought leadership (“content is king”) rarely earns citations. Specific, data-backed statements (“B2B SaaS companies that publish 4+ blog posts per month see 3.5x more organic traffic growth than those publishing monthly”) do.
Tactics:
– Include original data, survey results, and benchmarks wherever possible
– Write clear definitions that a model can extract as a standalone answer
– Use specific numbers and percentages, not generalities
– Attribute claims to named sources (your own research, industry reports, named experts)
Topical Authority Building
AI models develop “memory” around which sources are authoritative on which topics. This happens through training data exposure. A single great article won’t establish you. Sustained publishing depth on a connected set of topics will.
For B2B SaaS companies, this means:
– Building content clusters around your core service categories
– Covering the same topics from multiple angles (definitions, comparisons, how-tos, case studies)
– Earning mentions and citations from other authoritative sources in your space
For companies in the AI/ML space, this is particularly urgent — the competition for topical authority in AI-adjacent categories is accelerating fast.
Direct Answer Formatting
Structure content so AI models can extract clean answers without heavy interpretation:
- Lead sections with a direct, definitional answer before expanding
- Use headers that match the questions people actually ask
- Place key statistics and claims in standalone sentences, not buried in long paragraphs
- Use comparison tables for “vs” queries (like the one in this post)
How to Measure GEO Performance
This is the hardest part of the seo vs geo vs aeo conversation. SEO measurement is mature — you’ve got GSC, GA4, rank trackers, and pipeline attribution. GEO measurement is still developing.
Here’s what you can do today:
Manual brand monitoring. Regularly query the major AI tools (ChatGPT, Perplexity, Google AI Overviews, Claude) with your target keywords and category queries. Document where your brand appears and where competitors appear. This is manual, but it’s the most reliable signal.
Referral traffic tracking. Track referral traffic from AI search tools in GA4. Perplexity, in particular, sends identifiable referral traffic. ChatGPT browse-mode and Google AI Overviews also generate some trackable clicks.
Citation tracking tools. Emerging tools like Otterly.ai, Peec AI, and other GEO-specific monitoring platforms are starting to automate what we currently do manually. The space is evolving fast.
Branded search volume. If your GEO strategy is working, you’ll see an increase in branded search queries — people learning about you through AI responses and then Googling your company name. Monitor branded search volume in GSC as a leading indicator.
Share of voice in AI. For competitive categories, track how often your brand is cited vs. competitors for the same queries. This is the GEO equivalent of share of voice in traditional SEO.
The measurement story will improve. But waiting for perfect measurement before investing in GEO is like waiting for GA4 to exist before building a website in 2005.
The Integrated Approach: Why You Need All Three
The most important takeaway from the geo vs aeo debate: these are not mutually exclusive strategies. They’re concentric layers of the same organic growth system.
SEO is the foundation. Without technical health, quality content, and domain authority, your content won’t get retrieved by AI models or ranked by Google. SEO is not dying — it’s the infrastructure layer that everything else depends on.
AEO is the precision layer. Optimizing for featured snippets and direct answers captures zero-click traffic and builds the structured-answer formatting habits that also benefit GEO.
GEO is the emerging frontier. As AI search grows (and it will), the companies that invested in entity authority, citation-worthy content, and AI extractability will compound their advantage.
The right approach is integrated. Start with SEO fundamentals. Layer in AEO-style structured content. Then add GEO-specific tactics: entity optimization, citation-worthiness, and AI visibility monitoring.
At SearchLever, this is exactly how we approach generative engine optimization — not as a replacement for SEO, but as the next layer on top of it. Our clients don’t choose between SEO and GEO. They build organic systems that perform across the entire search ecosystem.
What This Means for Your 2026 Organic Strategy
If you’re planning organic growth for the rest of 2026, here’s the practical framework:
Don’t panic about traditional SEO. Google still drives the majority of B2B organic traffic. Your SEO investment isn’t wasted — it’s foundational. Keep doing it.
Start GEO optimization now, even if it’s lightweight. Audit your content for extractability. Add structured data. Write clearer definitions and include more original data in your content. These changes help SEO and GEO simultaneously.
Build measurement infrastructure. Set up manual AI brand monitoring. Track AI referral traffic in GA4. Establish baseline share of voice in AI tools so you can measure progress.
Invest in topical authority, not just individual pages. The companies that will win in both SEO and GEO are the ones with deep, interconnected content on their core topics. Single keyword-targeted pages won’t cut it.
Think in terms of pipeline, not traffic. Whether a prospect finds you through Google, ChatGPT, or Perplexity, what matters is whether they enter your pipeline. Measure organic growth by demos booked and pipeline created — not just impressions and clicks.
The seo geo aeo landscape will continue to evolve. AI search will claim a larger share of discovery. But the companies that build strong foundations now — technically sound, content-rich, entity-authoritative — will perform regardless of which interface serves the results.
Ready to build an organic strategy that works across SEO, AEO, and GEO? SearchLever helps B2B SaaS companies build integrated organic growth systems that drive pipeline — not just traffic. We’ll audit your current AI search visibility, identify the gaps, and build the infrastructure to close them.
Book a Strategy Call or explore our pricing to get started.