GEO vs SEO: do you need both?

Why people ask the question

Marketing leaders ask "GEO vs SEO?" because they're trying to make a budget decision. Either:

• They have an SEO budget and an agency relationship, and they're being told they also need to invest in GEO. Is that a separate line item? Or is it just "what good SEO looks like in 2026"?
• They're starting from zero (a new product, a new market) and trying to figure out where to spend first.
• They have a GEO-curious CEO and a sceptical SEO team, and they're trying to figure out who's right.

Honest answer: it depends on your buyers. The cleanest way to make the call is to actually look at how your buyers are researching purchases — not how you imagine they're researching, but how they actually do it. The mix of "Googling" vs "asking ChatGPT" varies enormously by category. Enterprise software buyers are AI-search-native; local services buyers still mostly Google. Get this empirical, not theoretical.

The disciplines, side by side

Below is the working comparison we use with clients deciding budget allocation. It's not exhaustive — both disciplines have details that don't fit on a one-page summary — but it's the version that keeps showing up as useful in CMO conversations.

The 60% that overlaps

If you're already doing SEO well, you've already done most of the foundational work for GEO. The shared substrate:

Technical accessibility

AI engines crawl the same way Google does — they need fast pages, clean HTML, working server-side rendering, and crawler access. A site that's good for Googlebot is also good for GPTBot, ClaudeBot, and PerplexityBot. The only AI-specific addition is making sure you haven't blocked the AI bots specifically (it's depressingly common; check your robots.txt).

Content quality

Both disciplines reward content that demonstrates expertise, cites sources, makes specific claims, and avoids fluff. Both punish thin content, keyword stuffing, and AI-generated drivel. If your content is genuinely useful and well-structured for SEO, it's already 80% of the way to being useful for GEO retrieval.

Site authority and trust

Backlinks from authoritative domains. Brand mentions in editorial. Wikipedia presence. These are SEO ranking factors and AI training signals simultaneously. The compounding asset that helps you rank on Google #1 is the same asset that gets you cited by ChatGPT.

Schema markup

Structured data tells search engines and AI engines exactly what your pages are about. Organisation schema, Product schema, FAQ schema, HowTo schema — all useful for both. The marginal cost is near-zero once you've done it once.

The 40% that's different

This is where the distinct disciplines emerge. The work that's specifically GEO and not SEO:

Editorial presence at scale

SEO rewards editorial mentions because they create backlinks. GEO rewards them because they create training-data presence. The volume threshold is different. For SEO, getting 10 quality editorial mentions a year materially improves your link profile. For GEO, you need closer to 30–60 high-authority mentions a year to meaningfully shift the AI's representation of your brand. The Digital PR investment for GEO is roughly 3–6× what most brands currently spend.

Entity and knowledge graph work

Wikipedia, Wikidata, Crunchbase, Google Knowledge Panel. These rarely show up in SEO checklists because they don't directly drive organic traffic. They show up in every GEO checklist because they're the structured data sources LLMs treat as authoritative ground truth. Wikipedia presence in particular is the single highest-leverage GEO move; it's barely an SEO move at all.

Comparison and alternative content

Pages explicitly structured around "X vs Y" or "alternatives to Z." For SEO, these can rank well if you're targeting specific comparison queries. For GEO, they're disproportionately valuable — AI engines synthesise comparison answers from comparison content. If you don't have comparison content about your category, the AI uses your competitors' comparison content as the source. The result is the AI describing you in your competitor's framing.

Reddit and community presence

SEO mostly ignores Reddit (low-authority links, hard to control). GEO can't ignore Reddit (LLMs train heavily on it). The behaviour required is also different: SEOs are used to creating content; getting genuine Reddit recommendations requires having a product worth recommending and a team genuinely active in communities. It's less marketing, more product/customer success.

Sentiment and frame management

SEO doesn't have a sentiment dimension — your URL either ranks or it doesn't. GEO does. Your brand can be mentioned negatively or framed unfavourably, and that's worse than not being mentioned at all. The discipline of monitoring how AI engines describe your brand qualitatively, and intervening when the framing slips, is genuinely new.

Where the disciplines actively conflict

The 40% non-overlap isn't always neutral — sometimes the best move for one is the wrong move for the other.

Click-optimised content vs. answer-complete content

Classic SEO content is structured to make users click and read further (cliffhanger intros, "read on to learn..."). Classic GEO content is structured to be summarised without a click (one clear claim per paragraph, factual density up front). The same page can't optimise for both perfectly. Most brands choose: foundational educational content goes GEO-style; conversion-driving lower-funnel content stays SEO-style.

Long content vs. extractable content

Google rewards comprehensive content. AI engines reward extractable content. A 5,000-word ultimate guide ranks well but gets summarised down to two sentences when an AI cites it. A 1,500-word piece with sharp, quotable claims gets the AI mention and ranks well enough. The new cost-effective unit of content is shorter and denser, not longer.

Keyword targeting vs. entity association

SEO's core method is targeting keyword phrases. GEO doesn't really have keywords — it has entities and topical clusters. Aggressive keyword optimisation can actively hurt GEO by making your content read as engineered rather than authoritative. The "write for humans, optimise for engines" maxim is more important for GEO than it ever was for SEO.

Budget allocation: the practical answer

How to actually split your budget depends on three variables:

1. Where your buyers research today — measure it, don't guess
2. Where your competitors are investing — being out-spent in a discipline you're already weak in is fatal
3. Your time horizon — GEO investments compound over 6–18 months; if you need pipeline this quarter, weight SEO heavier

If you're starting from zero

Spend 70/30 SEO/GEO for the first 6 months. The SEO foundation is non-negotiable — fast site, schema markup, comparison pages, Digital PR baseline. The GEO 30% goes into Wikipedia work (or earning the right to one), Reddit/community presence, and AI-specific schema additions.

Once that foundation exists, shift to 60/40 for the next 12 months. The marginal SEO investment after a baseline is hit has diminishing returns; the marginal GEO investment compounds.

If you have a mature SEO programme

You're probably under-investing in GEO by a factor of 3–10×. The fix isn't reallocating from SEO — it's adding a separate line item, ideally led by someone with PR/editorial chops, not someone retrained from a keyword-and-rank background.

The ratio that works for most mature B2B SaaS is 50/50 SEO/GEO going into 2027, with the GEO budget heavily weighted toward earned-media and entity-graph work.

If you're a B2C e-commerce brand

You're a special case. Google AI Overviews will eat a large fraction of your transactional traffic over the next 18 months. The defensive move is product-page schema + comparison content + reviews aggregation. The offensive move is being the brand AI Overviews recommends. Budget weighting probably stays 70/30 SEO/GEO because the SEO loss is the immediate revenue threat, but reallocate from "blog content" toward "AI-citable product information."

Who does GEO work?

This is where most agencies and in-house teams get tangled up. The honest taxonomy:

What good GEO talent actually looks like

• Comfortable with both technical SEO concepts (crawlability, schema, IndexNow) and PR-style outreach (pitching journalists, securing editorial coverage)
• Has measured Share of AI Voice for at least one real brand, not just talked about it theoretically
• Can read an audit and tell you which of the four GEO disciplines is weakest, not just generic recommendations
• Has a point of view on which AI engines matter most for which buyer types
• Doesn't promise specific rankings or specific share-of-voice numbers (anyone who does is selling, not consulting)

The most common failure mode: an SEO agency adds GEO services, hires a junior to write "AI-optimised" content, and bills it as if it's the same discipline. It isn't. The output looks like SEO content with the word "AI" added. The results match.

The "we'll just do it ourselves" question

Can a marketing team learn GEO in-house? Yes — but it's harder than learning SEO was, for two reasons.

First, the field changes faster than learning resources can keep up. By the time a comprehensive GEO course exists, three of its assumptions are wrong because OpenAI shipped a model update.

Second, the work is inherently multi-disciplinary. SEO can be done well by a single skilled practitioner. GEO needs people who do technical SEO, people who do Digital PR, people who manage editorial content, and someone who can connect them. A single hire usually can't cover all four. A team can — but most marketing teams aren't structured for it.

The pragmatic split: do the technical and on-page work in-house (your team can learn it). Outsource the Digital PR work to specialists (it's a different muscle). Get external benchmarking quarterly so you know whether what you're doing is moving the right numbers.

The 18-month forecast

Three predictions about how this plays out:

1. The line between SEO and GEO will blur for technical work. Schema, site speed, crawlability — these will become "search optimisation" without the qualifier. Both Google and AI engines will keep converging on similar technical signals.

2. The line will sharpen for editorial work. Digital PR, Wikipedia management, Reddit presence — these are where GEO becomes recognisably different from SEO, and the gap will widen, not close.

3. Measurement will consolidate. Today, Share of AI Voice is measured by a handful of specialist tools. By late 2026, expect the major SEO platforms (Ahrefs, Semrush, Moz) to roll AI visibility into their core product. The technical category will stop being separate; the strategic discipline of "what to do about your AI visibility" will remain distinct.

The brands setting their 2026 budgets correctly will be the ones who plan for that consolidation while still investing in the specialised work that's distinct now.