GEO: the right answer to the wrong question?

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By Coralie Dussart, CEO and founder of Spaag

In recent months, the same reflex has taken hold in executive committees. Companies search for themselves on ChatGPT, worry when they don’t see their name appear, and the verdict quickly follows: “we need to do GEO.” A hasty conclusion, reinforced by a tendency to attribute any drop in SEO traffic to LLMs.

While the reaction is understandable, it is not entirely rational. First, attributing every variation in traffic to generative engines is an oversimplification. Changes in tracking, cookie consent constraints, and algorithm updates also significantly impact performance. GEO is part of the phenomenon, not its sole explanation.

That being said, the core issue runs deeper: what is being treated as a visibility optimization problem is, in reality, a strategic one.

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GEO is not SEO 2.0

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With GEO (Generative Engine Optimization), the objective is no longer just to rank well in a list of links, but to influence how a model reformulates and synthesizes information. At the same time, AEO (Answer Engine Optimization) pushes this logic further by structuring content so it can be directly used by engines that deliver a final, clear, and ready-to-use answer.

Presented this way, GEO might seem like the natural next phase after SEO. But this shortcut is precisely the problem. GEO is not a standalone lever that replaces everything else. It would also be incorrect to oppose GEO and SEO. Generative models still rely on signals from the traditional web: semantic consistency, perceived authority, and structured content.

GEO does not replace SEO, it exposes it. AEO, for its part, simply requires greater clarity in how real user questions are answered. Adding FAQs or comparison tables cannot compensate for weak positioning.

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Good GEO is built on strong marketing strategy

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When discussing GEO, the first misunderstanding often concerns the target audience. Not all audiences have integrated LLMs into their information habits. Depending on sectors and generations, conversational search remains partial and represents only a fraction of traffic.

Many companies react as if the shift were immediate and total. In reality, the strategic question is not whether you should “do GEO,” but whether your audience is already expressing its needs in these environments—and whether this aligns with its decision-making journey. Reallocating budgets without validating this alignment is closer to anxiety than analysis.

Generative engines perform particularly well when it comes to comparing and clarifying complex decisions. Choosing an insurance plan, evaluating SaaS solutions, or identifying the right agency for a specific need are all cases where conversational interfaces provide real value through synthesis.

Conversely, for highly visual or emotional products, usage patterns remain different. Buying a handbag, sneakers, or a bottle of wine still largely starts on platforms like Google Shopping or visual discovery environments. LLMs tend to intervene later, to refine or compare options.

The relevance of GEO therefore depends on the type of decision being supported, not on hype.

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The real challenge: clarity, not visibility

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The real objective is not to appear at all costs in a generated answer. It is to ensure that your positioning is correctly understood by a system that interprets rather than simply lists.

In a world where engines synthesize and rephrase, raw visibility is no longer enough. What becomes strategic is semantic consistency, clarity of offer, and long-term brand credibility.

Last year, the same pattern emerged under a different label: companies felt they had to “do AI,” regardless of purpose. GEO risks following the same path if treated as a standalone imperative rather than as an evolution to be integrated intelligently.
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GEO and AEO do not replace marketing strategy—they reveal how strong it actually is.

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