Definition
Generative engine optimization, or GEO, covers the content, technical and reputation work that affects how AI assistants mention, describe and cite a brand. It includes making pages crawlable by AI crawlers, writing clear and quotable content, keeping facts consistent across the web and earning references from sources that assistants retrieve.
For example, Aarvi Skin notices assistants recommend Dermalume for fragrance-free moisturizer questions. Its GEO work might include a clear ingredient page, updated product details on retailer listings and tracking whether answers change over the following months. None of these steps guarantees a recommendation, so measuring results matters.
Why it matters
Generative answers can shape a buyer's shortlist, and they draw on sources and signals that traditional rank tracking does not show. GEO gives a name to the work of improving that presence. It overlaps heavily with good SEO and content practice, so it rarely needs a separate playbook. What it adds is a focus on measuring AI answers directly and on the sources those answers rely on.
What to do
- Track a fixed set of buyer questions across the AI assistants your customers use.
- Fix crawl access, factual gaps and unclear pages before creating new content.
- Identify third-party sources assistants cite in your category and check how they describe you.
Common questions
Is GEO replacing SEO?
No. GEO builds on SEO rather than replacing it. Many AI assistants retrieve pages from search indexes, so crawlability, indexing and useful content still matter. GEO adds attention to how AI answers describe your brand and which sources they cite, which traditional rank tracking does not measure.
How long does GEO take to show results?
It varies. Changes to live pages can affect answers that use real-time retrieval once those pages are recrawled, while model training data updates less often. Results also differ by assistant. Track the same questions over consistent periods so you can see whether changes coincide with your work.