SEO Evolution Analyzer

More and more buying decisions start with a prompt, not a search box. When a prospect asks an AI engine "which tool should we use?" and your brand is not in the answer, you are invisible to an entire generation of demand. Generative engine optimization (GEO) is how you fix that.

Why are some brands cited while others are ignored?

AI engines decide what to cite from a mix of training data, indexed web content, and trusted sources. A brand wins a citation when its site is crawlable, its claims are quantified, and its name appears in contexts the engine already trusts. Brands that block AI crawlers or publish thin pages are structurally invisible to these engines.

The gap shows up clearly in citation testing. When the same buyer-intent prompt is run against n=4 to 6 variants across engines, established brands are cited dozens of times while newer sites score 0%. That gap is not a ranking problem in the traditional sense — it is a presence problem.

What is generative engine optimization (GEO)?

GEO is the practice of improving how often a generative AI engine mentions your brand as a source in its answers. It is the successor concept to SEO for an interface where the "results page" is a single synthesized paragraph rather than ten blue links.

The readiness score used throughout this site is a 25% weighted blend of AEO, AIO, GEO, and crawlability. In practice, GEO is the layer that determines whether you are named, AEO determines whether your answer is quoted, and AIO determines whether Google surfaces you in its AI Overviews.

Which AI engines matter most?

Coverage across engines matters more than dominating any single one, because different buyers use different assistants. The table below shows where each engine sits in most B2B research journeys. For current feature detail, see the official Perplexity product page.

What signals actually increase citation rates?

Citation rate rises when an engine can both find you and confidently quote you. The highest-leverage signals are: allowing critical AI crawlers in robots.txt, shipping llms.txt, adding quantified statistics and named frameworks, structuring question-and-answer content, building an entity with consistent naming, and earning third-party mentions from sources the engine trusts.

Statistical density is disproportionately powerful. Engines prefer to quote claims that carry numbers, so pages that cite percentages, study findings, and sample sizes are cited more often than equivalent pages that do not. A brand mention that also carries a number is more quotable than a bare mention.

Engines do not cite pages, they cite entities they trust. Your job is to make the page quotable and the entity findable.

How is GEO different from SEO and AEO?

SEO wins the click, AEO wins the quote, and GEO wins the mention. SEO optimizes rankings in a results page, AEO optimizes being extracted as the direct answer, and GEO optimizes being named as a source inside an AI-generated answer. They reinforce each other but measure different outcomes.

A practical consequence: a page can hold the #1 SEO result and still fail GEO if the engine does not name the brand, while a page with modest SEO rankings can win GEO citations if its entity is well represented across the web. Measure all three separately.

How do you measure citation rate?

Citation rate is measured with prompt tests: you ask an engine a set of realistic buyer-intent questions and count how often your brand appears in the answers. The seo-ea.com analyzer automates this with n=4 to 6 prompts per engine and reports a share-of-voice matrix across engines.

Because LLM answers are stochastic, a single test run is noisy. Run the same prompt set multiple times and average the result, and always compare against competitors in the same run so the denominator is constant.

How do you run a citation test?

Write prompts the way a real buyer would, not as keywords. "What is the best tool for X?" and "Recommend a product that solves Y" are closer to real demand than "best X tools 2026". Then run the same set against each engine, record mentions per brand, and compute the citation rate and share of voice per prompt.

The point is not a single score. The point is a repeatable baseline you can re-run after each content change to see whether the number moves. Baseline, change, re-measure is the whole discipline.

How long does GEO take to show results?

On-page readiness can improve within weeks because crawlers see the changes almost immediately. Citation rates, however, depend on indexation and training-data cycles: expect 4 to 8 weeks for new content to influence answers, and longer for category-level prompts that depend on accumulated third-party mentions.

The fastest wins are almost always structural: unblocking AI crawlers, adding llms.txt, and making your highest-value pages quotable. The slowest wins are authority wins, which require third-party mentions to compound over quarters.

What does a GEO project actually cost?

The cost of a GEO project is mostly engineering and content time, not tools. The free tier of the analyzer at seo-ea.com runs unlimited rule-based readiness scans, so the checklist phase costs nothing beyond your own hours. The paid tiers add live citation tests and quota, which is the measurement cost rather than the fix cost.

A realistic starting budget is one to two days of engineering to unblock crawlers, ship llms.txt, and wire schema, plus one focused content pass per key page to add question headings and atomic answers. Third-party mentions in Phase 2 add the time cost of outreach, which compounds but does not require a tool spend.

How do you choose which pages to optimize first?

Optimize the pages that answer your highest-value buyer questions first, not the pages with the most traffic. A page that answers "which product should I pick?" is worth more to citation rate than a high-traffic page that answers a question nobody asks an assistant.

A useful ranking method is to score each candidate page on three criteria: whether it answers a question buyers actually prompt, whether the brand name appears in a quotable position, and whether the page already carries some authority signals. Pages that score high on the first and second criteria are where atomic answers and schema will move the citation needle fastest.

A step-by-step GEO process

1. Run a readiness scan on your key pages and fix crawlability first — blocked bots cap the score.
2. Ship llms.txt and confirm it returns HTTP 200 at the domain root.
3. Add question headings with atomic 30-50 word answers to your most important pages.
4. Quantify your claims: add statistics, percentages, and sample sizes where they are true.
5. Run a baseline citation test and record your citation rate and share of voice.
6. Repeat the test monthly after each content change, comparing the same prompt set.

What does a good GEO setup look like?

A mature setup pairs a crawlable, quotable site with consistent entity representation: the brand name appears consistently in headings and schema, sameAs profiles link to the same entity across platforms, and third-party pages mention the brand with context. At that point citation tests trend upward rather than bouncing at zero.