GEO Agency

A GEO agency is a team that takes on brand visibility in AI answers as a service. GEO stands for Generative Engine Optimization, and the industry also calls it AI SEO.

What sets such an agency apart from a classic SEO team is not the foundation but the success metric. Alongside rankings and clicks, it tracks brand mentions, citations and the accuracy of information in answers. Google does not require anything separate for these surfaces, so the work is built on a solid search foundation.

The real contribution is setting up consistent measurement across platforms and tracing misreported brand information back to its source. Asking an agency how it repeats this measurement is the fastest way to evaluate its promise.

AEO stands for Answer Engine Optimization. Its goal is to become the source on surfaces that give a single, direct answer to a question. Google's featured snippets and voice assistants that read the answer aloud fall into this group.

In GEO, the answer is compiled from multiple sources, so the goal is to be mentioned within that compilation. In practice, AEO means a page structure that puts the question in the heading and gives the answer in the first sentence.

You cannot mark a page as a featured snippet. According to Google's featured snippets documentation, Google's systems make that choice. So AEO is not a guaranteed placement but work that makes the right answer easy to find. Digitruva runs AEO inside the GEO plan, using the same question set, rather than as a separate project.

GEO optimization covers four areas of work: access, content, entity and measurement. For access, it confirms that pages are crawlable, indexed and eligible to be shown with a snippet, because that is what Google looks for in a supporting link within its AI features in Search.

Meeting that requirement still does not guarantee being shown. For content, priority pages are broken into passages that make sense when read on their own, and details such as definitions, scope and dates are stated clearly.

For entity work, the external profiles that carry brand information are listed and anything that contradicts the site is corrected. For measurement, the same question set is rerun periodically. Topic gaps that the measurement reveals are closed by producing quotable content, and the effect is then read in the same set.

Not for visibility on Google. In its AI features documentation, Google states clearly that no new machine-readable files, AI text files or special schema.org markup are needed to appear in AI Overviews and AI Mode.

Structured data has a different job. Organization markup helps search engines understand details about an organization, and the sameAs property links official profiles. What really needs checking is access. robots.txt controls crawling, nosnippet and max-snippet limit the text that can be shown, and Google-Extended does not affect inclusion in Google Search.

Digitruva reads each of these settings during the audit, because one wrong block can undermine all the content work. These checks are also part of the technical SEO foundation and serve both efforts.

Voice search optimization assumes the answer will be heard rather than scanned on a screen. That is why passages that answer the question in a short sentence, one that is still clear when read aloud, stand out. In multimodal search, users can send an image along with text.

Taking a photo and asking about a product is a familiar example. Here, image descriptions, product information and page copy need to be consistent. If the model shown in the image differs from the model in the text, matching the answer correctly gets harder.

Search Console's generative AI report can filter text-based and multimodal searches separately, so the difference can be tracked. These surfaces are not separate jobs but outcomes of the same content structure.

Be cautious of proposals that guarantee citations or promise a definite spot on a particular platform. AI answers can vary by person and time even for the same question, and a single screenshot is not proof.

A promise of secret Google-specific markup also contradicts official documentation. The proposal should state which question set will be measured, on which platforms and with how many repetitions. Work done without recording a baseline cannot be evaluated later.

It should also be clear who keeps which work and who owns the access. That is why Digitruva starts with an analysis that measures your visibility, which records the question set, and states the limits of the measurement in the report.