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Elevam

GEO

GEO Research (Generative Engine Optimization)

GEO Research (Generative Engine Optimization) is the Elevam Labs line dedicated to measuring how brands appear in generative engines.

We analyze presence, mention, source citation and attributed links in AI-generated responses.

This page works as an index of the line and gathers published baselines, studies and benchmarks.

What we publish in this line

We publish only studies with explicit methodology and reproducible criteria. We don't publish opinion or editorial content.

  • Baselines (periodic series): Recurring measurements with the same protocol and a stable dataset to compare evolution over time.
  • Cases and experiments (one-off tests): Mini-studies with a specific hypothesis and bounded results, designed to validate changes or specific behaviors.
  • Benchmarks (comparisons): Comparisons between brands, categories or approaches under a common criterion, when it adds context and is methodologically defensible.

In each study we detail the methodology and, when appropriate, we provide data or materials for replication and comparison.

Series and studies available

Cases and experiments

In preparation. Here we will publish one-off tests to answer specific questions (for example, changes in citation or links).

Benchmarks

In preparation. Here we will publish comparisons between brands or categories following the same rules.

Relation with methodology

  • The GEO line measures and documents results (evidence).
  • Cuando queremos probar mejoras o cambios, seguimos un protocolo común para hacerlo de forma controlada y comparable: HSA (Human · Search · AI).

Methodological framework and resources

Authorship and contact

Elevam Labs: Applied research in organic visibility and generative engines.

Contact: For citation, methodological context or access to data, write to: Asier López Ruíz