Why GEO visibility is not a rank or citation, but a multistage, stochastic, and partially observable system.
Why GEO needs a unified theory
The word “visibility” is often used for several different outcomes. A page can enter a retrieval set, a source can receive a citation, a brand can be mentioned, facts can shape several paragraphs, or a visit can become a sale. These outcomes are related, but they are not interchangeable.
Martinez argues that GEO should move beyond one ranking task and be modeled as a stochastic, partially observable pipeline. The implication is methodological: each stage needs its own dependent variable and often its own intervention.
Visibility unfolds through connected stages
A practical end-to-end sequence is discoverability → retrieval → context exposure → citation → absorption → prominence → fidelity → brand visibility → user action → conversion.
A source can succeed at one stage and disappear at the next.
An optimization can improve citation after retrieval while leaving discovery unchanged—or even harming an upstream outcome.
Visibility is a distribution, not a point
The same prompt can produce different sources, context order, wording, citations, and recommendations across repeated runs. Engine, date, location, query formulation, search activation, and generation variability all affect the outcome.
If a brand appears in six of ten comparable runs, the useful observation is a 60% mention rate under those conditions—not a claim that the brand holds one stable rank. Repetition turns an anecdote into a distribution.
The system is only partly observable
Practitioners can usually observe citations, mentions, response wording, visible position, referrals, and downstream behavior. They cannot normally inspect the complete retrieval pool, proprietary reranking scores, full context allocation, or internal model states.
Responsible GEO separates what was directly observed, what was inferred through a proxy, and what remains unknown.
Questions about this topic
Why is GEO not one ranking problem?+
Because discovery, retrieval, citation, answer influence, brand representation, action, and conversion are distinct mechanisms with different outcomes.
What does stochastic visibility mean?+
It means comparable runs can produce different results, so visibility should be described as a distribution across specified conditions rather than one fixed observation.
What is partially observable about GEO?+
Visible outputs can be measured, but commercial engines generally hide their complete candidate pools, reranking logic, context allocation, and internal generation states.
References
Sources are listed in APA 7 style. Preprints are identified as such and should not be treated as peer-reviewed findings unless separately published.
- Martinez, O. (2026). Optimizing visibility in generative engines: A critical survey of generative engine optimization (2023–2026) [Preprint]. arXiv. https://doi.org/10.48550/arXiv.2607.14035
- Aggarwal, P., Murahari, V., Rajpurohit, T., Kalyan, A., & Narasimhan, K. (2024). GEO: Generative engine optimization. In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 5–16). Association for Computing Machinery. https://doi.org/10.1145/3637528.3671900
- Zhang, K., He, X., & Yao, J. (2026). From citation selection to citation absorption: A measurement framework for generative engine optimization across AI search platforms [Preprint]. arXiv. https://doi.org/10.48550/arXiv.2604.25707