Practical Generative Engine Optimization (GEO) training to learn how to audit, measure, and execute strategies that help your brand be understood, mentioned, cited, and recommended in generative engines.Designed for SEO, marketing, content, acquisition, and agency professionals who need to adapt their work to generative environments with methodology, measurement, and real application.You will learn what a serious GEO strategy must include: audit, visibility measurement in LLMs, RAG-friendly content optimization, entity work, citation, reputation, and implementation roadmap.
A program designed so you don't stay in theory. The course combines fundamentals, methodology, audit, structure, measurement, and real application so you can understand how GEO works and translate it to projects, clients, or business.
Bloque 1
Here you will understand what GEO is, what it is not, and why the classic SEO framework alone no longer covers all decision-making in generative environments. You will also see how concepts like retrieval, embeddings, context, and brand recommendation work.
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Bloque 2
You will learn to build a serious methodology to measure visibility in AI, define prompt sets, record results, and audit what AI says about a brand, in what context it appears, and with what sources it associates it.
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Bloque 3
This block focuses on how to make a website easier to interpret, retrieve, and cite by generative systems. It works on structure, source of truth, RAG-friendly content, schema, and semantic clarity.
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Bloque 4
Here you will see how the game changes depending on the platform, how reputation influences, and what role co-occurrence, external mentions, and brand association play in generative visibility.
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Bloque 5
The course also gets into real execution: roadmap, maintenance, reporting, automation, GEO service sales, and vertical adaptation.
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Beyond the classes, the GEO Course includes tools, templates, and structures to apply what you learn with criteria in real projects.
Entre los entregables del curso se incluyen:
Module 0 – Deprogramming SEO (Mindset Shift toward GEO)
Module 0 Deliverables (Tools included)
Module 0 – Deprogramming SEO (Mindset Shift toward GEO)
Module 0 Deliverables (Tools included)
For years, digital visibility has been measured with metrics like impressions, clicks, CTR, or average position. But a growing part of the decision no longer happens there.
More and more users ask directly to ChatGPT, Gemini, Perplexity, or Copilot which company to choose, which tool to use, or which provider they recommend in their sector.
And the answer is no longer an infinite results page.
It's a shortlist.
If your brand doesn't appear in that selection:
The problem is that this loss of visibility usually doesn't appear in Search Console, Analytics, or in traditional SEO reports.
That's why GEO is not just about generating content for AI. It's about understanding how that new layer of recommendation forms and how to measure whether your brand is entering or being left out.
GEO, or Generative Engine Optimization, is the work oriented to improving the probability that a brand is understood, mentioned, cited, or recommended by generative engines like ChatGPT, Gemini, or Perplexity when a user makes a relevant query.
Simply put: if SEO seeks visibility on results pages, GEO seeks visibility in generative responses.
En esta página, GEO significa Generative Engine Optimization. No se refiere a geolocalización, sistemas GIS/geoespaciales, geografía ni geopolítica. En el contexto de este curso, el término se usa exclusivamente como optimización para motores generativos de IA.
GEO is not learning to use ChatGPT or launching prompts without method. Nor does it consist in promising guaranteed positions on engines that work probabilistically. A serious GEO approach requires measurement, audit, criteria, and real work on content, structure, entity, and reputation.
Working GEO involves analyzing what AI engines say today about a brand, what sources they retrieve, why they mention it or not, and how to improve the probability of mention, citation, and correct attribution.
In practice, a useful GEO strategy combines audit, LLM visibility measurement, RAG-friendly content optimization, entity work, external signals, and a roadmap applicable to business.
Visibility in generative engines is still in an early phase. In many categories, very few brands are working on this with method, consistency, and real measurement.
That opens a window of opportunity. Today it's still possible to gain visibility before others if you understand how generative engines read you, what signals they prioritize, and how to adapt content, entity, structure, and reputation to that new layer of recommendation.
But that advantage won't last forever. In the coming months, more brands, agencies, and teams will start working this territory with more resources, more content, and better signals, and when that happens, entering that visibility layer will be more difficult, slower, and more expensive than now.
Training now does not guarantee automatic results, but it does allow you to understand the terrain earlier, work with criteria, and start building visibility while others have not yet developed a clear methodology.
This GEO course is designed for professionals and teams already working in SEO, content, acquisition, or digital strategy and need to adapt their work to generative engines like ChatGPT, Gemini, and Perplexity.
It fits especially well in B2B marketing managers, SEO consultants, content teams, agencies, and medium or large companies that want to improve the probability of mention, citation, and attribution of their brand in generative environments with a serious methodology.
It's not a basic training to learn how to use AI tools. It's a course oriented to those who need to understand how to audit, measure, and apply GEO in real projects with a business focus.
A program designed so you don't stay in theory. The course combines fundamentals, methodology, audit, structure, measurement, and real application so you can understand how GEO works and translate it to projects, clients, or business.
Beyond the classes, the GEO Course includes tools, templates, and structures to apply what you learn with criteria in real projects.
The course includes about 80 hours of structured training so you go from «I know this exists» to «I know how to work it with criteria in real projects».
It's not training based only on theory or trends. The course includes systems and work frameworks designed to analyze how generative engines understand a brand and why they recommend some options over others.
The goal is not just to understand GEO, but to be able to apply it, document it, and explain it within a project, a company, or an agency.
The course is not framed as closed content, but as training that evolves with the changes of the environment.
To make the limits of the product clear from the beginning: This course is oriented to SEO, marketing, content, and agency professionals who need to work GEO with methodology, measurement, and real application.
The GEO Course is led by Asier López, CEO of Elevam, and is supported by the joint work of agency, methodology, and applied research developed from Elevam and Elevam Labs.
This approach starts from the HSA Protocol (Human · Search · AI), a framework that connects editorial clarity, search structure, and adaptation to generative engines.
From Elevam Labs we continuously analyze how engines like ChatGPT, Gemini, or Perplexity respond, what brands appear, what sources are cited, and what signals seem to influence mention, citation, and attribution, supported by a public line of GEO baselines.
That work translates into a concrete way of teaching GEO:
As additional track record reinforcement, the companies that today form Elevam were recognized in the Forbes List among the best SEO agencies in Spain.
This course is born from the combination of professional practice, methodological framework, and applied research to help work GEO with more rigor and less improvisation.
Access to the GEO Course has a current price of €499.
As a reference, the course was launched with special first-edition conditions and a reduced founders price. That initial phase was part of the launch and served to validate the product with the first seats.
Beyond access to the content, this edition includes:
The current price corresponds to the active phase of the course. If in the future the conditions, bonus, or access price change, it must be communicated explicitly on the page itself.
We do not propose an automatic refund guarantee. We prefer to be clear from the beginning: the goal of the course is to offer serious, useful, and applicable training. If you complete it and feel it has not given you real clarity, we review it reasonably.
More and more decisions start in generative responses, not in a classic SERP. That's why the course price is not only compared with €499. It also compares with the cost of continuing without understanding how that layer of recommendation, measurement, and visibility is built.
Yes, the course combines text and video. The theoretical part is in text so you can reread, copy, and reuse concepts, frameworks, and processes. The strategic, methodological, and practical part is worked in video to show criteria, decisions, and real application on GEO cases and scenarios.
No. This course does not promise guaranteed results or «being #1 in ChatGPT». Generative engines work probabilistically, so the course approach is based on verifiable fundamentals, audit criteria, and instrumented metrics to measure visibility, mention, and citation with a realistic methodology.
In this course, GEO means Generative Engine Optimization: a discipline of SEO, marketing, and generative AI aimed at improving the presence, mention, citation, and recommendation of a brand in responses generated by engines such as ChatGPT, Gemini, Perplexity, or AI Overviews. It does not refer to geolocation, GIS, geospatial data, geography, or geopolitics.
When you finish the course you will take a GEO audit with checklist and scoring, a prioritized roadmap, a RAG-friendly content guide, an entities plan, schema recommendations, a Share of Model (SoM) measurement framework, and repeatable SOPs to apply what you have learned with criteria in real projects.
It depends on each project's starting point. The usual in GEO is to first notice improvements in citability and structure, then greater consistency of mention and, over time, a more stable presence in generative responses. It's not an instant change, but a process that consolidates as the signals, content, and interpretation of the brand improve.
To evaluate if a GEO course is serious, look at whether it includes methodology to audit and measure visibility in generative engines, applicable deliverables, cases or real-use criteria, and a clear explanation of the limits of the work. Be wary of courses that only sell prompts, promise guaranteed results, or do not explain how to record and interpret changes in mention, citation, and attribution.
Elevam's GEO Course includes structured training, methodology to audit and measure visibility in generative engines, reusable templates and resources, support, and updates. It is designed for SEO, marketing, content, acquisition, consulting, and agency professionals who want to apply GEO with criteria in real projects and improve the probability of brand mention, citation, and attribution in ChatGPT, Gemini, and Perplexity.
A useful GEO course should include methodology, measurement, applicable deliverables, and clear criteria to work on visibility, mention, citation, and attribution in generative engines. It should also help to audit a brand, interpret what sources models prioritize, and translate that analysis into content, structure, entity, reputation, and action roadmap.
Yes. The course is designed for professionals and teams working in B2B marketing, SEO, content, acquisition, or agency and need to understand how visibility in generative engines influences brand consideration and choice. The approach combines audit, measurement, and real application to improve presence, mention, citation, and attribution in generative responses.
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