GEO
Generative artificial intelligence systems are increasingly shaping purchasing decisions. With a GEO Audit we analyse the digital and semantic foundations of the business, query generative environments to measure AI visibility, and define an optimisation strategy for AI-based search engines.
A company that is absent, or represented inconsistently, risks being excluded at precisely the moments when the decision is taking shape.
When a user asks an AI for advice on which solution to choose, the answer depends on how well that system knows and understands the brand, and on how far it considers it reliable.
An SEO audit assesses the technical and semantic factors that determine visibility in traditional search engines. A GEO Audit assesses whether the brand is structurally ready to be cited and recommended in the conversational contexts of AI.
The two approaches do not replace one another: they work together. The GEO Audit ensures that the brand is represented correctly by generative systems, where many purchasing decisions are now taking shape.
| Aspect | SEO audit | GEO audit |
|---|---|---|
| Objective | Analysing indexability, ranking and performance factors in search engines in order to build an SEO strategy. | Analysing how the brand is represented and how relevant it is within generative artificial intelligence systems, in order to build a GEO strategy that integrates with the SEO one. |
| Focus | Crawlability, indexing, relevance and semantic fit against the main search intents | Structural and semantic readiness of the brand for citation, LLM listening, visibility and consistency in AI answers |
| Unit of analysis | Site, backlinks, SERP. | Brand, semantic clusters, prompts, AI environments. |
| Key question | What is limiting organic rankings and what are the levers for improvement? | How and when is the brand represented in AI answers? |
| Main KPIs | Index ratio, traffic, rankings, CTR, visibility score | Share of presence, citation frequency, sentiment, context of mention and relevance within thematic clusters. |
| Output | Technical, editorial, semantic and UI priorities | Technical priorities, thematic gaps, sentiment analysis and exclusion risks |
The GEO Audit focuses on the brand’s presence, visibility and consistency within the clusters of answers generated by AI. To build a solid analysis, we take the following factors into account:
Readability for LLMs
Initial brand reputation
Web citations and E-E-A-T
Sentiment analysis
Brand sources
We offer an AI visibility analysis that maps the brand’s presence in the answers given by generative systems. The GEO Audit produced is the starting point for any GEO optimisation work.
We act on the technical requirements that make the site a source the AI can more easily cite.
We establish the requests for which the brand does not appear alongside its competitors, not just those where it is already present.
We analyse how the brand is represented today in language models. From that basis we identify the problems and define targeted measures to resolve them.
We build a path based on the specific problems of the brand, without applying predefined formulas divorced from the market context and from the competitors.
The GEO Audit is useful for companies operating in competitive markets, for B2B brands with long decision-making cycles, for organisations heavily dependent on their online reputation, and for businesses wanting to check whether AI systems correctly associate them with their own services.
Every analysis starts from an agreed strategic phase. Before beginning any activity, we define with you the services, products, target audience and competitors. This basis determines the topics and the entities related to the brand on which the whole audit is built.
We carry out an AI-oriented technical SEO analysis to assess how structurally “citable” the site is for generative systems. We check every element fundamental to SEO and add specific checks for AI environments.
We query AI environments through sets of prompts built around products, services, competitors, informational intents and comparative requests. We measure not only whether the brand appears, but in what role it is presented.
On the basis of the data gathered from the LLMs, we establish how the brand is cited and what its competitive framing is. We analyse share of presence, that is the brand’s relative weight against its competitors on the same set of prompts.
Having gathered the data, we map the risks of semantic exclusion. This stage covers association with critical reputational clusters and any mismatch between the actual positioning of the brand and the representation the AI generates.
All the analysis and the data gathered come together in a single strategic document, structured as an operational roadmap with priorities for action. Every analysis is overseen by a team of SEO specialists.
We set up monitoring of the brand’s visibility in AI-based search engines, using tools and models built for the purpose. This makes it possible to check progress and how the picture analysed evolves after the changes have been made.
We have carried out GEO Audit work for companies, associations, foundations and bodies active in national and international markets. The needs addressed vary: improving how the brand is represented in AI answers, checking its presence against competitors, and identifying reputational problems in the content generated by language models.
A GEO Audit is a structured analysis of a brand’s presence, visibility and consistency within generative artificial intelligence systems. It serves to establish whether and how the brand is cited, represented and recommended in AI answers, identifying technical problems, semantic gaps, reputational risks and opportunities for optimisation.
Yes. Technical and semantic SEO consultancy is the necessary basis for generative systems to be able to find and read the brand’s content correctly.
We use a proprietary model that combines specific metrics with composite indices. The main KPIs considered are: the presence of the brand, the level of citation (simple mention, comparative citation, in-depth treatment), the context and competitive framing, and the semantic associations triggered.
Timescales range from 60 to 90 days. That duration is not an arbitrary choice: it ensures that the data gathered is statistically meaningful. The answers given by AI models are variable by nature. One month is devoted to the LLM Listening Audit, which requires repeated querying in order to produce reliable results on which strategic decisions can be based. We deliver a solid document, not a snapshot.
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Get in touch to define the most suitable path together.
We analyse the starting context and identify the strategy geared to your objectives.