How a Global Pharmaceutical Company Grew From Minimal AI Visibility to a 45% Mention Rate in Four Months

The same priority therapeutic areas were monitored repeatedly over four months. The monitoring tracked where the company appeared, how frequently it was mentioned, which types of questions generated visibility and which sources were being used to construct the answers. This created a consistent baseline for measuring change rather than relying on a single snapshot.

The monitoring was broken down by therapeutic area to identify where visibility was developing fastest and where further work was required. This showed that the company's AI search presence was not concentrated in a single topic. By the latest monitoring round, it was appearing across several of the monitored therapeutic segments. The segment-level analysis was then used to guide the next monitoring and optimisation priorities.

Our team reviewed the sources used across the monitored AI answers alongside the brand visibility data. This made it possible to distinguish between answers where the company was simply mentioned and answers where its own website was actively being used as supporting information. First-party citation visibility increased over the monitoring period, with company-owned pages appearing more frequently as sources in later rounds. The latest monitoring therefore showed improvement across two separate layers: the company was appearing in more AI-generated answers, while its own website was also beginning to contribute more directly to those answers.

The company website was analysed specifically from the perspective of AI retrieval and citation readiness. The technical analysis covered 21 pages across 10 representative page templates and reviewed AI crawler accessibility, indexability, JavaScript dependency, content extractability, page and section structure, metadata, structured data, machine-readable freshness signals and technical page performance. The analysis identified a number of opportunities affecting how easily individual pages and passages could be understood, extracted and reused by AI systems.

Technical accessibility issues identified during the work were addressed to create a stronger foundation for AI discovery and retrieval. The latest technical check confirmed that the website was fully open to the measured AI crawler set. AI crawler access reached 100%, all sampled pages were indexable and the core content of the tested pages was available without requiring JavaScript rendering. This meant that basic accessibility was no longer the main technical constraint.

With the access layer in place, the next stage focused further down the retrieval process. The technical analysis identified additional opportunities around content extractability, page structure, machine-readable dates, metadata, structured data and page performance. These findings created a more detailed GEO roadmap for making the company's authoritative website content easier for AI systems to retrieve and cite.

Each new monitoring round was used to identify where visibility and citation presence were increasing and where gaps remained. As the company became more visible, the focus of the work evolved from establishing AI search presence toward strengthening visibility across individual therapeutic areas and increasing first-party citation coverage.