Real outcomes from AI-readiness audits for pharmaceutical companies.
Featured case study
A leading pharmaceutical treatment brand had invested significantly in digital content. Traditional analytics showed strong performance: good traffic, solid engagement metrics, and competitive SEO rankings.
But the marketing team had a nagging question: Why weren't they seeing the expected impact from their digital investments?
They suspected something was happening upstream - before users ever reached their content - but had no way to measure it.
We conducted a comprehensive AI-Readiness Digital Audit, analysing their key brand assets against competitors across 10 evaluation dimensions and all leading AI models.
Audited primary brand website, HCP portal, and patient materials
Benchmarked against 3 key competitors in the therapeutic area
Tested citation probability across GPT-5, Claude, Gemini, and 7 other AI models
Identified specific content gaps affecting AI perception
Our analysis revealed a 17%+ citation probability disadvantage compared to the leading competitor - a performance gap completely invisible in Google Analytics.
Traditional metrics showed strong engagement, but AI systems consistently favoured competitor content when answering health-related questions in this therapeutic area.
Information hierarchy made it difficult for AI to extract key facts. Competitors used clearer semantic structure.
Missing citation patterns and credential indicators that AI systems use to assess trustworthiness.
Schema markup and metadata gaps reduced AI's ability to interpret content context.
Content didn't directly address the specific questions AI systems were trying to answer.
Armed with specific, prioritised recommendations, the brand team was able to:
"For the first time, we could see what was happening before users reached our content. The gap was real, and now we knew exactly what to fix."
The bigger picture
Strong engagement metrics don't mean AI systems are surfacing your content. These are different evaluation processes with different criteria.
Every time an AI system answers a question using competitor content instead of yours, you lose an opportunity to shape the narrative.
You can't fix what you can't see. Quantifying AI perception transforms vague concerns into specific, actionable improvements.
We're documenting additional client outcomes across different therapeutic areas and content types. Want to be notified when new case studies are published?
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