SPEAKERS:
Harry Foster, VP, Commercial Director, North America, performance.io
Matt Smith, Senior SEO Director, performance.io
KEY TAKEAWAYS:
• Organic search converts four to six times better than paid traffic
• Ninety-five percent of companies report zero Gen AI investment returns
• Fragmented site strategies create internal keyword cannibalization and waste
• LLM queries are longer and more conversational than traditional searches
• Consolidated domain architecture eliminates maintenance costs and internal competition
The trust crisis in pharma has reached a critical inflection point, with 80% of HCPs reporting skepticism toward digital content while patient confidence erodes across generations. Harry Foster of performance.io posed a fundamental challenge to pharma executives at Pharma Customer Engagement USA: "Do you know what the top 10 things in your disease state or therapeutic area that your patients are searching for? How can you establish trust if you don't know what they're thinking?"
The business case for addressing this gap is compelling.
"The data shows that organic traffic is four to six times more likely to convert compared to paid search,"
Foster explained, highlighting a dramatically more efficient engagement channel that delivers measurably higher conversion rates when pharma meets audiences at their moment of need.
The Cost-Trust Paradox Reshaping Digital Strategy
Pharma companies face simultaneous pressure on two fronts that are fundamentally reshaping digital engagement strategies. The macro-economic reality creates an urgent imperative for cost discipline and strategic investment decisions. "The US healthcare system costs twice as much per person compared to other large wealthy nations," Foster noted, as pharma faces intensifying government scrutiny, IRA implementation, and demands to accomplish more with constrained resources.
The trust dimension compounds this challenge significantly. Patient satisfaction with pharma continues declining, particularly among younger digital-native generations who seek health information through peer-to-peer channels rather than traditional sources. When asked whether companies truly understand patient search behavior, Foster challenged executives to examine whether their organizations actually know what patients are searching for in their therapeutic areas.
The solution lies in using search insights as a listening tool rather than a broadcasting mechanism. By analyzing what patients and HCPs actively search for—their questions, concerns, and information needs—pharma can shift from pushing predetermined brand messages to responding to actual needs. This approach addresses both the cost and trust challenges simultaneously: it improves ROI by focusing content resources on topics that audiences demonstrably care about, while rebuilding trust by demonstrating that pharma understands and addresses real concerns.
However, achieving this requires a fundamental shift in how pharma approaches agency relationships and digital strategy.
"We need to make sure that it's not just following the status quo, listening to what the agencies are telling you to do without validating and challenging them,"
Foster emphasized. Too often, pharma follows the status quo because agencies have financial incentives to recommend approaches that generate fees rather than optimize outcomes.
Breaking this pattern requires pharma to challenge assumptions, demand data-driven justification, and prioritize patient outcomes over agency convenience. The current environment of cost pressure and eroding trust makes this strategic reassessment not just advisable but essential for companies seeking to maximize digital investment returns while rebuilding credibility with key stakeholders.
AI Investment Reality Check and LLM Fundamentals
While AI dominates industry conversation—with companies mentioning AI in earnings calls seeing stock price increases averaging 8.5%—the return on actual AI investments tells a different story. An MIT study found that 95% of companies report zero return on Gen AI investments despite $30-40 billion in collective spend. Matt Smith of performance.io used this data to advocate for a cautiously optimistic approach that makes pace without creating waste.
Smith provided an accessible framework for understanding the LLM shift through a Facebook analogy. "Back in 2006, Facebook introduced a new feature on their platform," Smith explained, describing how users previously navigated individual profiles to view content. "This is what LLMs are doing now with basically the wider Internet," he noted, highlighting how AI aggregates and personalizes information from across the internet in ways that fundamentally change information access patterns.
The behavioral changes are measurable and strategically important. "What we absolutely do know is that the searches that they are making are much longer, they're more conversational and they're more detailed," Smith observed. "So they are potentially more qualified once they interact with this chatbot and then go to your website because they have done their research before."
This suggests that traffic arriving from AI sources may be further along in their decision journey, having conducted more thorough research before reaching pharma websites.
Critically, Smith emphasized that existing SEO capabilities translate directly to LLM optimization. Referencing Danny Sullivan from Google, Smith noted that "the fundamentals of SEO very much are correlated with what we're doing with AI and LLMs." This insight is strategically important because it means companies need not completely rebuild their approach or make risky bets on unproven AI platforms.
However, Smith also injected a dose of skepticism about AI analytics claims. "If you see on LinkedIn someone spouting some specific data set around the amount of queries for a subject area, I would call BS," he stated bluntly. Because LLM databases remain largely private, precise query volume data is unavailable despite vendor claims to the contrary.
This uncertainty demands that pharma focus on strengthening foundational capabilities—technical infrastructure, content quality, citation relationships—that deliver value across both traditional search and emerging AI channels, reducing investment risk while building genuine AI readiness.
The Agency Fee Model and Cannibalization Problem
Foster delivered a pointed critique of the prevailing agency model in pharma digital strategy, describing a pattern that creates waste while reducing effectiveness. The typical scenario involves agencies recommending that pharma brands maintain multiple separate websites for different audiences and purposes.
"You have 12 different sites that they're being told they need: one for HCPs, patients, disease states, resources, market access, etc.," Foster explained. "Each one of these sites then needs all the build and development costs... and your top competitors are the other 11 sites from your own company."
This fragmented approach creates a fee generation machine that benefits agencies through multiplied build costs, separate campaign management, and repeated regulatory review cycles. But the business impact for pharma is deeply negative. Each site dilutes the SEO authority that would accrue to a consolidated domain, while maintenance costs multiply across properties. Most problematically, these sites compete with each other for the same keywords, creating internal cannibalization where a company's own digital properties become its primary competitors in search results.
The alternative—a consolidated one-domain approach using a unified technology platform—eliminates this waste systematically. A single property concentrates SEO authority, reduces maintenance costs, simplifies user experience, and eliminates internal competition. Foster emphasized that when this consolidation is executed properly, it delivers sustainable organic traffic by aligning company strategy with what audiences actually seek.
The technical benefits extend beyond SEO to user experience, as visitors navigate a consistent interface rather than encountering different designs and functionality across brand properties.
However, implementing this requires challenging entrenched agency relationships and potentially confronting internal organizational silos that prefer separate sites. "We need to make sure that it's not just following the status quo, listening to what the agencies are telling you to do without validating and challenging them," Foster reiterated. Pharma must validate and challenge agency recommendations rather than accepting them as given, prioritizing patient outcomes and business efficiency over agency fee structures.
Beyond Vanity Metrics to Commercial Signals
The final pillar of the performance.io framework addresses measurement, where Foster argued that current approaches focus on surface level metrics like clicks and impressions rather than meaningful business outcomes. Using a vacation analogy, he noted that success isn't measured by photo count but by the quality of experience—the time with family, the ability to recharge and return refreshed.
When executed properly, search delivers traffic that takes high-value actions indicating commercial intent: patients understanding how to initiate, switch, or titrate therapy; doctors requesting rep visits or medical science liaison sign-ups; meeting connection requests. "These are all key commercial buying signals that deliver dynamic script lift," Foster explained. This measurement framework enables sophisticated optimization that connects digital activity directly to revenue outcomes rather than relying on proxy metrics that may or may not correlate with business results.
This measurement shift enables strategic decisions based on actual ROI rather than volume metrics. Companies can identify which search queries and content types drive the highest-value actions, optimize the balance between paid and organic channels based on conversion efficiency rather than traffic volume, and directly connect search investments to revenue outcomes. The conversion advantage Foster cited earlier—"organic traffic is four to six times more likely to convert compared to paid search"—becomes actionable when measurement systems track these meaningful outcomes rather than vanity metrics.
The path forward requires balancing optimism about AI's potential with realism about implementation challenges. Foster and Smith emphasized making pace without waste—strengthening SEO fundamentals that translate to LLM performance, consolidating fragmented digital properties to eliminate internal competition, and measuring what truly matters for business outcomes.
Most critically, pharma must challenge the status quo, validate agency recommendations against data, and swim their own race rather than following predetermined playbooks that serve agency interests over patient needs. "If there's one thing you do today, go back and challenge your agency, ask them the questions, make them validate why they're selling you what they do," Foster urged. "Because if it's not in the best interest for you, it's definitely not in the best interest for patients."
In an environment of cost pressure, trust erosion, and technological disruption, this strategic independence becomes essential for companies seeking to maximize digital investment returns while genuinely serving patient and HCP information needs.
In order to get you the highlights of Pharma Customer Engagement USA 2025 faster, we are using generative AI technology to summarise the transcripts of the sessions. The conference organiser is checking the summary for accuracy. If you have any feedback about the summary, please contact lucy.fisher@thomsonreuters.com.
Discover more on this topic at Pharma USA 2026 (March 17-18, Philadelphia) - North America's largest cross-functional pharma gathering. Visit the website here.
