Search is no longer just about ranking — it's about being the source AI models cite when patients and HCPs ask questions directly. Neil Patel, co-founder of NP Digital, argues that the old SEO playbook is being replaced by Generative Engine Optimization (GEO) and Answer Engine Optimization (AEO) — a shift where structure, clarity, and citation-worthiness matter more than backlinks and keyword density. In this session, Neil makes the case that traffic alone is a vanity metric in 2026; what matters now is whether AI systems trust your content enough to surface it as the answer. For pharma marketers navigating strict compliance and review cycles, this raises a critical question: how do you build content that earns AI trust and citation, without sacrificing the accuracy and control regulated content demands? Neil will break down what's actually working across real GEO/AEO campaigns and what pharma CX and content teams need to rethink before their next content strategy cycle.
Neil Patel is the co-founder of NP Digital, Crazy Egg, Ubersuggest, and Hello Bar. The Wall Street Journal calls him a top influencer on the web, Forbes says he is one of the top 10 marketers, and Entrepreneur Magazine says he created one of the 100 most brilliant companies. Neil... Read More →
For years, pharma marketing has measured success by traffic — sessions, page views, time on site. That model is collapsing. AI Overviews, chatbot answers, and zero-click search results mean HCPs and patients increasingly get what they need without ever landing on a pharma website. The question isn't whether this shift is coming — it's already here. So what does marketing look like when the destination disappears? This keynote confronts the uncomfortable reality that "driving traffic" may be the wrong goal entirely, and reframes success around a harder, more urgent question: is your brand the source AI systems trust enough to cite, recommend, or answer with — even when no one ever clicks through? For pharma marketers still optimizing for a web that's quietly disappearing, this is the wake-up call.
Pharma has no shortage of data. The challenge isn't collecting more—it's using it to shape what happens next. This session explores how behavioral intelligence can transform marketing from a series of campaigns into a self-improving system: one that anticipates treatment opportunities, adapts in real time, and learns from every interaction. The result is a flywheel that makes every engagement more relevant, every campaign more effective, and every insight more valuable than the last.
Key takeaways:
Why behavioral intelligence is reshaping the future of pharma marketing.
How predictive signals can identify opportunities before they're visible in traditional reporting.
What it takes to build marketing systems that continuously learn and improve.
For most pharmaceutical product marketers, success is measured by product launches, market adoption, and commercial performance. Their days are spent balancing campaigns, regulatory requirements, stakeholder alignment, agency management, and increasingly complex launch timelines. Corporate brand has traditionally played only a limited role in that work.
That is beginning to change. Across the pharmaceutical industry, more organizations are investing in stronger enterprise brands, establishing centralized marketing functions, and creating greater consistency across product portfolios. While those strategic decisions are made long before implementation begins, product marketers are often the teams who experience them most directly through new governance, shared brand systems, portfolio decisions, and enterprise rollout plans.
In our experience helping large pharmaceutical organizations move these decisions into execution, we've seen where product marketing and corporate brand teams complement one another, where implementation creates friction, and what helps organizations make the shift successfully. This session will help product marketers understand why this evolution is happening, what to expect as corporate brand becomes more active, and how to leverage it to strengthen product launches, build stakeholder alignment, and maintain the distinct equity that makes individual product brands successful.
For most pharma brands, personalized content at scale means leaning on an agency partner — more capacity, more creative firepower, but also more handoffs, longer turnaround, and less control. Doug Nelson, [title] at Orasis Pharma, took a different path: building an in-house agentic AI platform designed to generate personalized content at the speed the business actually needed. In this session, Doug shares the real story behind that decision — what pushed Orasis to build rather than buy, what the platform actually does, and what changed (and what didn't) once content creation moved in-house. This isn't a pitch for AI as a cure-all; it's a candid look at the tradeoffs of ownership versus partnership, speed versus scale, and control versus capacity. For any marketer weighing whether to build their own AI capability or lean harder on external partners, this is a real-world data point, not a theory.
For decades, HCP engagement has meant segmenting physicians into broad buckets — specialty, tier, prescribing volume — and hoping the message lands. AI is breaking that model. Today's HCPs expect experiences shaped by their actual behavior, preferences, and moment-in-time needs, not a persona built from last year's data. But personalization at scale raises hard questions pharma marketers can't ignore: How much precision is genuinely useful versus invasive? Where does AI-driven relevance end and algorithmic guesswork begin? And what does trust look like when the HCP knows they're being read by a machine? This panel brings together CX and digital leaders reimagining the HCP journey from the ground up — exploring what it actually takes to move from segmentation to true individualization, and what pharma stands to gain (or risk) in getting there first.
Chief Marketing Office, Global Customer Excellence, Pfizer
Wayne Simmons is a commercial-focused customer experience leader within the Chief Marketing Office (CMO) of Pfizer, where he is responsible for crafting a first-of-a-kind global customer excellence strategy and leading the adoption of customer-centric ways of working within brand... Read More →
How merging digital engagement with syndicated data is powering precision, compliance, and smarter HCP strategies.
Pharma marketers are sitting on a goldmine of data, but it often lives in silos. This session explores how uniting digital engagement signals with syndicated datasets can unlock a true 360° view of HCP behavior. Learn how leading teams are overcoming integration challenges, ensuring compliance, and transforming raw data into actionable insights that drive precision targeting and smarter engagement strategies.
AI can now personalize content down to the individual HCP or patient — the right message, the right channel, the right moment. But precision isn't the same as empathy, and pharma marketers are running into an uncomfortable tension: the more targeted the experience, the more mechanical it can start to feel. This session digs into a question the industry hasn't fully answered — can personalization built by algorithms ever carry the warmth, nuance, and trust of genuine human connection? Or is pharma optimizing for relevance while quietly losing the thing that made engagement feel real in the first place? Expect a candid look at where AI-driven personalization is winning patients and HCPs over, where it's backfiring, and what "empathy at scale" actually requires beyond better data.
The traditional marketing funnel assumes a patient moves neatly from awareness to consideration to action. That assumption no longer holds. Today's patients bounce between search, social, symptom-checkers, AI chatbots, caregiver forums, and their HCP — often in a different order every time, and rarely in a straight line. This panel explores what happens when journey mapping stops trying to force patients into a linear path and instead reflects how people actually move: nonlinear, recursive, and driven as much by moments of doubt as moments of intent. In this session, participants share how they are rethinking journey design for a post-linear reality — what gets built differently, what gets measured differently, and what pharma marketers need to unlearn about the funnel model that's shaped the industry for decades.
Pharma sits on more customer data than almost any other industry — prescribing data, claims data, CRM data, digital engagement data, syndicated market research. And yet ask most brand teams to describe their customer beyond a segment or a persona slide, and the answer gets vague fast. This session confronts an uncomfortable paradox: why does more data so rarely translate into more understanding? The problem isn't a lack of information — it's fragmented systems, siloed teams, and a culture built around reporting metrics rather than generating insight. Expect a hard look at where pharma's data infrastructure is actually failing its marketers, what "knowing the customer" should mean in 2026, and what it would take to turn all that data into something a brand team can actually act on.
A leadership-driven look at how the role of the field rep is being redefined by personalization and content-driven engagement — and what it takes to lead teams through that shift. Dina draws on her own leadership experience to explore how field engagement strategies must evolve alongside personalized healthcare content, and what leaders need to unlearn to get there.
As AI-powered platforms like ChatGPT and Gemini reshape how consumers, patients, and HCPs seek health information, pharmaceutical brand perception is increasingly being shaped by algorithms, not ad budgets. LiveWorld’s new AI Brand Reputation Index evaluates how 50 top-selling pharmaceutical brands are portrayed by leading AI tools. This isn't just about digital presence—it’s about the stories AI is telling based on a mix of clinical data, HCP sentiment, patient experiences, and online discourse. As AI becomes the new front door to healthcare information, understanding and managing your AI reputation is no longer optional—it's essential.
Key Takeaways:
AI Is the New Healthcare Gatekeeper: Over 30% of patients already rely on AI for health questions, with usage accelerating across HCPs as well.
Reputation Is Algorithmically Built: AI combines structured data with public sentiment, media narratives, and online conversation to shape brand perception.
Traditional Tactics Fall Short: SEO and ad strategies alone can’t influence AI output—brands must actively manage how AI understands and presents them.
