Introduction

The statistic haunts every pharma launch team: only one in five failed launches can recover. For Simone Rebora, Global Marketing Director, this number defines the entire customer engagement imperative. "20% is the number when we say that only 20% of the failed launches are able to significantly change the trajectory or better improve their launch," he explained. Operating across 190-plus countries with complex hematology-oncology products, Rebora has learned that the margin for error is minimal and the consequences of poor execution are nearly permanent.

"If I launch badly, I have only a 20% chance to make my bad launch into a good launch. So it's practically very, very low," he stated. His framework for launch excellence challenges conventional wisdom about AI adoption, content strategy, and the fundamentals that most organizations skip. The stakes are clear: get it right the first time, or face an 80% probability of permanent underperformance.

The Fundamentals-First Philosophy in Global Markets

While the industry rushes toward AI and advanced analytics, Rebora offers a sobering warning from six years of next best action (NBA) implementation. The problem isn't technology capability—it's strategic readiness. Organizations deploying sophisticated tools without foundational customer knowledge are building on unstable ground, creating expensive systems that can't deliver value because basic questions remain unanswered.

"If we don't fix the basics, we can forget about AI. I daily speak with external partners that propose amazing tools to me. But we don't know how we can use them," Rebora said. Before considering AI-driven personalization or predictive analytics, launch teams must answer fundamental questions: Where are patients? What are prescriber volumes? Who are the actual customers?

This isn't data that can be inferred—it requires direct intelligence gathering, sometimes as straightforward as knocking on doors and asking. "How many patients do we have, where are they, and how many high prescribers can we have? We don't need AI. We have to go to the HCPs, knock on the door and ask," he emphasized.

This fundamentals-first philosophy stems from practical experience managing launches across massive geographic complexity. "In EMEA we have more than 100 countries, in the Americas more than 30," Rebora noted. He has seen external partners propose "amazing tools" that organizations can't effectively use because strategic clarity is missing. The result: technology adoption without impact, innovation initiatives without outcomes, and digital transformation programs that fail to transform anything meaningful.

The sequence matters critically. Customer identification must precede targeting and profiling. Targeting must precede persona creation. Personas must precede message library development. Only after these foundations are solid can NBA engines and AI assistants add value. "I started working on my NBA more than six years ago," Rebora shared, highlighting the extended timeline required for meaningful implementation.

Balancing Comprehensive Libraries with Communication Discipline

The tension in pharma content strategy is genuine: prescribers need comprehensive information across diverse clinical scenarios, yet cognitive limits demand simplicity. Rebora's resolution is architectural—a comprehensive message library enabling AI-driven recommendations, while human communication maintains disciplined focus on core differentiation.

Message libraries should contain roughly 40–50 key messages, varying based on clinical trial volume and subgroup analyses. This comprehensiveness enables AI systems to match content to specific contexts, markets, and customer characteristics. However, when human account managers engage prescribers directly, only three core differentiation elements should be communicated—distilled to fit a 15-second elevator pitch.

"I always say to my team: three key elements of differentiation, not more. Then we can talk about personas, about the next best action content. But if I had to meet the customers in the elevator, in the famous elevator pitch, 15 seconds, three elements and stop," Rebora stated. The library scales; the human message doesn't.

However, this architecture demands significant upfront investment and rigorous discipline. Content must be developed across the full library before launch, not iteratively added afterward. More critically, every message requires testing before deployment—through advisory boards, market research, or AI validation.

"Before delivering the key messages and the right content to incorporate in the next best action, please test them because if you make a mistake, you're going to waste time for two, three months," Rebora warned. The cost of content errors in launch scenarios is measured in months, not weeks. In an environment where the first six to nine months determine trajectory, losing two to three months to untested messaging can shift a launch from the recovering 20% to the failing 80%.

Why Launch Trajectory Becomes Fixed Quickly

Launch timing creates unforgiving dynamics. Rebora's experience across hematology-oncology products reveals that the first six to nine months establish trajectory in ways that become nearly impossible to alter afterward. "The first six months make the launch—maybe six is quite challenging. We can say nine months, but after nine months we have launched. If we fail, don't forget it—only a 20% chance to change the trajectory," he explained.

This compressed window demands that all elements—customer intelligence, targeting, personas, message libraries, engagement infrastructure—be operational at launch, not developed iteratively. Geographic complexity amplifies this challenge: diverse healthcare systems, regulations, languages, and cultures, plus exogenous factors such as geopolitical and economic conditions and entrenched competition.

The strategic question becomes how to maximize influence over controllable elements: customer engagement, content strategy, channel optimization, and timing precision. Traditional approaches often underfund pre-launch preparation, assuming that issues can be fixed post-launch. But if trajectory is largely fixed after nine months, and only 20% of poor launches recover, that assumption is demonstrably false.

Investment must therefore shift upstream—to customer identification, message testing, and engagement infrastructure—even if this extends preparation timelines or delays launch dates. The alternative is accepting an 80% probability of permanent underperformance. In competitive therapeutic areas with significant commercial stakes, that's not a risk; it's a near-certainty.

Integrating Strategic Intelligence with Tactical Preparation

Despite six years implementing NBA systems, Rebora identifies a capability gap that represents the next evolution in customer engagement: integrating strategic content recommendations with individual HCP-level AI simulation for call preparation.

Current systems typically operate at the persona or segment level—recommending content based on behavioral patterns or archetypes. Similarly, AI training avatars usually represent generic personas rather than specific physicians.

Rebora envisions connecting these capabilities in transformative ways. "What I'm still missing is creating an ideal avatar per single HCP where my key account manager can train, can, let's say, have what I call call optimization," he explained. Account managers would receive NBA recommendations for a specific doctor, then practice the conversation with an AI avatar trained on that individual physician's characteristics, preferences, and communication style before the actual call.

This integration would address the translation gap between strategic recommendation and effective execution. Knowing what to discuss matters, but so does knowing how to discuss it with this specific person. The approach would also create continuous feedback loops—real-time insights from field interactions would inform both content optimization and avatar refinement, enabling day-to-day improvement during critical launch windows rather than waiting for formal research cycles.

Rebora acknowledges this integration remains aspirational. The technical requirements are substantial: connecting CRM, NBA, and simulation platforms; developing AI sophisticated enough for believable individual representation; and gathering sufficient data for HCP-specific modeling. Ethical considerations around the depth of physician profiling also require careful navigation.

Yet the direction is clear. As pharma customer engagement matures beyond segment-level personalization toward true one-to-one preparation, organizations that successfully integrate strategic intelligence with tactical simulation will create competitive advantage in an environment where first-time execution determines outcomes. For launch teams operating under the shadow of that 20% recovery statistic, the ability to prepare account managers for individual physician conversations—with both the right content and the right delivery approach—could represent the difference between trajectory success and permanent underperformance.

KEY TAKEAWAYS:

• Only 20% of failed pharma launches successfully change trajectory after poor starts
• Fundamental customer intelligence must precede AI deployment across all markets
• Message discipline requires exactly three core differentiation elements for memorability
• The critical launch window spans six to nine months before trajectory becomes fixed
• Next best action integration with HCP-specific AI avatars represents the frontier

To get you highlights of Pharma Customer Engagement EU faster, we are using generative AI technology to summarise the transcripts of the sessions. If you have any feedback about the summary, please contact lucy.fisher@thomsonreuters.com.

"Historically we always wanted to be customer centric, but now we have the data and the operations to understand our customers, evolve to where they are, and let them tell us what they require and what they need,"

Canlas explained.

SPEAKERS:

Chiara Bolognini, Global Lead CX, Marketing and Sales, Roche
Kruti Popat, Director of Customer Experience, Boehringer Ingelheim
Yvette Venable, Head Global Market Access, Payer Partnerships and Policy, AstraZeneca
Jalilah Gibson, Associate Partner, Wavestone (Moderator)
KEY TAKEAWAYS:
• Fragmented touchpoints erode trust when customers experience pharma companies as different people across functions
• Early R&D engagement with payers and regulators prevents costly market access evidence gaps
• Patients consolidate all stakeholder perspectives, making patient experience the ultimate engagement quality test
• Human expert interpretation prevents data misattribution that misdirects strategy and wastes resources
• AI-powered responsive ecosystems enable customers to choose content rather than receive pushed messages

Imagine meeting a pharma company representative who speaks eloquently about patient outcomes, then encountering the same company through customer service where the tone, messaging, and approach feel completely unfamiliar. This jarring disconnect defines the current state of pharma customer engagement. "If you move for example, from sales to customer service, they feel lost our customer experience," Chiara Bolognini explained at Pharma Customer Engagement Europe 2025.

As Jalilah Gibson reinforces, "Our customers don't care which company we work for or which part of the function that we work for, but they do care when they get a very disjointed experience."

From Fragmented Touchpoints to Unified Ecosystems

The pharma industry's traditional organizational structure creates silos that customers experience as disconnected interactions. Sales, medical affairs, market access, and patient support each optimize their own engagement models without coordinating on how the company's identity is expressed across the patient journey. Trust, the foundation of prescribing influence and treatment adherence, erodes when customers cannot recognize consistent company presence.

"It's designing ecosystems where our customers can thrive, where we build the familiarity with them and basically expose them to best attributes of our identity," Bolognini emphasizes. This shift from isolated touchpoints to integrated ecosystems requires governance that operates above functional levels, with authority to transfer methodologies across commercial, medical, and patient partnership organizations.

For Kruti Popat, the strategic imperative is clear. "Delivering a seamless customer experience is not nice to have. It's really important strategic imperative. It's a really great differentiator," she notes, particularly in complex environments like the UK's NHS where multiple stakeholders each have distinct needs yet expect coherent company engagement.

The ecosystem approach extends beyond commercial interactions to the earliest stages of development. Yvette Venable describes how AstraZeneca's "Transforming Healthcare" framework orients all teams toward patient outcomes and health system resilience. "It's crucial that we're talking to patients, to payers and policymakers, and also to clinicians very, very early on in R&D in order to make sure we can change those paradigms over time," Venable explains.

This early engagement prevents the costly disconnect between regulatory approval and market access that plagues many launches when evidence generation fails to address payer requirements.

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Discover more on this topic at Pharma 2026 (22-24 April, Barcelona) - the global collaborative network for leading pharma innovators. Visit the website here.

The Patient as Universal Stakeholder

Patients aren't just another customer segment; they represent the consolidation point of all stakeholder perspectives. Healthcare providers treating patients today become patients themselves tomorrow. Policymakers making reimbursement decisions will eventually navigate the healthcare system as caregivers or patients.

"The patient is the consolidation of all our customers. Each of us in the company, so experiencing the perspective of the patient and the customer experience is fundamental," Bolognini emphasizes. This perspective shift has profound implications for how companies design information architecture and support systems across disease awareness, diagnosis, clinical trial participation, treatment initiation, and long-term management phases.

Yet the industry still struggles to move beyond transactional engagement models. "We as an industry do so much better today than we ever have on patient engagement, but at the same time, we're still not doing it well enough," Venable observes. The gap lies in viewing patient engagement through the lens of extraction rather than true partnership with mutual benefit.

Structural issues within organizations, where patient advocacy teams, patient support programs, and commercial patient engagement operate independently, create the same fragmentation patients experience externally.

The solution lies in persona-based approaches that maintain message consistency while adapting delivery. "It's understanding what is important to these personas, what's the value, what language resonates for them. You're still using the same content thread, you're not amending the content," Popat explains. For HCPs with high empathy toward patient journeys, the same clinical evidence is delivered with emphasis on patient experience rather than purely clinical endpoints.

Bridging the Evidence Gap Through Multi-Stakeholder Dialogue

A critical challenge in pharma development is the misalignment between regulatory requirements and payer value recognition. Clinical trials are designed using validated endpoints that satisfy regulatory approval, but health technology assessment bodies and payers often require different evidence, particularly hard outcomes rather than intermediary endpoints.

Venable shared a powerful example from AstraZeneca's experience with a chronic condition therapy. The regulatory-approved intermediary disease progression endpoint wasn't acceptable to payers demanding solid heart outcomes. However, extending trials to capture those outcomes would take so long that withholding new treatments from patients would be unethical.

"We got the regulators, the payers, clinicians and patients in a room together to have a conversation about how meaningful these endpoints were," Venable recounts. The resulting dialogue revealed striking disconnects, with clinicians sometimes "literally head in hands going, how do you not understand how important this is to clinical practice?"

While the immediate outcome didn't change payer positions on endpoint acceptance, it initiated the long-term process of building shared understanding across stakeholder groups that often operate in isolation from each other. This example illustrates why early multi-stakeholder engagement in R&D is essential.

When market access teams, medical affairs, and R&D collaborate from early development stages, they can shape trial designs that satisfy both regulatory approval and value demonstration needs. The alternative creates costly delays and restricts patient access to innovations.

Insights, AI, and the Human Interpretation Imperative

The pharma industry is investing heavily in data analytics, real-world evidence, and AI-powered insights to understand customer behavior and optimize engagement. Yet without human expert interpretation, these investments can generate misleading conclusions that misdirect strategy and waste resources.

Venable illustrated this risk with a striking anecdote about real-world evidence analysis. Data showed consistent patient treatment drop-offs at six months, which analysts attributed to intolerable side effects. "You bring a patient expert in and they look at that data and they go, well yeah, you need refrigeration and cold chain and everybody goes on holiday in August," she explained.

The operational reality was invisible in the data itself but immediately obvious to patients living that experience. As Gibson reflects, "Too often we've sat in data point and go, why is that happening without asking actual customers." This gap between data observation and customer validation leads companies to address the wrong problems.

The solution requires building patient expert consultation into data interpretation processes, not just data collection phases. Roche has developed sophisticated infrastructure to consolidate insights while enabling actionable application. "We have actually created a wonderful insights platform called Before Insights Intelligence, linking to our R&D excellence program to basically identify commercial ability of our molecules," Bolognini describes.

The platform uses large language model interfaces, allowing marketers to request insights for specific strategic needs rather than analyzing dashboards themselves.

Responsive Ecosystems and the AI Transformation

The convergence of these themes points toward a fundamental transformation in pharma customer engagement. The future belongs to responsive ecosystems where customers choose their own content through AI-powered interfaces rather than receiving pushed messages through predetermined channels. Large language models connected to validated company knowledge bases can provide instant, personalized responses while maintaining narrative consistency across stakeholder groups.

This technological capability must be balanced with human insight. Emotional journey research, patient expert validation of data interpretations, and persona-based delivery ensure that efficiency doesn't come at the cost of empathy. "Delivering a seamless customer experience empowers accelerated decision making and therefore ultimately patient outcomes," Popat notes.

The companies that will differentiate themselves are those that establish governance above functional silos, co-create narratives across medical affairs and commercial teams, and engage multiple stakeholders from early R&D through market access. Technology enables scale, but human expertise ensures relevance and trust.

The pharma industry's ultimate customer, the patient, navigates a complex ecosystem involving diagnosis, treatment decisions, adherence challenges, and disease management. When companies design experiences that support patients through these transitions with consistent identity, validated insights, and responsive support, they build the trust that influences not just individual treatment choices but entire standards of care. The shift from fragmented touchpoints to unified ecosystems isn't merely operational improvement. It's the foundation for delivering meaningful health outcomes at scale while strengthening relationships across every stakeholder group that influences patient access to innovation.

To get you highlights of Pharma Customer Engagement EU faster, we are using generative AI technology to summarise the transcripts of the sessions. If you have any feedback about the summary, please contact lucy.fisher@thomsonreuters.com.

"It's the combination of the patient and the HCP journey. As the patient is living with their disease for two years, three years, the information that physician needs is very different than the patient that walks in and says, 'I have these symptoms and I don't know what's wrong with me.'"

explained Dalton.

Wall highlighted the importance of considering the entire patient journey, not just the initial prescription: "One of the things I think we don't talk enough about is that it isn't just that first script. Part of the journey is also when you stay on something, and your physician helps you throughout the entire journey."

Cross-Functional Collaboration and Implementation

Successfully implementing omnichannel strategies requires breaking down traditional silos between departments. Canlas emphasized the importance of cross-functional teams that include "the entire commercial customer engagement, commercial operations team, the brand team, medical, legal, regulatory, and privacy."

The panel agreed that involving compliance teams early in the process is essential. "Having very good conversations and transparent conversations with your compliance colleagues are just key," said Canlas. "Leaning in, bringing them in that level of inclusion earlier in any experiment that you're looking to do, any sort of journey mapping exercise, is so key."

Measuring Success Beyond Activities

When asked about the most impactful KPIs for omnichannel marketing, the panel emphasized business outcomes over activity metrics. "MBRX [market basket Rx]," Canlas stated firmly, "because that is the culmination of all of the efforts. That means that physician and that patient have made a choiceful decision to start therapy."

Wall cautioned against metrics that focus solely on output: "Often I hear my friends and colleagues talk about how much they did, how many assets they created, how many channels they're on... if at the end of the year those people write in their self-input, 'I created a lot and I did more,' then we're measuring the wrong things."

Key Takeaways

1) Patient-centricity drives effective omnichannel: "It's the combination of the patient and the HCP journey... You start with the patient, identify then who are the HCPs in that moment," said Canlas.

2) Content strategy requires fundamental transformation: "Instead of that claim, chart, and table, we need to think about five claims, three different ways to display that data, and four different charts," explained Dalton.

3) Cross-functional collaboration is essential: "It's bringing the entire commercial customer engagement, commercial operations team, the brand team, medical, legal, regulatory, and privacy together," noted Canlas.

4) Measure business outcomes, not activities: "MBRX is ultimately the most customer-centric KPI," stated Canlas, emphasizing the importance of measuring actual patient impact.

5) Consider the complete patient journey: "Part of the journey is also when you stay on something. And your physician helps you throughout the entire journey," Wall emphasized, highlighting the need to support patients beyond initial prescription.

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Discover more on this topic at Pharma 2026 (22-24 April, Barcelona) - the global collaborative network for leading pharma innovators. Visit the website here.