From Targeting to Relevance: 4 Takeaways from Pharma Customer Engagement USA 2026

1. Start with the patient, not the target list

Traditional HCP targeting often starts with claims: identify historical activity, rank HCPs and build a target list.

But what if that means starting in the wrong place?

Claims can show what happened historically, but they do not necessarily provide a complete picture of what is happening clinically. A claim is a billing record. It tells us what was billed and by whom, but it does not tell us the full story of the patient’s care.

The HCP most visible in historical claims may not be the person influencing the patient’s next treatment decision.

Scott demonstrated how traditional targeting can overlook relevant HCPs. In one example from his presentation, 80% of prescriptions came from decile-zero doctors who had not previously been engaged.

The implication goes beyond improving the accuracy of a list.

The starting point itself needs to change.

Rather than beginning with Who prescribed?, commercial teams can start by asking: How does this patient get treated?

That means looking beyond the retrospective patient journey captured in claims and considering the wider patient experience: how the disease is diagnosed, which routes through care are available and which HCPs influence decisions at different points.

2. More signals don’t automatically mean more insight

Moving beyond claims does not mean simply adding more datasets. More data is not the same as better insight.

Claims, laboratory results, EMR data and diagnostic signals can each provide a different view of the patient experience. Together, they can provide more of the clinical picture than billing activity alone.

But a signal without context can only tell you so much. That is where clinical intent matters.

Scott Phillips described clinical intent as understanding the why behind a physician’s decision, rather than waiting until the decision has already happened before acting. Combined with richer clinical and diagnostic data, it can help build a more relevant view of the HCPs involved in the patient’s care. His framework covers diagnostic, referral, monitoring and treatment intent.

The same challenge applies to HCP segmentation: individual signals only become useful when they are interpreted in context.

In the session, ‘Decode HCP Signals: Smarter Segmentation for Relevant Engagement’, Akash Jain, Director, Data & Analytics Strategy, US Oncology at Merck, examined how observed HCP behaviors can be translated into actionable segments, distinguishing direct evidence from proxies and projections.

More signals do not automatically produce better insight. The better question is not:

How much data can we bring into our targeting? It is: Which signals help us understand what is happening with the patient and what may happen next?

3. Orchestration isn’t another technology project

AI, automation and omnichannel infrastructure featured heavily across Pharma Customer Engagement USA.

But technology is an enabler, not the starting point.

In the Keynote panel ‘The New Commercial Frontier: From Static Journeys to Dynamic Customer Orchestration’, Darshan Joshi of Takeda and Elizabeth Beringer of Real Chemistry looked beyond rigid CRM journeys towards orchestration that can respond to context, timing and intent.

But orchestration requires more than infrastructure. Data, content and channels need to work together across the customer experience.

And the customer journey cannot be separated from the patient journey. In From Prescription to Patient Journey, Saket Malhotra of BioMarin, Holly Valdiviez of Acadia Pharmaceuticals and Lauren Cole of Valeris discussed how data, technology and cross-functional working can connect commercial activity more closely to the patient journey.

Sophisticated technology cannot compensate for a poorly defined problem, weak inputs or an organization that cannot act on the output.

Scott Phillips’ presentation reached a similar conclusion from a diagnostic data perspective. Getting to a more relevant view of the patient is not simply about more data. It requires the right data, with the right context, expertise and question.

AI can accelerate analysis, identify patterns and help teams operate at scale. The presentation makes the distinction particularly clear: AI can accelerate the data-heavy parts of the process, while judgement remains necessary around the patient experience and who, when and why to engage.

The question is not simply how quickly pharma can execute.

Are teams accelerating the right strategy in the first place?

4. Insight only matters if teams can act on it

Better data and richer segmentation have limited value if the intelligence arrives too late or cannot be translated into action.

That was the focus of the panel ‘From Insight to Action: Empower Teams with Real-time Data Intelligence’, where Nadia Tantsyura from Bristol Myers Squibb and Philip Poulidis of ODAIA discussed moving beyond static reporting towards real-time intelligence that can help commercial and medical teams act faster.

That shift from insight to action matters for HCP engagement.

It is not enough to identify a signal. Teams need the context to understand it and the ability to act while the information is still relevant.