As pharmaceutical audiences become more fragmented and regulations tighten, marketers face a familiar challenge: how do you create personalization without overstepping. Every campaign now demands a balance between audience precision and empathy.
That tension was the focus of Precision in Practice: Personalizing Omnichannel Targeting for HCPs and Patients, a panel at the Fierce Pharma Marketing Week 2025 featuring:
Together, they explored how pharma marketers can apply machine learning and privacy-first data design for better targeting, leverage behavioral insight to guide tone and timing, and use real-world feedback to turn engagement into authentic connections.
Today’s advertisers have a plethora of channels to choose from to connect with audiences. And while it may be tempting to activate every channel to maximize exposure, relevance—not just reach—is what truly moves the needle. Striking the right balance between consistency in messaging with thoughtful reach—across audiences, channels, and perpetually-evolving regulations—is what unlocks opportunity for today’s advertisers.
As new trends and channels emerge, advertisers should consider that, as Driscoll noted, “Just because you can doesn’t mean you should,” underscoring the importance of choosing fewer, more effective touchpoints rather than stretching across every possible channel. Lawless echoed this sentiment sharing that success is no longer about volume, but continuity and how well each interaction reflects the same story, tone, and cadence.
Even with all the progress around omnichannel, many marketers still struggle to deliver personalization. In one survey, 62% of pharma executives said the lack of personalized content remains a major hurdle to successful omnichannel engagement. This is a reminder that precision isn’t about having more data or technology, it’s about creating experiences that actually resonate.
Today’s hyperconnectivity—across devices, channels, and digital transactions—has created a wealth of data for advertisers and marketers to tap into. And while new technologies like AI promise to enable organizations to easily derive clarity and insights from troves of data, many don’t know where to begin—or if it’s feasible to responsibly use AI and data together.
“There’s a big misconception in the industry that the advancements of AI are actually going to make it more challenging for us to stay within the guidelines of these laws,” said Deutsch. He goes on to explain that he feels it’s the opposite, rather that AI allows marketers to analyze metadata and demographic patterns without ever touching protected health information (PHI). “What AI enables us to do is remove PHI from the claims information, but look at their demographic data and model off of the demographic data in an accurate way so we can still deliver an effective message to a patient that needs to see the message without infringing on their privacy."
Lawless agreed and stated: “We have more data than we know what to do with.” He further reflected that scale can blur strategy. Together, their points underscore how AI is helping teams make smarter choices evidenced by the tremendous backing of AI in healthcare valued at $29 billion in 2024 and is expected to exceed $500 billion by 2032, illustrating how quickly this technology is becoming standard in pharma.
So how do you put precision into practice? The panelists stressed the value of iteration, where you treat performance data as a feedback loop rather than a final result. “If I see all greens [KPI’s], that’s a red flag,” said Lawless, arguing that it’s the “misses” that provide signals for marketers to adjust, optimize and refine their approach. Driscoll agreed, sharing that, "being in the red isn’t bad. It’s a chance to talk about how we make the work better."
Deutsch shared how iteration could play out in real time. He called out that most pharma brands brief their agencies once a year—leaving them vulnerable to constantly-evolving market dynamics. “Plan[s] ha[ve] to be adjustable,” he said. He also covered his unique viewpoint from Cadent: “by being able to leverage algorithms to look at real-time data is as real-time as we can get. [... We can] look at real-world outcomes more now than what used to be clicks and watching views and time spent on my page. [...] How do we optimize that? How do we change the delivery in real time so that a 12-month strategy isn't in the same place it was before Thanksgiving when you booked the buy?”
The overall message was clear: Marketers should not wait until the end of a campaign to learn. Rather, they need to build mechanisms in the form of a feedback loop to learn and adjust while campaigns are running.
Across the discussion, one point kept surfacing: precision is only powerful when it’s practical. It’s not about more data or more channels; it’s about using what you already have more intelligently. When marketers ground their strategies in behavioral understanding, uphold privacy, and build systems that adapt in real time, personalization becomes both scalable and responsible.
As AI, privacy regulation, and audience expectations evolve, the brands that succeed will be the ones that use precision to create better consumer experiences, not just focus on more sophisticated technology.
Watch the full panel, Precision in Practice, to hear how leaders from Cadent, Merck, Corcept Therapeutics, and Evolve MKD are bringing personalization to life across patient and HCP engagement.