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Episode 6

Next Best Action in Pharma Sales

Powering personalization with predictive analytics
Personalization in pharma sales is evolving rapidly, and Next Best Action strategies are emerging as a key driver of commercial success. In this episode of C&F Talks, we explore how companies can harness data, and AI-driven insights, and predictive analytics in pharma, to anticipate customer needs, optimize engagement, and improve sales outcomes.

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Key insights into Next Best Action in pharma

What Next Best Action means in pharma sales
How AI-driven insights support Next Best Action success
The role of predictive analytics in pharma engagement
Steps to scale Next Best Action programs effectively

Enhancing pharma outcomes with AI-driven insights

Pharma companies face growing pressure to personalize interactions with healthcare professionals and patients. Next Best Action strategies powered by AI-driven insights help commercial teams deliver relevant, timely messages across channels. By combining predictive analytics in pharma with a strong data foundation, organizations can better understand customer behavior and drive measurable improvements in engagement.

Scaling Next Best Action in pharma

While many companies pilot Next Best Action initiatives, scaling them successfully requires clear governance and cross-functional alignment. In this episode, we discuss best practices for moving from pilots to enterprise-wide programs. You’ll learn how to operationalize Next Best Action in pharma, measure impact, and create a culture of continuous learning powered by AI-driven insights.

Learn how to apply Next Best Action with our practical pharma sales guide.

Meet the expert

Michał Osuch

Head of Enterprise Data Consulting & Insights, C&F

Michał is an experienced IT and Project Manager with broad knowledge of the pharmaceutical and animal health industries. With over 20 years of experience gained in various IT roles within domestic and regional pharmaceutical organizations, he has contributed to numerous commercial data management projects, data wrangling initiatives, and deep root cause analysis. Michał has a proven track record in defining business requirements for systems and integration implementations, as well as overseeing detailed testing and validation. He currently leads the Enterprise Data Consulting & Insights business unit.

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