Precision Pharma Marketing: How AI and Process Mining Can Drive Better Customer Segmentation

Pharmaceutical marketing is at an inflection point. The increasing complexity of patient journeys and healthcare provider (HCP) engagement means traditional segmentation methods are no longer sufficient. Pharma companies are now leveraging artificial intelligence (AI) and process mining to drive more precise, data-driven customer segmentation. These advanced technologies enable pharmaceutical firms to enhance targeting, improve engagement, and maximize the return on investment (ROI) for marketing efforts.

This article explores how AI and process mining are reshaping customer segmentation, offering real-world insights and vendor analysis to help pharmaceutical executives and their agency partners adopt these powerful tools.

The Evolving Landscape of Pharma Customer Segmentation

Traditionally, pharmaceutical companies have relied on demographic data—such as age, geographic location, and specialty—to segment HCPs and patients. However, the rapidly changing healthcare environment demands more nuanced approaches. Factors such as evolving prescribing behaviors, regulatory requirements, and patient-specific outcomes now play a critical role in shaping segmentation strategies.

This complexity has exposed significant gaps in the ability of pharma marketers to predict and respond to market dynamics effectively. As digital transformation sweeps through the industry, tools such as AI and process mining offer an opportunity to dramatically improve segmentation accuracy by turning vast datasets into actionable insights.

How AI Refines Customer Segmentation in Pharma

Data-Driven Insights

At its core, AI leverages vast data sets to uncover patterns and insights that are invisible through manual analysis. In the pharmaceutical sector, AI tools can process large volumes of data—ranging from HCP prescribing behaviors to patient adherence trends—to build precise customer segments.

For example, IQVIA, a leading healthcare analytics provider, offers AI-powered tools for dynamic segmentation. Their solutions provide real-time profiling of HCPs, allowing pharma marketers to adjust their targeting based on current prescribing behaviors and digital engagement. This ensures that marketers are reaching the right providers with the right message at the optimal time(IQVIA Health).

Predictive Analytics and Real-Time Segmentation

One of the most compelling aspects of AI is its predictive power. AI-powered analytics allow pharmaceutical companies to predict how different HCPs and patients are likely to respond to certain drugs or therapies. This helps in refining segmentation strategies by prioritizing those most likely to engage, thus improving the efficiency of marketing spend.

Predictive analytics also enable real-time segmentation, ensuring that pharma companies can respond swiftly to shifts in market behavior. For example, if a new drug is launched, AI can quickly identify which HCPs are early adopters and adjust marketing strategies accordingly.

Process Mining: Enhancing Segmentation by Understanding Journeys

While AI provides the data insights necessary for segmentation, process mining adds another layer of understanding by analyzing customer journeys and workflows. It helps pharma marketers visualize how HCPs and patients interact with the healthcare ecosystem and the various touchpoints that influence their behavior.

Mapping the End-to-End Journey

Process mining enables pharmaceutical companies to map the full end-to-end journey of an HCP or patient, from initial engagement through prescription to ongoing care. This approach provides deeper insights into where engagement occurs, where potential drop-offs happen, and which interactions have the most significant impact.

For example, Celonis, a leader in process mining technology, helps companies uncover inefficiencies in their customer engagement workflows. By understanding how HCPs move through the funnel—from initial awareness to adoption—pharma companies can optimize each touchpoint, resulting in more personalized marketing(Business Wire).

Key Touchpoints and Bottlenecks

Process mining also helps identify the key touchpoints where interventions are most effective. In pharmaceutical marketing, these touchpoints could include digital engagements such as webinars, HCP visits, or patient support programs. Process mining can pinpoint where bottlenecks occur, such as delayed engagement with HCPs post-launch, and recommend adjustments to the strategy to maintain momentum.

The Combined Power of AI and Process Mining for Precision Segmentation

The true potential of AI and process mining lies in their combined application. While AI helps segment customers based on behaviors and predictive insights, process mining provides the context needed to understand how and when to act on those segments.

Integrated Insights for Better Targeting

By integrating AI-driven segmentation with process mining, pharma marketers can build more dynamic and flexible targeting strategies. For example, AI might identify HCPs who are high-value targets based on prescribing patterns, while process mining will show which touchpoints are most effective in converting those HCPs. This combined insight allows for more tailored and impactful marketing interventions.

Case Study: Improving Engagement for New Product Launches

A pharmaceutical company launching a new drug could use AI to identify the HCPs most likely to prescribe it based on historical data and engagement behavior. Simultaneously, process mining could map out the optimal sequence of touchpoints—such as digital campaigns, webinars, and one-on-one outreach—required to convert these HCPs. This approach ensures that every marketing dollar is spent on high-value targets, improving the overall ROI of the campaign.

Key Vendors in the Space

Several vendors are leading the charge in providing AI and process mining solutions specifically tailored to pharmaceutical marketing:

• IQVIA: A pioneer in healthcare analytics, IQVIA provides AI-powered dynamic segmentation tools that allow pharma companies to refine their customer segmentation in real-time. Their solutions are widely adopted for precision targeting and personalized marketing strategies(
• Celonis: Known for its expertise in process mining, Celonis helps pharmaceutical firms visualize and optimize their customer engagement workflows. By providing a deeper understanding of customer journeys, Celonis enables pharma marketers to fine-tune their segmentation strategies for better results(
• IBM: IBM offers a range of AI and process mining solutions that are designed to help pharmaceutical companies optimize their operations, including customer segmentation and marketing strategies(

Practical Benefits for Pharma Marketers

The combined use of AI and process mining offers several tangible benefits for pharmaceutical companies:

1. Enhanced Personalization: More precise segmentation allows for highly personalized marketing campaigns, improving engagement with both HCPs and patients.
2. Increased ROI: By focusing on high-value segments and optimizing engagement touchpoints, pharma companies can significantly improve the return on their marketing investments.
3. Better Customer Relationships: AI and process mining enable marketers to build stronger relationships with HCPs and patients by delivering relevant content at the right time.

Conclusion: A Strategic Imperative for Pharma Executives

As the pharmaceutical industry continues to evolve, AI and process mining are becoming essential tools for marketers seeking to improve customer segmentation. By leveraging these technologies, pharma companies can build more dynamic, data-driven strategies that enhance engagement, improve personalization, and maximize ROI.

Pharmaceutical executives and their marketing teams should consider adopting these advanced tools not just as enhancements, but as strategic imperatives for future growth. Working with leading vendors like IQVIA and Celonis will ensure access to cutting-edge capabilities that keep their marketing efforts competitive in an increasingly complex landscape.