Pharma Analytics: A Dynamic Approach to Segmentation & Targeting

Aug 23, 2023

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AUTHOR(s)

Astajyoti Behera

Corporate Vice President, Analytics, WNS Triange

Yashajit Saha

Deputy Manager, Analytics, WNS Triange

Key Points

In the face of unprecedented challenges within the pharmaceutical industry's intricate economic landscape, the focus on growth while optimizing costs has assumed paramount importance. The current pharmaceutical market segmentation and targeting model, reliant on past prescription behavior, falls short of capturing the dynamism of today's rapidly evolving market.

Challenges with Traditional Pharma Targeting Models

This whitepaper proposes a groundbreaking shift in the conventional segmentation and targeting approach in pharma, harnessing the transformative power of advanced pharma analytics to address the limitations of historical prescription data and static methodologies. As the application of AI in pharma industry operatioss matures, it introduces a dynamic segmentation and targeting approach that capitalizes on the influx of data and leverages the capabilities of Artificial Intelligence (AI) and Machine Learning (ML).

Harnessing AI and Advanced Pharma Analytics for Dynamic Segmentation

The solution advocated is an AI / ML-driven system that seamlessly integrates predictive models and data from various channels, such as personal interactions and Non-personal Promotions (NPP), to create an agile targeting strategy for each Healthcare Provider (HCP).

This dynamic approach envisions an agile targeting strategy that adapts to individual HCPs' behaviors, leveraging unsupervised clustering techniques to classify HCPs and employing supervised ML algorithms to predict shifts in their behavior. Driven by AI in pharma industry applications, the solution culminates in a recommendation engine that guides representatives to interact with HCPs through the most effective channels and optimal timings for maximum market share growth.

The Future of Pharma Industry & Personalized Targeting

The whitepaper showcases the transformative potential of such a dynamic segmentation and targeting approach in pharma. By capturing the essence of real-time data and harnessing the analytical power of AI and ML, modern pharma analytics can revolutionize how the sector identifies, segments and targets HCPs. This approach signifies a paradigm shift toward personalized and agile engagement, shaping the future of pharma industry practices into an era where data-driven decision-making is a necessity and a strategic advantage.

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FAQs

1. Why are traditional HCP segmentation models no longer effective for pharmaceutical commercial teams?

Traditional segmentation models rely heavily on historical prescription behavior and infrequent updates, making them less effective in today's rapidly changing healthcare environment. Healthcare Professionals (HCPs) continually evolve their prescribing patterns, engagement preferences and treatment decisions. WNS helps pharmaceutical companies implement AI-powered dynamic segmentation models that continuously adapt to changing market conditions, enabling more precise targeting and stronger commercial outcomes.

2. How can AI-powered dynamic segmentation improve pharmaceutical commercial performance?

AI and machine learning enable pharmaceutical companies to analyze real-time engagement signals, prescription trends, digital interactions and market dynamics to create continuously evolving HCP segments. This allows commercial teams to prioritize the right physicians, deliver personalized engagement and optimize sales force productivity. WNS combines advanced analytics, predictive modeling and life sciences expertise to help organizations improve commercial effectiveness through intelligent segmentation and targeting.

3. How does dynamic targeting support omnichannel HCP engagement?

Modern HCP engagement requires selecting the right channel, message and timing for every interaction. Dynamic targeting uses AI to recommend the next best action based on HCP behavior, preferred communication channels and engagement history. WNS helps pharmaceutical organizations build omnichannel commercial strategies that improve HCP engagement, campaign effectiveness and customer experience through data-driven decision intelligence.

4. What challenges prevent pharmaceutical companies from adopting dynamic segmentation successfully?

Organizations often face fragmented commercial data, disconnected engagement platforms, limited AI adoption and legacy segmentation methodologies. Without integrated analytics, commercial teams struggle to respond to rapidly changing market conditions. WNS addresses these challenges through unified data ecosystems, AI-enabled segmentation frameworks, predictive analytics and scalable commercial operating models that support continuous optimization.

5. Why should pharmaceutical companies partner with WNS for AI-driven segmentation and commercial analytics?

WNS combines deep life sciences expertise with advanced analytics, AI, machine learning and commercial consulting capabilities to modernize pharmaceutical targeting strategies. From HCP micro-segmentation and predictive targeting to omnichannel engagement optimization, next-best-action recommendations and commercial performance analytics, WNS helps pharmaceutical companies create agile, customer-centric commercial ecosystems that improve field force effectiveness and accelerate business growth.