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Predict HCPs Engagement

Improve omnichannel engagement with data-driven, personalized approaches.

Problem

The pharmaceutical industry across different regions is facing a significant challenge in effectively engaging healthcare professionals (HCPs) through their commercial strategies. Traditional approaches to HCP engagement have been disrupted by factors such as the widespread impact of the COVID-19 pandemic and the rapid expansion of digital communication channels. These developments have underscored the necessity for pharmaceutical companies to urgently adapt and implement more versatile, personalized engagement models. The shift is driven by the evolving expectations of HCPs, who increasingly prefer diverse channels for receiving information, including email, social media, and virtual events (1). This transformation is not merely a response to current disruptions but also a strategic imperative, as companies utilizing omnichannel marketing strategies are shown to be 39% more likely to increase revenue compared to those relying solely on traditional methods (2). Furthermore, HCPs who are satisfied with omnichannel experiences are significantly more inclined to recommend pharmaceutical companies to their peers, highlighting the pivotal role of effective engagement in fostering strong professional relationships and industry influence (3).

Why it matters

  • The pharmaceutical industry is challenged to engage healthcare professionals (HCPs) effectively amidst disruptions from COVID-19 and digital proliferation.
  • HCPs increasingly prefer diverse communication channels, including email, social media, and virtual events.
  • Companies using omnichannel strategies are 39% more likely to increase revenue, and satisfied HCPs are 70% more likely to recommend a company to their peers.

Solution

"HCPengage AI" is a predictive model designed to identify healthcare professionals most receptive to marketing campaigns, improving engagement by leveraging synthetic data to assess the likelihood of a positive response based on professional characteristics and campaign interactions passed.

User person: Digital Marketing Manager, Sales Director, Omnichannel Manager, Pharmaceutical Product Development Manager, Corporate Communications Manager, Medical Marketing Strategies Specialist.

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Datasources

The model uses variables related to contact frequency, specialty, and preferred communication channels of healthcare professionals, derived from industry research on marketing to healthcare professionals, such as findings from McKinsey & Company (1= and Indegene (2). Furthermore, insights into pharmaceutical sales marketing strategies from P360 (3) and Mrinmoy Roy (4) teach the model algorithm to personalize outreach and improve healthcare professional engagement.

Citations

  1. McKinsey & Company. (n.d.). Demystifying the omnichannel commercial model for pharma companies in Asia. McKinsey & Company.
  2. Indegene. (n.d.). Digitally Savvy HCP. Indegene.
  3. P360. (n.d.). 4 Ways that Machine Learning is Transforming Pharma Sales. P360 BirdzAI. https://www.p360.com/birdzai/4-ways-that-machine-learning-is-transforming-pharma-sales-p360/
  4. Roy, Mrinmoy. (2022). Artificial Intelligence in Pharmaceutical Sales & Marketing -A Conceptual Overview.

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