use cases

Revolutionizing Pharma Engagement for HCPs

Improve omnichannel engagement with data-driven, personalized approaches


The pharmaceutical industry in various regions is grappling with the challenge of effectively engaging healthcare professionals (HCPs) through their commercial strategies. The traditional methods of engaging HCPs have been disrupted by factors such as the COVID-19 pandemic and the rapid proliferation of digital channels. This has created an urgent need for pharmaceutical companies to adopt more versatile and personalized engagement models that cater to the evolving dynamics of HCP interactions (2).

The challenge of transforming HCP engagement is significant and far-reaching. Conventional sales approaches relying on instinct are no longer adequate, given the complexity of today's digital landscape and the multitude of engagement channels available. The ongoing pandemic has intensified this problem, as many physical visits to HCPs have been restricted. This situation has led to a growing gap between the existing engagement models and the evolving expectations of HCPs, creating a pressing need for a comprehensive solution (2).

Size of the Problem

  • 83% of healthcare professionals prefer to receive information from multiple channels, including email, social media, and in-person events. (1)
  • Companies using omnichannel marketing strategies are 39% more likely to increase revenue than those that do not use them. (2)
  • HCPs satisfied with the omnichannel experience are 70% more likely to recommend a company to their peers. (3)

Why it matters

Adopting an analytics-enabled omnichannel commercial model is crucial for the pharmaceutical industry to address the challenges of HCP engagement. Companies that successfully embrace this transformation can unlock substantial value. These benefits include increased revenue, enhanced marketing efficiency, higher HCP satisfaction, improved engagement, and more meaningful interactions (3). The impact of the COVID-19 pandemic underscores the urgency, which has accelerated the shift towards digital interactions and necessitates a reimagining of stakeholder engagement models. Embracing analytics-driven strategies is a means to adapt to the current environment and a pathway to long-term success and competitiveness (4).


Integrating advanced analytics and AI offer a promising solution to the pharmaceutical industry's engagement challenges. By harnessing the power of AI, companies can transition from traditional engagement methods to data-driven, personalized approaches. AI-driven insights comprehensively understand HCPs by analyzing historical interactions, prescribing patterns, and market context. Predictive analytics enable companies to anticipate optimal touchpoints and messages for HCPs, optimizing resource allocation and enhancing overall engagement effectiveness (2) in a Next-Best Action model.

Moreover, AI-powered analytics facilitate agile content and delivery optimization through real-time A/B testing. This iterative approach ensures engagement strategies remain relevant and impactful in an ever-changing environment. AI-driven optimization goes a step further, recommending the most effective sequence of interactions for individual HCPs, strategically aligning engagement efforts to maximize impact and influence prescribing behavior. To implement these solutions, companies need to establish cross-functional teams, embrace change management efforts, and focus on building data-driven capabilities (5).

Adopting an analytics-enabled omnichannel commercial model powered by AI is imperative for pharmaceutical companies to overcome the challenges of engaging HCPs effectively. This solution addresses the immediate disruptions caused by the pandemic and positions the industry for sustainable success in a digitally-driven healthcare landscape.


  • Sales and Prescription Data: Information about pharmaceutical product sales at the level of individual healthcare professionals (HCPs) or small groups of HCPs, along with prescription data. This data helps estimate the impact of interactions on sales and models the effects of engagement strategy changes.
  • HCP Interaction Data: Records of past interactions between sales representatives and HCPs, including details about the channels used (in-person meetings, phone calls, emails, etc.), frequency, and content of interactions.
  • Content and Messaging Data: Information about messages and content delivered to HCPs through different channels, along with details of response and effectiveness of these contents in generating interest and prescriptions.
  • HCP Characteristics Data: Demographic data, medical specialties, locations, practice size, and type, and any other relevant information about HCPs to enable precise segmentation and personalization.
  • Market and Competition Data: Information about the competitive landscape, market events, epidemiological trends, market access, and other factors that may impact prescription behavior.


  1. FiercePharma. (n.d.). HCPs want less clutter and more relevance from pharma marketers, survey shows. FiercePharma.
  2. McKinsey & Company. (n.d.). Demystifying the omnichannel commercial model for pharma companies in Asia. McKinsey & Company.
  3. Indegene. (n.d.). Digitally Savvy HCP. Indegene.
  4. Treasure Data. (2023, March 3). Next-Best-Action Marketing. Treasure Data Blog.
  5. P360. (n.d.). 4 Ways that Machine Learning is Transforming Pharma Sales. P360 BirdzAI.

Book a Free Consultation

Trusted by the world's top healthcare institutions