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The integration of AI/ML (artificial intelligence/machine learning) and generative AI into omnichannel engagement strategies is reshaping how pharma companies interact with healthcare professionals (HCPs), patients and other stakeholders. This paradigm shift promises to enhance customer experiences, optimize resource allocation, and drive better health outcomes. In this blog, we look at the challenges and the potential of generative AI, while providing key insights to support the implementation of these innovations.
Pharma companies have long relied on siloed approaches to engage with their stakeholders. Each channel – including digital marketing and sales reps – operated independently, often leading to fragmented customer experiences and inefficient resource allocation. The transition to omnichannel engagement represents a strategic shift designed to provide a cohesive, personalized experience across all touchpoints, with the stakeholder at the center.
In essence, omnichannel engagement is an orchestration of personalized communications and interactions that resonate with the specific needs and preferences of stakeholders at every stage of their journey. |
By harnessing vast amounts of data from diverse sources such as claims, digital interactions, and more, AI algorithms can uncover patterns and insights that have been previously invisible to human analysts. This capability enables pharma companies to hyper-personalize engagement by predicting individual preferences and needs, allowing for tailored content and channel selection – whether it’s a prescriber needing education on a new treatment, for example, or a patient seeking help with medication adherence.
Multiple factors have accelerated the AI-driven evolution:
While AI has been supporting engagement strategy for some time, the advent of generative AI is opening new frontiers in customer engagement. Generative AI’s ability to have human-like conversations and even create virtual personas is transforming how companies can interact with their stakeholders.
Personalized content at scale |
Generative AI can rapidly produce thousands of variations of compliant content, tailored in terms of channel and depth of information |
24/7 support |
AI-powered chatbots and virtual assistants can provide round-the-clock support to HCPs and patients, answering queries about treatment pathways, drug information and more |
Enhanced field force training |
Virtual AI trainers can help sales representatives and medical science liaisons (MSLs) prepare for HCP interactions, providing guided messaging and real-time support – for example, during the launch of a specialized treatment in a new market |
Insight generation and summarization |
Generative AI can distill complex data into actionable insights, providing context-driven summaries to field teams and decision-makers |
While the potential of generative AI in omnichannel strategies is immense, pharma companies often encounter challenges that can be addressed with these best practices.
Case Study: Accelerating impactful engagements for top biopharma company A leading pharmaceutical customer sought to improve its omnichannel engagement with healthcare professionals (HCPs) across several markets and brands. Facing challenges such as data management issues, lack of customer-level insights, and adaptation difficulties, these issues hindered their ability to effectively engage with HCPs and optimize their marketing strategies. The customer partnered with IQVIA to implement an omnichannel solution including predictive alerts for select brands in the United States and a global Next Best Action (NBA) program. Predictive alerts enabled the customer to increase the reach, accuracy, and ROI on an existing suggestions program, resulting in a 20% increase in new patient initiation for one brand and a 36% increase for another, leading to $16.3M in increased sales. Leveraging Next Best Action, the customer program was meticulously crafted to enhance call pacing, pinpoint sales outliers, and recommend follow-up actions based on HCP interactions. This resulted in a 32% improvement in email send rates and a 4x increase in the accuracy of identifying high-value patients compared to the previous vendor’s program. |
As AI continues to evolve, several trends are likely to shape the future of omnichannel engagement in life sciences. The combination of AI and VR technologies may lead to more immersive and empathetic virtual interactions between patients and AI-powered healthcare providers. Different AI capabilities will increasingly work together seamlessly, creating more sophisticated and holistic engagement ecosystems. AI could enable more coordinated patient support programs, integrating various aspects of care from medication management to emotional support.
IQVIA’s experts offer this advice to leaders who are looking to implement AI-driven omnichannel strategies: make sure you’re building on a strong foundation, including a clear understanding of what you want to achieve, the data you bring to bear, and the team you have to do this critical work. If the talent isn’t available internally, it’s key to bring in external resources, or ideally, a seasoned global partner like IQVIA to navigate the complex AI landscape. In addition, our team recommends that organizations start small and scale, perhaps kicking things off with a pilot project or single brand before going regional or portfolio-wide.
The strategic use of AI technologies can help pharma companies differentiate to create more personalized, efficient, and effective engagement experiences. As the field continues to evolve, those who successfully navigate the challenges and embrace the potential of AI will be well-positioned to lead in the new era of pharmaceutical engagement.
Take advantage of the latest tools, techniques, and deep healthcare expertise to create scalable resources, precision insights, and actionable ideas.
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