Patient-Centric Pharma Marketing Powered by AI
In today's dynamic healthcare landscape, healthcare providers (HCPs) are constantly bombarded with information, making it challenging for life science companies to effectively engage HCPs and deliver timely, relevant information that can improve patient care. As the power of artificial intelligence (AI) for data analysis improves, next-best action (NBA) marketing has emerged as a powerful approach to address this challenge and enhance HCP engagement. However, one crucial stakeholder is often overlooked: the patient.
The Origins of Next-Best Action: From the Army to McDonalds
It might come as a surprise, but the concept of NBA isn’t new; its roots can be traced back to a mid-20th-century military strategy known as the "OODA Loop" – observe, orient, decide, act. This framework, initially adopted to enhance combat effectiveness, emphasized making real-time decisions based on current conditions rather than relying on pre-planned campaigns. The result? Better outcomes guided by dynamic, adaptable strategies.
As businesses began to recognize the importance of understanding and catering to customer needs directly, the concept of customer centricity became a guiding principle.
For example, McDonalds implemented a simple yet effective NBA strategy by asking customers the famous question "Do you want fries with that?" This simple question considered another action the customer could take, resulting in an estimated 15-40% increase in annual revenue.
But there’s a problem with this approach. Customers are unique and might want other options – how can pharma marketers create highly personalized, actionable content that serves these individual needs?
By identifying pivotal disease milestones and knowing the windows when patients will be visiting their physicians, marketers can deliver timely, targeted information to HCPs when they are treating a brand-eligible patient.
Next-Best Action in Pharma: The Importance of Customer Centricity
In healthcare, customer centricity means putting the patient first. While this approach has been embraced in areas like clinical care development and delivery, disease awareness and prevention, and consumer education, in pharma's three main segments – physicians, payors, and patients – patients have yet to be prioritized effectively in HCP marketing. Brands have instead turned to proxies such as static patient journey modeling, past physician prescribing behavior, and other historic data in hopes of predicting future patient needs.
But the advent of AI and machine learning (ML) has opened up exciting possibilities for patient-first engagement, making the approach all the more relevant in today's pharma advertising landscape. As new data sources develop, pharma marketers can harness and analyze patient data from various sources, including electronic health records (EHRs), claims data, and more – identifying the patient journey in a privacy-safe, real-time way that wasn’t possible before.
Backed by this real-time data analysis, life science brands can offer increased support and value to patients in the form of access information, clinical trial updates, affordability resources, and more. By identifying pivotal disease milestones and knowing the windows when patients will be visiting their physicians, marketers can deliver timely, targeted information to HCPs when they are treating a brand-eligible patient.
Navigating the NBA Landscape: Bridging Stakeholder Gaps
As generic, mass advertising continues to lose efficacy in favor of data-driven, precision approaches, it’s no surprise that life science companies, healthcare advertising agencies, and technology providers all play a crucial role in the evolution of NBA marketing strategies. However, each group faces unique challenges in implementing this approach effectively.
Life Science Companies:
- Over-focusing on physician data: In their quest to align marketing efforts to HCP behaviors, life science brands are overly focused on physician data, neglecting the importance of real-time patient data for effective HCP-focused marketing.
- Siloed data analysis: Brands are often taking a siloed approach to data analysis, failing to integrate patient and physician data to identify pivotal patient milestones that drive next-best action.
Healthcare Advertising Agencies:
- Calendar-based media buys: Healthcare advertising agencies play a crucial role in implementing NBA strategies by analyzing HCP behaviors and advising on “business rule” development, but too often rely on calendar-based media buys, missing opportunities to target patients at critical disease milestones and leading to unproductive media impressions.
- Lack of focus on dynamic patient journeys: Technology providers are developing AI-powered platforms, but need to prioritize the development of solutions that capture and analyze the dynamic flow of patients along their care journeys.
- Need for privacy-safe engagement models: Technology providers need to develop more personalized engagement models that are tailored to individual physician needs and preferences, while keeping patient privacy concerns a top priority.
The ultimate goal for brands, agencies and tech providers is to build a responsible, accessible healthcare engagement ecosystem that increases transparency and access to the best information and treatments for each individual patient. Reaching this goal requires a shift from siloed data analysis and calendar-based targeting to a dynamic, patient-centric approach that reflects the diversity of the patient journey and serves HCPs information that aligns to each patient’s evolving needs.
Dynamic Patient-Centric Pharma Marketing Strategies
Next-best action is more than just a marketing buzzword; it's an evolution of customer-centricity, driven by today's AI advancements. By embracing real-time patient data, leveraging AI-powered insights, and collaborating across stakeholders, brands can create a patient-centric NBA ecosystem that drives meaningful HCP engagement, improves patient outcomes, and transforms the healthcare landscape.
Want to learn more about how AI is making patient centricity a reality? Read the Full Whitepaper