One of the biggest challenges that launch brands in unique therapeutic areas face is identifying the right target audience for both unbranded and branded messaging. This is a critical first step for brand/therapeutic marketers, multi-channel engagement managers, AORs and field operations. Understanding your initial audience can impact speed to market, awareness and trial, business impact, key influencers and opinion leaders (market buzz) and of course, ROI.
Research shows that the migration of healthcare professionals (HCPs) from initial touch to progressively increasing levels of engagement leads to defined levels of Rx activity[1]. Migration patterns are quantified based on writing activity for each period, and the longitudinal analysis provides a basis for targeting, message optimization and positioning over the period of launch.
Early-stage engagement is a critical first step in defining and predicting the migration of HCPs along the prescribing continuum. Identifying these audiences, and analyzing their message engagement in the early stages of a campaign accommodates “in-program” adjustments. This approach expedites establishing a segmented communication standard that optimizes spend, reach, and business impact, while incorporating target engagement and value to the brand.
[1] Groves, Kent and Bret Baker. Optimizing Frequency, Sequencing and Messaging for Emails in a Portfolio of Products and Non-Personal Tactics, PMSA Winter Symposium, January, 2018.
Based on analysis and the in-market activity associated with a recent biologic launch, this approach provides early insight into binary segmentation of HCPs into “bio-naïves” and innovators relative to the audience of engagers vs non-engagers.
Continued messaging further differentiates non, single and multiple engagers, relative to their longitudinal Rx activity. It also identifies the content and sequence that produces trial, leading to migration of HCPs from the primary levels of engagement to higher quintiles of Rx activity.
In an environment where all eyes are on machine learning and AI-driven algorithms to predict next-best-action, this process reinforces the role of strategy, marketing, and analytics working together to test, design, and leverage real-time insight. Furthermore, it validates and reinforces target selection, communication messaging, sequence, and activity-based segmentation.
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