In the first two installments of our series on the Four Pillars of Next-Best-Action Success, we explored Omnichannel Integration and Patient-First Data and Message Delivery. For part three, Robust Audience Intelligence, we’re taking a deeper dive into audience profiling, segmentation, and targeting, and the role the right data plays in reaching your key audience at the right moments.
Pharma marketers are drawing on massive amounts of fragmented data to inform and direct their brand communications, but not all datasets are created equal when it comes to next-best action. To achieve the precise audience targeting that drives next-best action, you need integrated data that can better uncover your relevant audience segments.
Is Your Data Limiting Audience Segmentation?
The data sources used by pharma marketers start with basic, commoditized data such as NPI numbers and claims history. But despite their widespread availability and use, these sources only allow for static list matches or retrospective views. This method yields a snapshot in time and vastly limits the data’s value in audience segmentation or their applicability to dynamic next-best-action programs. And that’s before factoring in the 6-month average lag for most commercial claims sources.
On the physician side, claims and EHR data can be used to model both historic prescribing activity and patient flow, creating preliminary audience segmentations around past volumes. This enables reactive, “trigger” campaigns that can be used to increase the message's relevance. While layering in additional this data starts to address the problem, it still falls short of true next-best action programs.
On the patient side, using social determinants of health (SDOH) and media consumption data can create basic consumer audience profiles and segmentations, as well as insights into channel preferences. Especially with the rise of streaming, CTV, and other newer channels gaining prominence, this data can lay the foundation for reaching audiences in better ways. However, without integration alongside clinical and medical data, it offers an incomplete audience picture.
Advanced-Data, Advancing Next-Best Action
The datasets noted above have two key similarities: 1) they offer only historic / moment-in-time snapshots, and 2) they aren’t sufficiently integrated for dynamic use. That means they result in hazy, inaccurate, incomplete audience profiles – leading to inefficient, reactive targeting.
But there are now data sources already integrated to favor NBA because they provide the granularity and comprehensiveness that enable the audience definition and segmentation to fine-tune outreach and engagement. That translates into more expedient execution and results. Here’s what you should be looking for:
- Future Patient Flow Data: Predictive view of upcoming patient activity treatment needs, linked to a specific window in time. Typically generated from AI algorithms applied to historic patient and physician behavior and medical data.
- Integrated Clinical / Consumer & Media Preference Data: Single-view dataset that combines patient clinical history, lifestyle, and social determinants of health for streamlined use.
- Real-Time Physician Engagement Behavior: Captures individual HCP responses to various media, and links to corresponding prescribing activity.
- Hyperlocal Geo-Targeting: HIPAA-compliant, tokenized data that links brand-eligible patients to specific physical locations critical to understanding the nature of your brand’s audience makeup.
Unlike the earlier examples, these datasets are both forward-looking and strategically integrated and enable segmentation based on near-term needs and behaviors. As a result, they can be used to dynamically target audiences with the precision needed for next-best-action marketing, then optimize message delivery and content based on observed activity.
Considering the Whole Patient and Physician
Next-best-action thrives on context and relevance. But too often, physicians are only seen through the lens of their prescribing activity, and patients are only seen through their diagnoses and treatments. But using holistic, integrated, and dynamic data allows pharma marketers to understand the full range of motivations and needs that drive behavior. In turn, this enables marketing to engage their audiences at the times and in the channels where brand information is relevant and actionable. So how does your current data sourcing strategy stack up?