Chris Paquette is CEO at DeepIntent, the leading healthcare marketing technology company created to influence positive health outcomes.
Using clinical data, genomics and machine learning, researchers have found key correlations between select biomarkers and clinical diagnoses. For example, the detection of BRCA1 and BRCA2 gene mutations is understood to be highly connected with metastatic breast cancer. Discoveries like this have the potential to save millions of lives and raise the question of how we can replicate lifesaving innovation more broadly across the entire healthcare system.
What if we could apply that same kind of analysis to discover new knowledge that supports patient outcomes by improving their engagement with physicians at the point of care? What if we could use broad, population-level insights to better predict and deliver relevant information patients need during their journey of care? What if we could do it in a way that respects patient privacy? Wouldn’t that be worth pursuing?
That’s the opportunity in front of the industry, sitting at the convergence of digital health data and digital marketing. As healthcare has become more digital, the availability of data has increased and will continue to, exponentially. We’re barely scratching the surface of the true value of that data when it comes to advertising, for now.
The State Of Digital Marketing In Healthcare
Each year, pharmaceutical drug companies spend more than $4.5 billion on linear TV ads, which lack the precision offered by digital and programmatic channels. This number represents approximately 75% of their ad budgets. While research shows patients want to be informed about their treatment options—with nearly 75% saying they agree more lives could be saved if patients were better informed about their pharmaceutical options—patients don’t find most ads relevant to them (registration required). In short, there’s a major opportunity to do pharma advertising better.
Unlocking the value of health data in advertising requires that marketers take full advantage of the latest generation of digital marketing technology. Data isn’t actionable on its own. As in the example above, it takes the application of the latest techniques and technology to realize its potential and make those insights actionable within campaigns.
Let’s look at one of the most common approaches that pharma marketers today use to reach physicians. Often, marketers rely on premade, third-party target lists based on relevant national provider identifier numbers. But that data is often a year or more old, incomplete and lacks the granularity needed to reach clinically relevant campaign-specific audiences.
Modern solutions enable marketers to move beyond the target list approach and leverage more actionable data that is HIPAA-compliant and anonymized. That data can serve as the raw input for a new generation of healthcare marketing campaigns that is much more adaptive to in-market changes. This will drive awareness and engagement more efficiently, driven by the idea that personalization creates relevance, ultimately improving patient outcomes.
If digital health data is the oil, programmatic advertising is the engine.
The combination of real-time data and machine learning presents an opportunity for marketers to go beyond their current, static target lists and improve personalization.
If digital health data is the oil for personalized marketing, programmatic advertising is the engine. Fresh, timely data keeps the programmatic engine spinning to supercharge results compared to traditional campaigns, as algorithms take constant data inputs to auto-optimize variables, including creativity, audience, frequency, inventory, geography and more that impact whether an ad is timely or relevant.
Functionally, data from nearly any health data source can be tokenized to protect patient privacy and fed into a healthcare marketing platform to be modeled or processed for same-day activation. Depending on the type of data, campaigns can update in real time or daily.
But the speed at which data refreshes is important, since delayed inputs inherently lead to missed opportunities and a lack of timely campaign optimization. Put another way, what may have been an actionable insight can quickly fade into a nice-to-know reflection in hindsight in the age of machine learning.
Recent advancements in advertising technology give healthcare marketers unprecedented ability to create highly targeted campaigns for both providers and patients, no matter where they are in their journey. Using machine learning, healthcare marketers can reasonably ensure that they are reaching relevant audiences with the right message at the right time—whether these audiences are new-to-brand or more established with a higher familiarity of different treatment options—all without knowing any of the underlying identifiers that are constantly steering their campaigns in the right direction.
The potential of this technology is absolutely massive, particularly in improving the conversations that patients have with their healthcare providers. As a result of these advancements, for the first time in the history of healthcare advertising, marketers can now program campaigns to reach patients and providers in the critical weeks leading up to patient visits. It’s time to start marketing to the future, that is, not the past that was.
Imagine how campaigns like that can accelerate the treatment of rare diseases, where early detection and proactivity are critical. Small patient populations, limited awareness of the condition, and unique patient journeys too often delay vital treatment, but programmatic advertising powered with machine learning holds the potential to dramatically accelerate the process of getting rare disease patients the care they need.
This is but one example of how recent innovations in the use of health data can power more relevant, informed conversations that lead to better outcomes. Applied more broadly, and using larger data sets, in front of us stands a new frontier for pharmaceutical advertising.
That future holds the promise of previously unseen innovations as advancements in AI and machine learning unlock new ways of bringing treatments to consumers. But data isn’t actionable on its own. Only by embracing new technologies and challenging the status quo can marketers realize the opportunity in front of them at the convergence of digital health data and digital marketing.
In my next article, I look forward to discussing the ongoing, increased impact of programmatic advertising and will provide some basic strategies for how to get started utilizing it to achieve success and meaningful results.