The last decade saw an explosion of health data from sources including the digitization of health records, genomics, wearables, insurance claims, and more – which by some estimates now represents about 30% of the world’s data volume.
When combined with the power of machine learning, this data has the potential to reveal new insights into patients and their unique care journeys. Just imagine an AI model that improves the accuracy of cancer diagnosis, or can help isolate the genes responsible for rare genetic conditions. Innovations like these are already beginning to improve patient outcomes, and they raise the question of how else we can replicate the beneficial application of health data more generally across the entire healthcare system in a privacy-safe way.
Digital marketing in pharma seems like a prime candidate for this type of innovation. For example, what if we could glean broad, population-level insights to deliver relevant information exactly when patients need it? Or what if we could improve the experience for the 42% of consumers who say that the relevance of the pharma ads they see are poor or very poor?
Considering that our past research has found that pharmaceutical ads can empower patients to take a more active role in researching treatments – which is also the most common factor that patients state influences their medication adherence – that would be powerful indeed. So let’s examine the state of programmatic advertising in healthcare today, dig into some of the trends holding back the use of privacy-safe health data in advertising, and explore the opportunity for pharma marketers who successfully combine the two.
The State of Pharma Marketing in 2022
For a number of reasons, linear TV has long dominated the marketing mix for pharmaceutical brands and their agencies, but viewing habits change and audiences are fragmenting. In fact, some estimate that up to 70% of streaming audiences can’t be reached by linear-only campaigns – driving many advertisers to explore programmatic formats like digital video and connected TV (CTV). The pandemic further changed the way many pharma brands view advertising, with many appreciating the important difference it made in educating consumers and providers alike.
This major landscape shift toward programmatic media by pharma represents an opportunity to rethink both ad relevancy and measurement for the industry.
First, programmatic channels offer much more precise targeting than traditional TV – with as many as four or more variables like location and household income, compared with traditional demographics. Incidentally, this aligns with what patients say they want: relevancy. According to research conducted by DeepIntent and LG Ads Solutions, 65% of the more than 2,900 adults surveyed said that targeted ads improved their experience – and 57% said CTV ads were more relevant than linear or traditional TV ads. However, the deprecation of third-party cookies in 2023 will impact the precision of some programmatic channels, making it important to invest in new tools and strategies that allow for privacy-safe audience building, targeting, and measurement. CTV, for instance, doesn’t rely on third-party cookies for audience identification and measurement.
Second, linking digital ad campaign data and health data allows advertisers to go a step beyond traditional reporting metrics. Instead of simply tracking top-level data points like the number of impressions or clicks an ad received, marketers can go much deeper and analyze real-world patient outcomes, such as the number of new patients who actually follow through with filling the prescriptions written by their doctors after viewing an ad. This is also where there is the greatest opportunity to improve audience targeting, activation, and measurement over time – and is what will soon transform digital marketing in pharma.
Supercharging Pharma Marketing With Real-Time Data and Campaign Optimization
Health data isn’t actionable on its own, and a number of challenges have historically prevented its use for advertising.
For starters, data siloing and property systems have made it difficult to extract data and collect insights from connected data sets. The need for privacy and regulatory compliance further complicates its use for advertising purposes. Plus claims data, when available, is often lagged, and a lack of integration between marketing platforms and measurement tools has made campaign optimization a difficult, time-intensive process that is nearly impossible to automate at the same depth other industries enjoy today.
But why should healthcare marketers be relegated to using tools and solutions that are second-rate and downright inferior compared to what other marketers can do? The answer is they shouldn’t, and thankfully, the latest digital marketing technology leveraging real-time data, clean rooms, and machine learning makes it possible to optimize campaigns toward real-world outcomes using digital health data in a privacy-safe way.
Within just a few days, healthcare marketers using this technology can begin to determine which of their channels and demographics are most effective at achieving their campaign goals such as audience quality and new-to-brand scripts. That information can then be interpreted using machine learning to optimize variables including creative, audience, frequency, inventory geography, and more that impact whether an ad is both timely and relevant.
For an industry that has traditionally lagged behind others like retail or finance in its adoption of programmatic, the consequences of this shift are huge. Marketers will gain a much better understanding of campaign performance, and can optimize their campaigns faster and more effectively than ever before. And for patients who may rely on a new drug or therapy, the effects of this transformation can be literally life-changing.
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