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Blog
Data-Driven Precision Marketing
Why it's time for drug developers and device manufacturers to embrace a data-driven approach to marketing
Kal Chaudhuri, MBA, Principal, AI/ML Products and Consulting
Jun 04, 2021

The pharma industry spends about $4 billion dollars per year on national TV ads alone, and another $11 billion dollars on digital ads. This is a huge part of their marketing budget, with some brands spending $20 million per month on TV ads alone. Yet only a fraction of population who see these ads will find value in them, and an even smaller number will take an action as a result.

This approach is a fine way to raise general awareness of a product, but it could be far more cost-effective. When marketing teams use existing healthcare data to customize their advertising message, channels and outreach, they can have a much more powerful impact.

Lessons from Amazon

Pharma companies capture millions of pieces of data about their customers. Marketing teams can use that data to engage with customers in more meaningful ways, and to customize messages based on their most recent behavior.

This real-time custom approach to marketing is not only possible, it has become the norm for consumers who are accustomed to receiving real-time suggestions from companies like Netflix, Amazon, and Facebook. These tech companies built their business models around the ability to deliver highly tailored recommendations to every user based on past decisions and behaviors. Their use of real time analytics and data makes the recommendations almost eerily accurate.

The pharma industry can do the same thing with drugs and devices. Using real-world patient data and machine learning algorithms, developers can analyze details about patients’ healthcare needs, their behaviors and choices, to predict what products they will need next, when they will need them, and what obstacles could be standing in their way.

These insights can be used to create highly customized marketing campaigns that target the specific subpopulations most likely to respond to an ad. The payoff of this level of customization could deliver a huge bump in response to current pharma ad campaigns.

Who? What? Where?

The transition to data driven marketing isn’t difficult.

Pharma companies already capture detailed data about their customers’ preferences, including what they like, when they shop, where they live, and what price points they prefer. When they introduce machine learning algorithms and global healthcare data analytics to their marketing strategy, they can compare individual insights found in their data against decisions made by a similar sub-population of patients, to predict what that customer will need before they even know they need it. Each time a consumer responds to (or ignores) their recommendations, it further informs the algorithm, so it becomes more precise with every interaction.

IQVIA’s Subpopulation Optimization and Modeling Solutions (SOMS) has this capability. Our data analytics experts work with clients to create custom algorithms that combine their internal customer data, with IQVIA’s global healthcare data sets to define specific population subgroups based on differential research methods.

For example, if a drug developer wants to create a marketing campaign to encourage adherence to a specific product, they would work with IQVIA’s SOMS team to analyze internal product and supply chain data in combination with IQVIA’s Longitudinal Prescription Database (LRx) to identify specific regions, markets, and patient demographics that have a high rate of non-adherence.

They can use these insights to create ads targeting this specific demographic, then monitor prescription refill rates to link the ads to market improvements.

It is one of many examples of how the SOMS technology can be used to improve and measure the impact of marketing efforts. Developers can also use it to determine things like which patient subgroup will prefer their treatment over a competitor, which patients are likely to switch treatments and when, and how a patient’s insurance provider or physician preferences impacts treatment decisions.

All of this data can inform more targeted campaigns that funnel marketing dollars toward the channels, regions, and messages that are most likely to resonate.

This approach could also help developers accelerate uptake of new drugs. By combining clinical research and market data, the SOMS technology can predict which subpopulations are most likely to experience the fastest or best health outcomes from the product. This knowledge can be used to target patients of interest, which can bolster early product success data and drive excitement about the product in its crucial first months in the market.

Generate some buzz

The pharma industry is wildly innovative when it comes to creating lifesaving drugs and devices, but it has been slower to embrace digital innovations to support these products in the marketplace. As a result, they are spending millions of dollars on ads that aren’t delivering the best possible results.

Integrating a data-driven approach to their marketing efforts could have a significant impact, and the risk is low. This is not bleeding edge technology. Online retailers, media streaming services, and social media companies have been using this approach for years, and the benefits are well documented. It’s time for pharma to follow suit.

If you’d like to learn more about how to better use this methodology to shape your marketing strategy, please contact us today: sos_support@iqvia.com.

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