Life Sciences, Strategy, Performance Marketing

Omnichannel Marketing: Optimizing Your Strategy With Data and Look-alike Models (Part 7)

Part Seven of MERGE’s seven-part series on omnichannel marketing focuses on optimization and how organizations can leverage data to optimize marketing mix and build look-alike models that help drive efficiency and reduce costs

PUBLISHED: 12/6/2023

In the rapidly evolving field of life science, marketing efficiency and cost-effectiveness are more crucial than ever. As organizations strive to reach the right audiences with tailored messaging while maximizing efficiency and minimizing costs, the role of data-driven decision-making and the utilization of cutting-edge look-alike models has become vitally important.

Here, MERGE addresses the challenges life science organizations face when it comes to optimizing their marketing efforts for an omnichannel ecosystem, and explores how industry players can harness the power of data and sophisticated modeling techniques to elevate their marketing efforts, ensuring that it not only aligns with your business objectives but also paves the way for more effective, cost-efficient, and responsive marketing campaigns.

The Challenges and Opportunities of Leveraging, Optimizing Data Within Your Omnichannel Strategy

With an abundance of data at their disposal, it can be daunting for some organizations to determine which data is truly effective in measuring outcomes. To use a coined term from Bob Deininger, Vice President and Integrated Media Lead at MERGE, this “infobesity,” in his opinion, actually stands as one of the biggest obstacles for organizations when it comes to optimizing marketing efforts.

“What we try to do with clients is think about their goal, the KPIs, the metrics to measure that goal, and then the data,” says Deininger. “Sometimes there is so much data it can be hard to find what is most relevant, useful, and actionable.”

Adding even more complexity to the data overload is the fact that many organizations encounter data lags, a relatively common occurrence in the life science sector, where some critical data, such as claims data, may have a significant lag, which can impede real-time decision-making.

“Claims data oftentimes helps inform how impactful media was, though it typically has a two-month plus lag,” says Sara Van Kuiken, Director of Integrated Media at MERGE. “If we’re doing a prescription life analysis, to get the relevant claims data and to be able to analyze that and optimize against that, there’s usually a very small window of data that can be analyzed in order to make optimizations mid-flight to impact the rest of the campaign.”

So what types of data are most valuable for optimizing an omnichannel marketing strategy? 

In general, historical data is always preferred over 3rd-party data, but that doesn’t really tell the full story. In a more specific sense, data points such as a National Provider Identifier (NPI) number can be tremendously useful when it comes to enabling one to pinpoint specific HCPs that are visiting your website or landing page.

“We’ve talked to clients about being able to identify their site visitors by an NPI number,” says Deininger. “There are ways of collecting that NPI number and that can be a very valuable data point as it allows you to identify specific HCPs. Oftentimes there are campaigns with PLD (physician level data), which can provide a campaign with information on which physician (by NPI number) was reached, did they click an ad, did they visit the site, and stuff like that so you can connect those dots. 

“Part of the challenge with analytics is what I call ‘making the handshake’ between data sets. Something like an NPI number can be that sort of link that can ‘make the handshake’ between two data sets.”

NPI data also plays an integral role in look-alike targeting, which is the practice of delivering messages to individuals who look and act similar to the members of your target audience. From the perspective of Jason Budelmann, Vice President and Analytics Leader at MERGE, this is an effective way for organizations to anticipate certain actions taken by a target audience.

“By purchasing NPI data or physician lists, and then looking at specialities and the prescribing habits of not just the desired drug, but also the competitors and doing our own version of algorithmic look-alike modeling, we can figure out what traits show the highest propensity for an action,” says Budelmann. “We can find out that, of the people that are the highest prescribers right now, we can uncover who that next wave is or what that next style is of HCPs we want to target.”

Attribution is another key component of the omnichannel marketing mix, which allows an organization to measure what touches are needed in order to get members of a target audience to a desired end point or business outcome. In many ways, leveraging attribution helps shape the overall campaign strategy that an organization may have.

“It could be as simple as media, sometimes it's the website experience, or sometimes it's making sure that you're routing a member of your target audience to an actual person on the phone rather than just a generic email or something like that,” says Budelmann.

“Attribution measurement is probably one of the more critical areas that we're kind of going into. It's tailor-made for omnichannel, because omnichannel – to me – means that all these data sets are working together and it unlocks what’s possible when all these data sets are working together. It allows us to understand that it was a certain creative, or a certain touch that prompted the phone call or action that the customer took.”


The complete omnichannel marketing series is below:

Part One: An Intro to Omnichannel Marketing
Part Two: Mastering the Art of Journey Mapping in Pharma
Part Three: Captivating Customers with Creative Content
Part Four: Making the Most Out Of Media Activation
Part Five: A Deep Dive On Data Capture and Analytics
Part Six: Keys to Supercharging Your CRM Program
Part Seven: Optimizing Your Omnichannel Strategy With Data and Look-alike Models