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Analyzing Data in the Medical Device Marketing Landscape

Understanding how to analyze and leverage data for medical device marketing is critical to product launch success.

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- Unlike the pharmaceutical industry, which has built-in data collection strategies through prescription data, medical device companies do not have the same regulated data-tracking technologies. Understanding the importance of data and how to analyze it appropriately is critical to successful medical device marketing.

Michael Monovoukas, Co-Founder and CEO of AcuityMD, discussed the crucial components of medical device marketing and provided predictions on the industry’s future in an interview with LifeSciencesIntelligence.

Essential Factors in Medical Device Marketing

Monovoukas described multiple important components in medical device marketing that good data and appropriate analytic tools can support.

Ideal Customer Profiles

“It all comes down to identifying and empathizing with the ideal customer profile. And that ideal customer profile might be different as a product launch versus when it has already been in the market for three or four years,” he began.

For example, companies launching a surgical medical device may ask themselves the following questions.

  • Who are the surgeons who may be early adopters?
  • What do they care about?
  • What research is available on them, and what research can be conducted?
  • What data can be extracted to understand that ideal customer profile?

According to Monovoukas, the medical device industry broadly comprises two dimensions of ideal customer profiles. On the one hand, marketing teams must consider people using the product, including healthcare providers and surgeons. But beyond that, the teams must understand the facilities supplying the products.

“Each of those dimensions might have a different definition of the ideal customer profile,” he explained. The dimensions may also have different data sets defining the ideal customer profile.

Gathering Data

Monovoukas mentions that there is built-in data to understand who is “using” a particular product through prescription data in the pharmaceutical industry. However, he notes, “In the medical device industry, there is no system of record or dataset that can tell companies which physicians are using which products.”

As a result, most medical device companies have a hard time gathering data on who the product users are.

“There's no central database that these companies rely on to structure that information of who's using their products today. If they don't have that building block dataset built out of who uses the products today, it's tough to understand and empathize with the ideal customer profile,” he added.

Marketing and Sales Collaborations

Another critical component of effective and successful medical device marketing is collaboration between the marketing and sales teams during the launch. Monovoukas noted that marketing teams are well-positioned to keep sales teams focused, informing them where to launch new products.

“The feedback that [marketing teams] get from sales can also help them tune their understanding of the ideal customer profile,” he added. “That relationship is critical as products launch.”

Beyond keeping the sales team focused, the marketing team must be open to learning from the sales team and adjusting things that they may have gotten wrong.

Early Adopters            

Finally, Monovoukas emphasized the importance of turning early adopters into product champions to advocate for the product. These individuals can act as a reference point when the products reach the market, supporting the uptake of the tool and sharing their experiences.

Types of Medical Device Data

Companies can use a lot of data to analyze their market; however, it is critical to understand what data will provide insights into product or market outcomes.

“For data to lead to outcomes, it not only needs to be presented in a way that is actionable, but it also needs to be tracked.”

Companies can begin to gather information from external market data or data providers to compile an ideal customer profile; however, it can take multiple attempts before a company or marketing team accurately understands what data is vital to developing the ideal customer profile. As a result, Monovoukas recommends integrating first-party data with external data to enrich the information and gather the relevant information.

By leveraging insight from sales reps and the outcomes in the market, companies can gather a more comprehensive picture of the ideal customer profile, enriching their understanding of that community and its needs.

“It’s [about] combining external or market data with internal feedback. And creating a feedback loop or a flywheel, such that external data and internal data make [up] the way [marketing teams] define the ideal customer profile better and better over time,” outlined Monovoukas.

Static Data

There are two primary buckets of data in the medical device industry. “The first is static data purchased from data providers,” Monovoukas said.

For example, static data can be collected from medical claims data purchased from aggregators. However, this data type is only helpful for singular analyses, like building presentations for leadership and investors. Static data does not provide insights into the return on investment (ROI).

“It's a one-off pull of data, and that data gets stale quickly.” Medical device companies that rely on that static data and are accustomed to purchasing static data to drive analytics cannot adapt to market changes.

For example, “companies who relied on static data pulls and outdated analyses were not able to adapt to the changing market as COVID unfolded,” Monovoukas elaborated.

In that scenario, many elective surgeries were canceled; however, other surgeries or procedures that could be moved were migrated to the outpatient settings. Companies using static data relied on the idea that surgical cases in in-patient settings would rebound after the pandemic, and there would be a backlog of cases to account for any pandemic-related sales losses. However, that’s not what happened.

“Hospital volumes for certain surgeries never rebounded to their pre-COVID levels. And those surgeries permanently shifted to an outpatient and ASC setting. Companies that relied on static data were blindsided by that shift, as opposed to companies that had built data into their day-to-day commercial workflows, that could see that change unfold in real time,” indicated Monovoukas.

So, although static data can power reporting, companies using it exclusively cannot remain agile.

CRM Data

In place of static data, the medical device industry may also rely on customer relationship management (CRM) systems requiring sales representatives to enter data manually.Monovoukas defines it as “surveying reps for data so that marketing can build smarter campaigns.”

When done correctly, CRMs can provide valuable insights into sales trends and inform marketing; however, it is an uphill task for sales representatives.

“A sales rep doesn't want to be spending a bunch of time inputting notes, filling out questionnaires, and clicking different boxes when they could be selling,” he commented. “So, it's a tax on those sales reps. It takes away from their time in the field, learning about the customers, building new relationships, and selling new products. That's the challenge with traditional CRM systems.”

Enriched Data and Product Launches

Despite having innovative technologies and science, many medtech companies struggle to commercialize their products due to the astronomical cost of bringing a medical product to market in the United States.

“Part of the reason we started AcuityMD was to use data and software to make it easier to launch a product and gain traction across the country so that we could put the power back into the hands of the innovators, and they could get their product out to the doctors and the patients who needed it the most.”

Monovoukas reiterates the importance of understanding the ideal customer profile to facilitate that. Moreover, he indicates the level of detail required for that success.

“Once a company builds that database of who's using its innovative new technology, it can join that data against all sorts of other market data about that type of physician. So, for example, what do product users care about? What disease states do they treat? What procedures do they do? Where do they operate?”

Having enriched, detailed insight into the customer profile allows teams to customize their messaging and cater to what a particular individual or organization cares about.

ROI

Beyond standard datasets, Monovoukas emphasized that ensuring the underlying data is high quality and complete is critical for getting to the correct answer. He notes that investing in data analytics for the sake of data analytics will be limited in the future. Instead, the focus will shift to ROI.

“Data and analytics are only as good as the outcomes and actions they generate or the insights generated. That's why data quality and completeness are paramount. It can lead to the right actions and outcomes, but [companies] also need to ensure the outcomes and the actions happen.”

Future Predictions

Monovoukas also provided LifeSciencesIntelligence with his insights into the future of data analytics in medical device marketing.

“[Language models are] going to have huge impacts in the medical device industry,” said Monovoukas. “First, from a data and analytics perspective, one of the big pain points with reporting and analytics, in general, is that it's just a lot of work to munch through the data, figure out the right visual to display, iterate on the visual, and come up with a theme and a tagline of what to present, and package it in a way and in a narrative that makes sense for the audience.”

Monovoukas implied that business intelligence tools will revolutionize analytics in the next two. He anticipates that in the next two years, marketers will be able to ask AI for trends in a specific market, and the language model will be able to pull out insights independently.

“The ability to generate reports will become powered by AI. That's right around the corner, which is exciting because it saves leadership and analysts a lot of time trying to craft these stories and munch through the data themselves.”