Mapping data innovations—from transactions to transformation

Virtually every company in business today operates in a rapidly evolving data landscape. It seems like a week doesn’t pass without a shiny new data solution appearing on the scene, promising better insights, greater efficiency, or increasingly seamless automation. This leaves decision-makers—especially in healthcare marketing—with the challenging task of wading through these options to determine the right course of action to steer their company through this complex and crowded industry.

Many of these modern advances, while helpful, also require significant retooling of existing data infrastructures—which often means a significant capital investment. So how do leaders actually decide on a path forward? Do the benefits of adopting a new data solution outweigh the financial costs of change and the inevitable organizational chaos that comes with retooling data infrastructure? First and foremost, it’s crucial to remember that the fundamental key to success is the data.

Therefore, the top priority must be collecting and retaining data at a transactional level. For pharmaceutical companies, this includes keeping promotional partners and targeted healthcare providers (HCPs) at the center of these exchanges. After all, a data-driven company is nothing without its data.

The transactional data advantage

Transactional data capabilities have progressed rapidly. Promotional partners have built systems that allow clients to seamlessly transfer transaction-level data from one company to another, enabling agencies and other marketing partners to integrate this valuable information into a single comprehensive data warehouse.

In many ways, the rising demand for transparency has been the driving force behind these developments. Companies spending millions of dollars on promotional channels now expect accountability. As a result, when decision-makers are given a choice, the promotional partner who can provide a transactional data feed has a decisive edge over their less capable competitors.

Breaking down barriers to claims data

However, the innovations surrounding data run much deeper than just the transactional level. Even when companies manage to collect promotional data from multiple partners, they still struggle to precisely target and measure promotional impact without data on diagnoses, procedures, and, most importantly, prescriptions.

Historically, access to this claims data came with a steep price tag—often requiring a six- to seven-figure up-front spend. This cost barrier left many small and mid-sized pharmaceutical brands relying on less precise tools for targeting and impact analysis.

The solution to this problem brings us to one of the most exciting data innovations happening today. Data providers and promotional partners are experimenting with different business models that offer potential clients “up-front” access to this data—without requiring a major check to get started.This democratized approach is opening up access to vital data resources for more data vendors, promotional partners, and pharmaceutical marketing agencies than ever before.

The business models democratizing access

To see this experimentation in action, one just has to look at DeepIntent. By partnering with both IQVIA and Symphony, they are giving their clients access to the claims data from either of these health information companies. That access can then be used to identify potential targets and analyze the impacts of their promotional efforts. The result is a single hub where marketers can view target data, promotional engagements, and prescribing outcomes.

Similarly, companies like HealthVerity are also experimenting with new financial models. By building a clearinghouse of diverse claims data sources, they give potential customers the opportunity to access and review the intersectionality between them. This provides clients with a transparent overview of the options available to them which, in turn, can help guide their purchasing decisions.

Through these evolving models, clients now have a unique opportunity to access claims data in new, cost-effective ways. This shift is particularly beneficial for mid-sized pharmaceutical companies and the agencies that serve them. As the data landscape continues to expand, it will be increasingly important for all of the parties involved in pharmaceutical marketing to embrace—and keep experimenting with—new business arrangements that can broaden data access and address critical unmet needs. There will undoubtedly be stumbles along the way, but when the right combination is found, it will be an industry-wide game changer.

The limitations of AI today

No discussion of data advancement is complete without mentioning artificial intelligence (AI). There is little doubt that the societal impacts of AI will ultimately rival the impact of electrification. Still, there are limitations to this technology, especially in its current configuration, and caution is warranted when using it for pharmaceutical marketing data efforts.

AI is already useful for freeing up staff hours in repetitive workload functions, such as quality assurance (QA), quality control (QC), and data monitoring. However, there is some hesitation around its use in high-level analytics like ROI assessments. The pharmaceutical market in the United States is one of the most complex in the world. A typical campaign may involve a dozen or more promotional partners, in addition to the company’s sales force influencing HCP prescribing behavior. Add to that consumer-facing social media campaigns used to sway consumer sentiment, government pressures, and pharmacy benefit manager (PBM) negotiations, and it becomes extremely difficult to pinpoint what truly moved the sales needle.

On the surface, this may seem like the perfect opportunity for AI to decipher which campaign effort had the most impact—but is it really? At the end of the day, the insights generated by AI must still be defended up the chain of command, and it can be difficult to inspire confidence in a recommendation that emerges from a “black box.” Traditional statistical methodologies, by contrast, give a company the calculations, parameters, and confidence intervals marketers need to stand behind their conclusions.

A future defined by AI and human intelligence

AI will eventually win out. It’s almost guaranteed that in the not-so-distant future, analysts will be able to ask an AI assistant to produce, explain, and defend data analyses. Undoubtedly, it will also be able to present its findings at client meetings—perhaps even directly to a client’s own AI system.

However, we are not there yet. In the meantime, AI’s greatest value remains its ability to help companies save innumerable staff hours by handling the redundant, time-consuming grunt work analysts once did by hand—letting them focus on what clients really care about: ROI analyses and high-level data strategy.

The pace of data advances is fast and furious—and it shows no signs of slowing down anytime soon. The best way for pharmaceutical brands and agencies to handle this flurry of changes? Remembering that, from transactions to transformation, the brands and marketers who remain focused on the data will define the future of healthcare marketing success.