When a target group of physicians isn’t prescribing your brand, you need to understand the "why" so you can figure out how to change their behavior. You need to determine how best to promote the brand based on the current needs of individual doctors in that market.
Thanks to claims data and electronic health records, pharma marketers have a lot of quantitative data about which physicians prescribe specific drugs and for what conditions. You also know when and where these drugs are most often prescribed. But understanding the reasons why a doctor prescribes a specific brand remains elusive.
Factors that Influence Prescribing Behavior
The qualitative factors that influence prescribing behavior are complicated. The “why” behind a specific decision may be based on the physician’s feelings or past experience with a particular drug. It could also be based on patient-specific circumstances that may or may not be medical.
One physician may prefer Drug A over the very similar Drug B because his patients have experienced fewer side effects with A. But, as market access and reimbursement has become more critical than ever before, it is important to note another variable. A doctor might prescribe Drug A because she sees a large number of patients who are part of the same employer group, and it is the preferred option on their insurance plan.
How AIM Fills the Quantitative Gap
Teasing out the subtle differences – practice location, case mix, demographics, and any number of other factors – that influence physician prescribing decisions continue to be challenging. By providing insight into the real-time online behavior of individual physicians, audience identity management technology takes pharma marketers a big step closer.
Imagine this scenario. You’ve marketed your new oncology drug to Dr. Patel consistently for six months. His profile in your email database confirms that he sees patients who could benefit from your new drug, and email metrics indicate that he opens your emails.
You know that he has clicked-through to your website, and since you’re reporting on individual website visitors, you also know that he downloaded the clinical trial offered in your CTA. He even viewed several other research reports on your website. Clearly, Dr. Patel is interested, yet he hasn't written a single prescription. Now, you can engage with relevant and meaningful content to that prescriber.
A Possible Explanation
At this point, you might compare Dr. Patel’s profile with similar physicians who are prescribers, as well as non-prescribers. By identifying trends and differences in the content these doctors view on your website, you can develop a predicitive models as to why the non-prescribers aren’t converting.
For instance, you might notice that most prescribers visit your site frequently, rarely bounce back-and-forth between your site and other sites, and download multiple trials before prescribing. On the other hand, non-prescribers tend to bounce between sites and download fewer resources.
The fact that Dr. Patel has downloaded several reports and is focused on your site during his visits suggests that he is strongly considering your drug, but remains unsure about its safety or efficacy. Your best strategy might be to follow up personally, either with a customized email that provides additional scientific data, or through an upcoming event or sales call.
You should also cross-check profiles of prescribers and non-prescribers in your email database to identify geographic or demographic factors that might influence their decisions. Together, reporting on individual HCP website visitors and an authenticated email database deliver new insights into the motivations underlying physician prescribing behavior.