Yet something still seems to be missing. Most pharma companies know little more than some basic demographics and prescribing patterns about their primary customers. That lack of information leads to fragmented marketing efforts, which dilute overall strategies and diminish returns.
Take sales forces, for example. The bulk of all industry marketing efforts go into setting up detailing programs. And yet many reps waste time and money again and again by visiting certain doctors 15 times, despite the fact that the last 14 visits did not lead to an appreciable rise in scripts. Good data mining may even reveal that some of those doctors are much more likely to respond to dinner meetings or to e-detailing programs. Knowing that would help companies spread their marketing dollars much more efficiently and effectively across channels.But to truly understand and engage in targeted marketing to physicians, a paradigm shift must occur. Pharma companies must move from being brand-focused to physician-centric by learning to link their marketing efforts. This can only be accomplished through a centralized data repository in which all marketing-to-physician activities are collected, measured, and analyzed. Then pharma executives could begin to identify the most effective marketing tactics for individual providers.
The Business Repository
This central database should capture information about every physician interaction across brands and channels, from sales rep visits to direct mail campaigns to interactive e-detailing sessions. Pharma vendors interacting with physicians, sales reps, and internal staff should enter data from those contacts into the repository in great detail. Specific information could include answers to the following questions:
Don't let labels fool you Profiles are the categories into which a given target falls. A "high-value" prescriber is a low prescriber with a tendency to increase new prescriptions when marketed to. A "high responder," in contrast, likes to attend events but is unlikely to change prescribing behavior. The "optimal" prescriber offers the perfect profile for the company's product. Categorizing physicians based on these profiles allows executives to identify the best ways to market to a given prescriber.
But marketers should not accept these profiles as black-and-white divisions; instead, they should use them as part of a mathematically derived scoring system, using econometric and statistical modeling to provide a probability ratio to help determine the likelihood that a certain physician will respond to a certain message.