Television represents the largest direct-to-consumer (DTC) promotion expenditure for most pharma marketers. In the first quarter
of 2010, 59 percent of pharmaceutical DTC spending was on television ads.
Photo credit: NBC (Cast of "Law & Order Special Victim's Unit")
But brand managers who are relying solely on traditional ad placement methods rather than using newer, more sophisticated
methodologies, may be missing opportunities to reach target patients as well as wasting spend.
So what are these new methods? Digital capabilities that anonymously link what we tune in to watch on TV with the prescription
behavior of consumers. The result? An ability to determine the most effective networks, programs, and times of day to reach
patients of interest and to measure the impact of the campaigns. In turn, it enables brand mangers to base the placement,
measurement, and refinement of their strategies on empirical data, which can result in more efficient investments and greater
Is Pre-Market Planning Hitting the Mark?
A key objective of DTC advertising is to drive patients to visit their physician and request the prescription brand advertised.
And when it works, it works: Take TV advertising for the osteoporosis market. At its peak in 2008, osteoporosis patients requested
a specific drug from their physician during 20 percent of visits. And studies show that physicians tend to grant patient requests
and issue the sought-after drug, unless there is a valid reason not to. In 2008, when Actonel was requested by patients, physicians
issued it 98 percent of the time.
Given the significant investment that goes into pre-market campaign planning, particularly creative and message testing, the
same level of rigor needs to be applied to ensure the ad is effectively reaching the intended audience of patients. However,
TV real estate continues to be purchased based on traditional parameters of audience age and gender demographics, at the right
More Sophisticated Post-Market Methods
How exactly do these new methodologies work? Anonymous longitudinal patient data tracks, among other things, prescription
activity over time. By reviewing what drugs patients have filled recently, they can be classified as being treated for conditions
in different therapeutic markets. A combination of tuning and prescription behavior then enables an analysis of what patients
in different healthcare markets are watching.
In addition, evaluations can determine the influence an ad has had on patients who viewed it. Advertisers are then able to
accurately gauge differences in the prescription behavior of patients exposed to an ad compared with nonviewers.