Are You Still Using Clicks to Measure Hard Conversions?

Many of our clients spend a lot of money on DTC pharma digital marketing for their copay assistance programs. When we ask them how they measure the effectiveness of their DTC marketing dollars, we are often told that they i) optimize their cost per click and ii) count specific clicks (eg. going to a copay registration site or beginning the search for a physician) as "hard" conversions.

We know this can be frustrating, especially for people with financial oversight as they are unable to see the direct economic benefit of their pharmaceutical marketing strategies and investments.

CodeBroker offers a unique solution for pharma marketers that provides a way to easily change the definition of a hard conversion from a click into a utilization/NRx. With the knowledge of the number of copay utilizations/NRx's that can be directly attributed to your specific DTC promotions/channels, you can optimize your pharma digital marketing dollars and identify which DTC promotional activity is most advantageous for your business.

As an example, one of our clients had been focused on "clicks" to their copay assistance registration page as a "hard" conversion and they were using Google analytics to track their "funnel" with the view of the registration page as the final step. With CodeBroker's 1:1 tracking solution, our client is able to look at their data very differently. They are able to build a detailed funnel beginning with the original click and ending with with an NRx/TRx. They can see how many people arrived at the copay assistance registration page, what subset of these people completed registration (and how long in between), and what subset of the people who completed registration utilized the copay program (as well as how long between registration and NRx). This data can be viewed by the original source of the click/patient interaction (eg. September Facebook campaign), providing key insights into exactly which promotional vehicles are working best and generating the most utilization per invested dollar thereby enabling them to improve their pharmaceutical marketing strategies.

Similarly, the funnel data can be sliced by time. For example, our clients can see how many people viewed the copay assistance registration page in September, the subset of those people that viewed the registration page in September who eventually registered for a copay card, and the subset of the people that viewed the registration form in September and later registered who used their copay card (even if the registration/utilization occurred in a later months).

By providing our clients with detailed funnel information that can be sliced by time and by originating source/web site, they are able to identify key opportunities for improvement to help avoid drop offs, improve performance, and strenghten their pharmaceutical marketing strategies.

For further reading on this subject, check out our whitepaper on how to map and execute a thorough best-in-class impact measurement plan for co-pay programs or read more on our pharmaceutical solution page on this site.

If you are tired of using clicks as a proxy for hard conversions, please contact us so we can show you how easy it is to implement our solution.