Healthcare and pharmaceutical companies are multi-channel veterans – addressing physicians and other target groups across differentiated communications channels is the standard in the industry. Which communication channel has the biggest impact on the prescription behavior of physicians often remains unclear for many companies, however.
Our customer, a globally leading pharmaceutical company sought to answer this question when he contacted Homburg & Partner. His goal was to choose the right channels for communicating with general practitioners based on data. In connection with this, internal resources and budgets were to be allocated more efficiently according to the expected value contribution per channel.
“Nobody has a magic ball – you cannot nor will you be able to completely model prescriptions from doctors. While communication channels often used to be selected in an unsystematic way, the statistical analysis of large data volumes for the prioritization of channels is a milestone in Commercial Performance Management. This is a huge help for our clients to drive the future selection of channels as well as the discussion surrounding appropriate budget and resource allocations a step further both based on facts and independently of people’s personal gut feeling.”
The development of a high-quality database was at the heart of the first project step. We developed these together with our client by aggregating information from internal client systems (such as channel frequencies of the target group from CRM system) as well as external customer data (such as prescription figures of general practitioners from external service providers) in a data cube. Internal and external data could be linked via unambiguous key criteria. Data protection conformity was ensured throughout the entire process. To make it easier to provide available data from the internal CRM system, we created a standard template that clearly showed our client contact persons the required data structure.
The created data cube made it possible to quantify the value the 15 analyzed channels contribute and to visualize their impact on the prescribing behavior of general practitioners and their attitude towards the product. To achieve this, a stochastic model (correlation analyses, multivariate regression analyses, cluster analyses) was used to prove the effect of individual communication channels in a statistically significant manner. The available data on the client’s communication measures with general practitioners exhibit a high degree of complexity. This makes it possible to carry out analyses according to certain sub-target groups and geographical regions (e.g. associations of statutory health insurance physicians).
The creation of a data cube marked the starting point for the analysis of the value contribution per channel. The cube combined all relevant internal and external data on client communication with general practitioners. This data cube was the client’s first tool that integrated all information on the frequencies of different channels that had previously been collected decentrally. Together with our client, we collected internal data from the CRM system to create it. In addition, we took over the communication with third party data providers for our clients in order to ensure the anonymity of external data (such as the prescription data of general practitioners) according to the ethical and moral principles of market research. After the project, the data cube could be provided to the client as a starting point for further individual analyses of communication with general practitioners.
The project provided our client a clear statement about which communication channel contributes which value to the prescription behavior of general practitioners. The 15 channels used were not only considered as individual silos, but also examined as different sequences of channels that are combinable – depending on how the client fashioned the communication with general practitioners across different channels. For example, it was possible to determine the value contribution of a trade conference with customer communication measures that occurred before and afterwards compared to a conference without accompanying communication.
In addition to the impact of a channel on prescribing behavior, it also became apparent how communication across channels affects general practices’ attitude regarding the product. To this end, data on the channel frequencies of the target group were combined with the classification of general practitioners on an internal adoption ladder by the responsible field staff. One result of this step was to provide the client with a clear statement on which communication channel increases the likelihood that a general practitioner recommends a product to a colleague.
The project results were presented to our client as a digital dashboard, which shows a channel’s effects on the prescription behavior of general practitioners as well as on their qualitative attitude towards the product and recommending it. This way, the client can take both effects into account when prioritizing channels in the future. In addition, all project results were visualized in a typical visualization tool to allow the client to conduct further analyses beyond the project scope. In the course of this step, the interface was custom-adapted to our client’s preferences and available systems and the compatibility with established tools such as Tableau or PowerBI was ensured.
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