- Random marketing data via social media may not be applicable for your product/health condition.
- Marketers need to ask “why?” and “what does this include?”
- Perfect example is the latest health data from Rock Health. It doesn’t differentiate between health apps and fitness apps.
- DTC marketers need to conduct their own research and validate it with follow up research.
The PR cycle within the pharma industry sometimes creates more confusion and leads to bad decisions by DTC marketers. Two examples are data released by DRG and Rock Health.
First, let me say that I am a huge fan of DRG Research. I recommend that every pharma organization subscribe to their services. However, DTC marketers should never make strategic decisions based on their data alone. You need to work closely with your market research people to answer the questions about marketing YOUR product.
DRG released some data from one of their studies that seemed to show that more people are making a decision to ask for an advertised product from digital ads but is this true? First, it may not be applicable to your product category and second if someone saw your ad on TV and wanted to go online to “find out more” a digital ad would remind them of something they were going to do anyway.
Then there are the recent data released by Rock Health. On the surface, it looks like a good study, but it fails to differentiate between “health” and “fitness” apps. There is a huge difference between the two both in adoption by users and utility.
Readers of this BLOG know that I have spent a lot of time leading and sitting in research. By using qualitative research to listen to your audience and then validating the results with quantitative your strategy can take shape. However, you can’t just do some research and then run with it. You need to ensure your research is adaptive so you can implement changes as the market/your audience changes.
Releasing bits of data is a great way to gain exposure on social media, but trade magazines need to understand the limitations of what this data is telling us. Pharma does a lot of research, but the “art” of understanding what this data tells us, and more importantly, doesn’t tell us is may be hard to come by.