This is the second post in a two-part series that discusses healthcare predictive and propensity modeling and selecting the optimal analytics partner to support your growth and engagement efforts. The first post in this series shares five best practices in healthcare propensity modeling.
In our last post, we talked about big data, healthcare, and predictive modeling: How can you leverage your health data, analytics, and modeling to get the “biggest bang” for your marketing dollars?
However, as we mentioned, the million-dollar question is: With so many variables (and so much data) at play, how can healthcare marketers ensure they are effectively leveraging propensity and other predictive modeling?
We provided five guidelines for consideration when you commence predictive modeling:
- Define target/goal
- Use best data
- Use multiple data sources and most appropriate analytics
- Ensure data are vetted/validated
- Deploy validated analytics and employ follow-up testing
If you decide to use predictive modeling, you must ensure you are engaging with a HCRM partner that can support best-in-class analytics. There are several components to consider when doing your due diligence on a potential partner. For example, some provide in-house modeling and analytics; sometimes as a menu of options, other times as custom services for a fee. Others outsource their modeling and analytics to (usually) industry agnostic companies; however, there are also many smaller, boutique/niche analytics companies that provide some specialization. More