Find out what's a barrier to entry for healthcare marketing analytics, as well as what these institutions are hoping to learn and gain from big data.
Operating in a highly regulated environment with complex compliance and security requirements, the healthcare sector historically lags behind other industries when it comes to technology adoption, and marketing analytics is no exception. Instead, the focus in medicine has been squarely on technology that directly relates to healthcare and how it can affect positive outcomes in patients.
This is slowly changing, as hospital networks and other medical practitioners begin to more earnestly compete for market share. Healthcare marketing departments approach market share issues in two ways: by identifying prospective patients who are most likely to need the healthcare services they provide, and by ensuring these customers stay within their institutional networks once they become patients.
"We are seeing a growth of interest in demographics analytics in healthcare," said Matt Elson, a senior vice president for Evariant, which has developed a healthcare CRM platform that combines digital marketing solutions, big data, and analytics. "More of our healthcare clients want to be able to both manage and monetize big data," he said.
Elson said that one barrier to entry for healthcare marketing analytics is that developing these analytics must be a task that end business users can do — without having to enlist the help of an IT data analyst, or even a data scientist. "If you are a vendor in this business, you have to be able to 'abstract' big data in ways where the end user can work with the data without having to know the technical intricacies," he explained.
What do healthcare institutions want to know?
"They want predictive analytics derived from big data that can help them to better understand consumer behaviors and patterns in their service areas so they can determine which of their services is most likely to be in demand for certain demographic segments," said Elson. This might mean determining if there are certain demographic profiles at high risk for diabetes that might need preventive or treatment care. In other cases, analytics can be employed to assist hospital personnel in keeping add-on revenues within the institution by measuring which doctors regularly make referrals out of network where these add-on revenues are lost — or even preventing costs by identifying patients who should be reached out to for preventive care, which in turn can lessen visits to the ER.
There is also the "payback" side of every marketing campaign. In other words, if you invested one million dollars in a marketing campaign, did you derive more than one million dollars in revenue from the campaign?
"This is an underexploited 'sweet spot' for healthcare institutions that traditionally has been approached through customer relationship management (CRM) systems," said Kristin Hambelton, Evariant chief marketing officer. "When a healthcare institution marketing department launched a marketing campaign, it first constructed a 'propensity' model for consumers in its service area who would be most likely to use the service being promoted. Today, however, a marketer wants to use a mix of data from systems of record like an EMR (electronic medical record) system, and even video and digital media records. The marketer might then blend this data with third-party data, such as patient demographics profiles furnished by vendors like Experien. The marketer then develops a list of consumers most likely to need the new service. At the end of the day, someone is going to ask if the campaign was profitable. If 26 new people signed up for a new but expensive program, it's likely that the investment will be recouped and exceeded. An approach like this certainly has the ability to be more effective than just advertising the new service on billboards along roadways."
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