Predictive modeling is a subset of concurrent analytics, which uses two or more types of statistical analysis simultaneously. The goal of predictive modeling is to anticipate an event, behavior, or outcome using a multivariate set of predictors. Ultimately, predictive analytics can help marketers refine their list of target prospects to ensure highly relevant communication reaches the right audience. More
Healthcare Big Data & Analytics
By Sherrie Mersdorf | August 10, 2016
As we’ve written about previously, the key to harnessing the power of big data in healthcare is effectively analyzing, interpreting, and applying the data to create more successful healthcare marketing campaigns that ultimately result in improved patient outcomes.
But the obvious question is: Who in the healthcare organization is responsible for analyzing data sets and determining which data points will lend themselves to actionable insights?
The truth is that it’s no one person’s role – it’s the responsibility of the entire health system as a whole. In order to improve the patient experience, all moving parts of a hospital must be on the same page, especially the marketing and clinical departments.
That said, if there’s one role that’s emerging as critical to making effective use of big data, it’s that of the data analyst (or data scientist).
Let’s put a spotlight on the role of the data analyst in healthcare and explore why it’s so important:
By Sherrie Mersdorf | July 21, 2016
In a recent webinar, Dr. Bill Disch, Director of Analytics at Evariant, explained how to use concurrent analytics to optimize healthcare marketing campaigns. Concurrent analytics, a type of multivariate analysis, requires looking at multiple statistic categories related a single campaign, at the same time.
Ultimately, marketers can use this analysis to identify the consumers and/or patients most likely to respond to a particular healthcare campaign about a service or procedure, such as a hip replacement surgery. Marketers can take advantage of concurrent analysis to maximize their data analysis, reduce marketing cost, and improve short- and long-term ROI.
Let’s take a look at some key takeaways and questions asked during the webinar: More
By William Disch | July 20, 2016
Try this statistic on for size: The 500 petabytes of digital healthcare data that existed in 2012 is predicted to reach 25,000 petabytes by the year 2020. That’s an increase of nearly 50 times the amount of data from just eight years prior!
Healthcare marketers may be swimming in data, but what’s important is to not drown in it. The key, in other words, is to not just have the data – but to figure out what you’re going to do with the data.
As will be discussed during today’s Evariant webinar, analytics in healthcare is critical for making effective use of data. Predictive analytics can help drive improved health outcomes for patients and give you the biggest bang for your marketing buck.
But the question is: What, exactly, is predictive analytics? More
By Sherrie Mersdorf | June 15, 2016
Healthcare marketers want to reach their target audiences at the right time with the right message. A data platform that integrates patient information from a variety of sources can assist marketers in creating and optimizing their marketing campaigns.
According to Jeff House, AVP of Marketing at Wake Forest Baptist Health, real-time analytics has helped their marketing department optimize Facebook campaigns to drive success. More