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Behind The Scenes Applications of Predictive Analytics

Behind The Scenes Applications of Predictive Analytics

In every industry, there are several behind-the-scenes applications of business intelligence and predictive analytics. Take a look at 3 analytics-based solutions that you might not be aware of:

  1. Retail & Merchandising Optimization

It has been the universal rule in merchandising to place a brand’s best and most popular products on shelves that are the easiest to reach. The items that do not move as fast are then placed on the lower shelves. However, with the help of data analytics and the ability to record media before combining them with other data, it is now possible to chart the paths that customers take through shops, observe which products they reach for most, and analyze how placement affects how much they prefer a product. In-store merchandising is rising to new levels thanks to this form of analytics.

  1. Identifying Law Enforcement Suspects

Right after a crime has been committed, it can be challenging for police officers to identify suspects who have left the crime scene and chase them down for arrest. During the past decade, city, county, state and federal authorities have been working together to offer continuous access to a wide range of databases at all government levels. These databases have both unstructured and structured data, such as fingerprints, arrest records, photo IDs, and text entries from various computer systems. This information is easily accessible by officers in their cars and increases the chances of quickly identifying and pursuing suspects.

  1. Collecting Patient Demographics

Due to insights gained into demographic pockets of patient groups, many more health and life saving steps can be made. One notable example includes the discovery that people from a specific geographic area have higher likelihood of getting diabetes. While preventive medicine diagnostics is not as widely used now as they will be in the future, there is significant potential for it. The ability to accurately predict conditions that are most likely to affect patients before the conditions even manifest can greatly assist patients in lessening its impact or avoiding it completely.

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