Predictive Analytics Today

Nothing new here, but nicely presented, with visuals.  We did predictive analytics many years before AI or Machine learning.  Many millions in value.  True we sometimes did not have the data required, especially outside the enterprise.  Or as it related to consumers.   Today that's much easier to get.  But the methods were often useful pointers to real predictive value.   Taking this beyond to prescriptive analytics should also be used as a method to both build and deliver such systems.  If can always be done with process models.  Start simply.

Use Machine-Assisted Predictive Analytics to Capture Your Customer’s Heart, Mind, and Pocketbook!     Bob Hayes, PhD in CustomerThink

As users/customers engage with a company (their products, services, surveys), they generate a lot of data about their behaviors and interactions with the brand. Predictive analytics and machine learning capabilities provide a way to extract insights from that data to help you improve the customer experience and optimize customer loyalty.

Machine Learning and Predictive Analytics

Today, businesses can collect hundreds of variables about their customers. Real-time delivery of insights necessitates the quick processing of these data. Toward that end, companies are employing the power of predictive analytics and machine learning (ML) to extract insights from data.

There are generally three types of analytics: descriptive, predictive and prescriptive. Descriptive tells you what happened. Predictive tells you what will happen. Finally, prescriptive analytics tells you what decisions/actions you need to make/take to maximize opportunities/mitigate risk. .... "