They can be used to predict virtually anything containing existing data, in every sector imaginable, from ratings of any program, a customer's next purchase, credit risks, decision making among others.
Most predictive models work quickly and often complete their calculations in real time. So banks and retailers
can, for example, calculate the risk of an online mortgage or credit card application and accept or reject the request almost instantly based on a prediction, also a software
company could model historical sales data versus marketing
spend in various regions to create a model of future revenue based on economic impact.
You may be interested in: "Big Data Models Most Commonly Used in Business
A predictive model is not fixed; it is regularly validated or revised to incorporate changes in the underlying data. In other words, it is not a one-time prediction.
Predictive models make assumptions based on what has happened in the past and what is happening now.
Also see: "Data Science for Analyzing Business-to-Business Relationships
".What are the two models most commonly used by businesses?Forecasting Models
Handles the prediction of metrics by estimating new data values based on learnings from historical data. It is often used to generate numerical values on historical data when none exists.
Forecasting models are popular because they are incredibly versatile.Classification Models
These models work by categorizing information based on historical data. Classification models are used in different industries because they can be easily retrained with new data and can provide extensive analysis to answer business questions.
Do you know that we are now part of something bigger?
Learn about PREDIK Data-Driven
, our new global brand.
, help gain long-term insights of the average purchase value, customer lifetime value and users interaction with a brand, enabling companies to incorporate data-driven business strategies that facilitate decision making and revenue maximization.
that enables organizations to identify hidden patterns, understand market trends, identify demand, establish pricing strategies, achieve a high return on investment, optimize and reduce