Predictive analytics utilizes present and past data to forecast future events, acts and trends. It entails using statistical analysis methods, analytical queries, and automated machine learning algorithms to generate predictive models that set a numeric value or score on the probability of a specific event occurring.
Predictive analytics helps enterprises uncover data patterns by going farther than simply knowing what has occurred, to expecting what will probably occur next. Companies rely on predictive analytics to answer questions and discover new opportunities such as:
Marketing Optimization: Predictive analytics help to uncover consumer responses or buying behavior and helps to increase cross-selling opportunities. Predictive analytics helps organizations acquire, keep and nurture their best clients and buyers.
Detect Fraud: With a growing cybersecurity concern, high-performance behavioral analytics looks at all activities on a network in real time to discover irregularities that may show signs of fraud.
Minimize Risk: A person’s credit score is used to determine a consumer’s probability of non-payment or default.
Improve Operations: Organizations often use predictive models to predict inventory and manage assets. For example, airlines utilize predictive analytics to determine ticket prices. Predictive analytics empowers companies to better perform.