What Is Predictive Intelligence?
Predictive intelligence (PI) is the application of predictive data analytics to derive insights that enable organizations to make better decisions and take actions that improve their performance. It applies predictive data models to identify patterns and relationships in data and then uses those insights to generate predictions about future events.
PI revolves around creating unique experiences for each customer by monitoring their behavior. The behavior helps the enterprise create a profile with that customer’s specific preferences, data they can use to predict what the customer might want next.
How to Build the Outcomes Model for Smarter Decision-making
The outcomes model is a simple, powerful propensity modeling tool that uses historical data to predict the likelihood of an event occurring. Propensity models are statistical models that are used to predict the probability of an event happening. The outcomes model is based on the principle that past behavior is a good predictor of future behavior.
The development of an outcomes model begins with identifying the organization’s goals and the factors that influence the achievement of those goals. Once the relevant factors have been identified, they can be mapped out. The final step in developing the outcomes model is to use it to generate predictions about future events by inputting data into the model and then using the results to inform decision-making.
How to Use Predictive Intelligence: Predictive Data Analytics in Action
Predictive intelligence can be used to improve a wide variety of business processes, including customer segmentation, target marketing efforts, and credit scoring. It also comes in handy when making marketing decisions, such as which customers are most likely to respond to a particular offer.
Predictive data analytics also help to identify risks and opportunities. For example, banks use predictive data models to determine which customers are most likely to default on their loans. Insurance companies use predictive data models to identify which customers are most likely to file a claim. And retailers use predictive data models to identify which customers are most likely to purchase.
The Takeaway
Predictive intelligence is a rapidly growing field, and its applications are becoming more widespread. Many businesses are using predictive intelligence to reveal their customers’ hidden intent. As predictive data analytics becomes more sophisticated, the potential uses for predictive intelligence will continue to grow.
