Predictive intelligence (PI) is the built-in layer of artificial intelligence 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 an effective machine-learning solution that helps to interconnect the data and predicted outcomes, and define the key results for smarter decision-making. The model is based on the principle that past behavior is a good predictor of future behavior.
The development of a propensity models 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 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.
It works by pulling in real-time data from various sources across the organization and analyzing this against historical data and seasonal insights. It helps anticipate market changes and missed assumptions or future outcomes that are critical to make business-wide decisions.
Predictive Data Analytics in Action
Predictive data analytics is essential 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 organizations use predictive data models to identify which customers are most likely to file a claim. And retailers use propensity models to identify which customers are most likely to purchase.
The role of predictive intelligence is high as it helps organizations compete in a dynamic market and achieve their business goals in the short and long term. And, most importantly, it helps reduce risks and save resources.
Predictive intelligence is a rapidly growing smart technique that makes businesses more efficient, effective and successful. Many businesses use 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.
Put It Forward is a predictive data analytics platform that helps organizations to understand customers’ true intent as well as their propensity to act. By leveraging this platform, business leaders can transform decision-making and modeling ,and deliver hyper-personalized experiences.