Apigee has announced a new version of Insights, the company’s big data predictive analytics platform that enables enterprises to deliver API-powered predictive apps that individualize each interaction by applying real-time predictive analytics using fine grained customer, product interaction, and machine data.
Insights is optimized to work with fine-grained, unstructured, and semi-structured data. Insights pays special attention to individual interactions, each web click, each page visited, each product viewed, each product purchased, along with relevant unstructured and semi-structured data such as agent notes, tweets, searches and reviews, and relevant context for each of those interactions.
When viewed in isolation, each of these data points doesn’t tell provide relevant information. When viewed with analytics and machine learning, individualized interactions become accessible and predictable.
Insights is designed to work with real-time data. Insights is integrated with Apigee Edge, and provides visibility into user actions as they occur on web, mobile, and other emerging channels.
Insights is tightly integrated with Hadoop and provides predictive intelligence to translate into insight data enterprises are aggregating in their data lakes and data warehouses. It enables enterprises to use the insights gleaned from predictive and advanced analytics to optimize their APIs and adapt their apps. For example, enterprises can dynamically change the behavior of their apps to deliver the optimal offer, recommendation, or experience for that individual.
It automatically uses feedback from customers, such as offers accepted or rejected, to validate predictions, which enhances the predictive models so each experience is fresh and relevant.
With Insights, enterprises can precisely target each customer, offer them individualized recommendations, and proactively serve their needs. The end result is accelerated business growth and stronger customer relationships.