METHODS AND SYSTEMS FOR TRANSFORMING COMPUTING ANALYTICS FRAMEWORKS INTO CROSS-PLATFORM REAL-TIME DECISION-MAKING SYSTEMS THAT OPTIMIZE CONFIGURABLE GOAL METRICS

摘要

Systems described herein provide structures and functionality for transforming passive analytics systems into systems that can actively modify software behavior based on analytic data to improve software performance relative to configurable goal metrics. An example method generally includes generating a decision-making policy representing logic learned by a machine-learning model from time-series data collected for sessions of a software application; deploying the decision-making policy; receiving a decision-making request originating from the software application including a consumer identifier and a decision-point type; retrieving time-series data in a session associated with the consumer identifier; selecting actions for the software application to perform by comparing the time-series data and the event type to the decision-making policy; sending an indication of the selected actions in response to the decision-making request; and updating data in the session associated with the consumer identifier to reflect the decision-point event and the one or more selected actions.