American Express Travel Related Services Company, Inc.

Hector Flores

Yogaraj Jayaprakasam

Jordan Meyerowitz

Srinivas K Kumandan

Abhishek Jain

Robin Jain

Systems and methods for optimizing user task schedules in a customer relationship management (CRM) platform is disclosed. In one example, a system comprising a computing device and a cache. The computing device is configured to generate child user task schedules and calculate task win probabilities of tasks for the child user task schedules using a machine learning system. The machine learning system is used to determine the plurality of task win probabilities. The computing device is also configured to calculate total task win probabilities for the child user task schedules based on the task win probabilities and is configured to determine an optimized user task schedule by selecting a respective user task schedule having a greatest total task win probability from a subset of the plurality of child user task schedules stored in the distributed cache.

Optimizing user task schedules in a customer relationship management platform

Systems and methods for optimizing user task schedules in a customer relationship management (CRM) platform is disclosed. The system may optimally input tasks into time slots in a user schedule to generate the optimized user task schedule. The system may generate a plurality of user task schedules and calculate a total task win probability for each of the user task schedules. The system may comprise the total task win probabilities and select the user task schedule having the greatest total task win probability. The system may also perform a genetic processing analysis of the user task schedules to further optimize task placement in the user task schedule.

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Phoenix, AZ, United States of America

Hector Flores