SPENDING ALLOCATION IN MULTI-CHANNEL DIGITAL MARKETING

• Main Authors: CHARAFEDDINE Mohamad, KATHALAGIRI SOMASHEKARIAH Girish, SRINIVASA Sunil, QUINTELA Luis, BELOI Aleksander, MISHRA Abhishek
• Format: Patent
• Language: English
• Published: 15.02.2018
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; PHYSICS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

An approach for spending allocation, executed by one or more processors to provide one or more monetary output values in response to a request for determining spending allocation in a digital marketing channel, is provided. The approach fits one or more models to train a business environment simulator. The approach generates a supervised learning policy. The approach evolves a supervised learning policy into a distribution estimator policy by adjusting network weights of the supervised learning policy. The approach generates an optimized policy by evolving the distribution estimator policy through interaction with the business environment simulator. The approach determines a profit uplift of the optimized policy by comparing the optimized policy and the supervised learning policy. Further, in response to the optimized policy outperforming the supervised learning policy, the approach deploys the optimized policy in a live environment.