Abstract: Provided are methods and systems for optimization and personalization of marketing actions using cloud, hybrid, and quantum-based computing techniques. An example method commences with iteratively selecting, from a pool of prospective clients, at least one subgroup of the prospective clients based on predetermined criteria. The method further includes performing at least one marketing action on the at least one subgroup of the prospective clients. The method then continues with receiving a feedback from a prospective client belonging to the at least one subgroup of the prospective clients in response to the at least one marketing action. The method further includes scoring, by a machine learning technique, the feedback received from the prospective client. The method further includes modifying the at least one marketing action until the at least one marketing action is optimized for the prospective client based on the scoring of the feedback.

Abstract: Provided are methods and systems for optimization and personalization of existing communication channels. An example method commences with aggregating user data received from a plurality of data sources and creating a user profile for a user associated with the user data. The method includes creating a business logic for user interactions of the user via the existing communication channels. The business logic includes trigger conditions and actions corresponding to the trigger conditions. The method continues with mapping, using a recommendation algorithm, content to the user according to the business logic. The content is templatized to create personalized communication messages for the existing communication channels. The method includes receiving feedback data in response to the user interactions with the personalized communication messages.