Abstract: Provided herein are exemplary embodiments including a computer-implemented method of using artificial intelligence for automatically collecting and enriching network data for a smart campaign with autopilot features. The method includes, collecting a set of network data relevant to a smart campaign with autopilot features, applying one or more transformations to the collected set of data to create a modified set of data, generating from the modified set of data, enriched network data for a smart campaign with autopilot features, the enriched network data having content, context and event data, and using the enriched data to deploy a personalized campaign by identifying an audience, time, channel, content and goal of the communication.

Abstract: Methods and systems are provided for communication of one or more campaigns via personalized electronic messaging. An example method includes automatically creating an electronic communication personalized for each of a plurality of individual customers of a client. The automatically creating may include dynamic configuring the electronic communication for each individual customer into a single campaign for the client to optimize both relevancy for each of a plurality of individual customers and one or more desired business outcomes for the client. The dynamic configuring can include decision making using at least a business context. Performance goals of a business can comprise the business context. The decision-making can further use a user context and/or an external context. The electronic communication can be dynamically configured to include personalized recommendations and may further include personalized content and/or a personalized offer.

Abstract: Exemplary embodiments include a reinforcement learning model configured at a given point in time to receive digital data about a state of a user at the given point in time, receive digital data about an environment at the given point in time, receive digital data about a campaign at the given point in time, optimize total expected future number of positive rewards at the given point in time, and to execute an action at the given point in time. The state of the user at the given point in time may be a number of communications the user has received in a particular time period, a time since a last communication, the user's past behavior, and/or the user's engagement score from a predictive model to engage with a communication.

Abstract: Methods and corresponding systems are provided for configuring communications to customers when there are multiple campaigns scheduled in a given period. An optimal number of communications are sent prioritized according to business or performance measures where send times are spaced out in a manner that strives to attain the highest value. An example method includes determining a number of electronic communications, for a plurality of campaigns to send to the particular customer during a particular time period; determining the optimal send time during the particular time period; determining for which campaigns the particular customer is eligible; for each determined optimal time: determining a strategy including selecting an electronic communication for one of the campaigns to send to the eligible particular customer so as to maximize the value over the particular time period; and causing the selected electronic communication to be sent to the particular customer at the determined optimal time.

Abstract: Methods and systems are provided for communication of one or more campaigns via personalized electronic messaging. An example method includes automatically creating an electronic communication personalized for each of a plurality of individual customers of a client. The automatically creating may include dynamic configuring the electronic communication for each individual customer into a single campaign for the client to optimize both relevancy for each of a plurality of individual customers and one or more desired business outcomes for the client. The dynamic configuring can include decision making using at least a business context. Performance goals of a business can comprise the business context. The decision-making can further use a user context and/or an external context. The electronic communication can be dynamically configured to include personalized recommendations and may further include personalized content and/or a personalized offer.

Abstract: Methods and corresponding systems are provided for configuring communications to customers when there are multiple campaigns scheduled in a given period. An optimal number of communications are sent prioritized according to business or performance measures where send times are spaced out in a manner that strives to attain the highest value. An example method includes determining a number of electronic communications, for a plurality of campaigns to send to the particular customer during a particular time period; determining the optimal send time during the particular time period; determining for which campaigns the particular customer is eligible; for each determined optimal time: determining a strategy including selecting an electronic communication for one of the campaigns to send to the eligible particular customer so as to maximize the value over the particular time period; and causing the selected electronic communication to be sent to the particular customer at the determined optimal time.