Abstract: Described herein is a social media engagement engine. In accordance with another aspect of the framework, a social media message from a person (e.g., customer, prospect) is received via a social media data connector plugged into a social media interface. The social media message may be analyzed to generate processed data. At least one predefined rule is identified based on the processed data. The framework then facilitates engagement with the person according to the predefined rule.

Abstract: Described herein is a social media engagement engine. In accordance with another aspect of the framework, a social media message from a person (e.g., customer, prospect) is received via a social media data connector plugged into a social media interface. The social media message may be analyzed to generate processed data. At least one predefined rule is identified based on the processed data. The framework then facilitates engagement with the person according to the predefined rule.

Abstract: A method for predictive network congestion control may include receiving network traffic data of a network. The network traffic data may be indicative of a current level of use or the network. A predicted future level of use at the location of the network may be identified based on the received network traffic data and based on past network traffic data for the location of the network. A recommendation to alter the future level of use for the location may be generated. The recommendation may include a type of alert to transmit to devices of users in the location of the network. The recommendation may be transmitted to a network policy management server of the network.

Abstract: Techniques for providing social networking based offers, including identifying a particular user that is a customer of a service provider; identifying one or more other users that are socially connected to the particular user through at least one social network; generating, by the service provider, a master social plan for the particular user and a subset of the one or more other users, the master social plan identifying a business model between (i) each of the particular user and the subset of the one or more other users and (ii) the service provider; and providing an offer associated with the master social plan to the subset of the one or more other users.

Abstract: A system and method includes determination of an offer and a first customer, provision of the offer to the first customer, reception of an indication of a redemption of the offer by a second customer, identification of the first customer based on the indication, calculation, in response to identifying the first customer, of a referral value of the first customer based on the indication, and determination of a second offer to provide to the first customer based on the referral value.

Abstract: A method for predictive network congestion control may include receiving network traffic data of a network. The network traffic data may be indicative of a current level of use or the network. A predicted future level of use at the location of the network may be identified based on the received network traffic data and based on past network traffic data for the location of the network. A recommendation to alter the future level of use for the location may be generated. The recommendation may include a type of alert to transmit to devices of users in the location of the network.

Abstract: An interaction event associated with a customer is received by a real-time loyalty management engine executing on at least one data processor from an application. Thereafter, the engine retrieves data responsive to the interaction event that characterizes at least one loyalty program associated with the customer and a plurality of offerings. Next, the engine determines which of the offerings is most likely to result in an optimal conversion event based on the data characterizing the at least one loyalty program. The engine then transmits data to the application characterizing the determined offering to enable a transaction to be initiated based on the determined offering. Related apparatus, systems, techniques and articles are also described.

Abstract: A computer-implemented method for processing options requests includes: storing, in a first system, static information regarding subscriptions by customers, the static information including at least customer names and product identifiers; storing, in a second system separate from the first system, flexible information regarding the subscriptions including at least activated options; and processing requests from the customers regarding options in the second system, wherein the first system and the static information are not used in processing the requests.

Abstract: A computer-implemented method for processing options requests includes: storing, in a first system, static information regarding subscriptions by customers, the static information including at least customer names and product identifiers; storing, in a second system separate from the first system, flexible information regarding the subscriptions including at least activated options; and processing requests from the customers regarding options in the second system, wherein the first system and the static information are not used in processing the requests.