Systems, methods, and applications for mobile intelligent outside sales assistance are provided. Embodiments include receiving speech for recognition of an outside sales call; converting the speech for recognition to text; parsing the converted text into outside sales triples; storing the outside sales triples in an enterprise knowledge graph of a semantic graph database; generating real-time outside sales insights in dependence upon the speech of the outside sales call and the stored outside triples in the enterprise knowledge graph; and presenting the real-time outside sales insights to an outside sales agent.

A social media platform is provided. The social media platform, Phaction, implements digital activism, social action, societal understanding and social issue conversation. Powered by information and data from various sources, such as Clarintel, Inc., and user generated content and internal research approaches, Phaction provides the user with an environment built on cloud-based products that redefine social action. Phaction allows clients to access tools that enhance social action approaches both individually and in groups, to track, manage, and organize all social impact, capital, and philanthropic opportunities, and engage in social action, empathy building, and truth sharing, and keep up with the rising demand for social action involvement, societal understanding, and social justice advocacy. Clarintel offers analytical measures, resources, and research materials that allows stakeholders to enhance their social impact, deepen their social issue research approaches and understanding, and increase the personal and external value of nonprofit and philanthropic involvement.

Described are a system, method, and computer program product for segmenting a plurality of accounts. The method includes processing transaction data for a plurality of transactions conducted by a plurality of accounts using a plurality of account identifiers, the transaction data for each transaction including data identifying the transaction as an electronic transaction or a physical transaction, segmenting the plurality of accounts into at least two groups including an active customer group and an inactive customer group based on the transaction data for each transaction conducted by each of the plurality of accounts, determining a third subset of customers from the second subset of customers based on at least one predicative model and a transaction profile of each customer of the second subset of customers, and automatically enrolling the third subset of customers into an automated campaign.

A smart card, including a card with EMV contacts, for determining a person's preferences and for providing services.

A system and method for determining market share of an organization. The method encompasses receiving, at least one of a voice of customer data, an internal data of the organization and an external data. The method thereafter leads to determining, one or more set of target features based on at least one of the voice of customer data, the internal data of the organization and the external data. Further the method comprises generating, one or more pre-trained dataset based at least on the one or more set of target features. The method thereafter encompasses receiving, at least one of a first set of feature constraints and a second set of feature constraints. Further the method comprises determining, the market share of the organization based at least on the one or more pre-trained dataset, the first set of feature constraints and the second set of feature constraints.

An embodiment for generating an electronic coupon based on user preferences is provided. The embodiment may include receiving real-time and historical data relating to one or more reward coupons. The embodiment may also include identifying a contextual situation of the user and one or more preferences of the user regarding a coupon reward type. The embodiment may further include identifying one or more vendors that match with the one or more preferences of the user. The embodiment may also include generating one or more electronic coupons and presenting the one or more generated electronic coupons to the user. The embodiment may further include in response to determining the one or more generated electronic coupons match at least one preference of the user, adding the one or more generated electronic coupons that match the at least one preference of the user to an account of the user.

Implementations of various methods and systems for creating and calculating a transportation capacity unit index and trading derivative products based thereon to transact and trade transportation seats or freight or transportation capacity units and resulting financial swap, futures, forwards and option structures in airline transport, subway transport, train transport, automobile transport, autonomous vehicle transport, taxi transport, space transport, package freight transport, tractor trailer freight transport, cargo freight transport, container freight transport, virtual transport, underground transport, ship or sea transport, public transport, private transport or drone transport on a computer, mobile computer device, audio computer device, virtual reality computer device or mixed reality computing device.

A Gamified Participatory Recommender System is disclosed which employs Content-based Art Recommendations which are combined with Collaborative Filtering Art Recommendations and are adjusted by the Participation Score of the Current User to identify Art similar to art that a Current User is viewing. The similar Art is displayed to the Current User, and the Current User's actions are monitored. Subsequent recommendations are adjusted based upon the Current User's actions. The System also employs Content-based User Recommendations which are combined with Collaborative Filtering User Recommendations that are adjusted by a Participation Score of the Current User to identify similar Users and create links between the Current User and at least one similar User. These recommendations are affected by the amount of user participation, thereby rewarding those with extensive user participation.

A system and method for predicting behavior and/or outcomes related to a consumer's experience with an organization are implemented. Household data for households that are associated with a customer service interaction as of a certain date is collected, the household data having been created over a first pre-determined period of time preceding the certain date. The household data is analyzed to identify positive household data sets and negative household data sets. The positive household data sets relate to customer service interactions which preceded a high level customer service interaction within a subsequent period of time and the negative household data sets relate to customer service transactions which did not precede a high level customer service interaction with the subsequent period of time. The positive household data sets and the negative household data sets are processed in the aggregate, using a trained support vector machine model, to determine cumulative differences between data contained within the positive household data sets and the negative household data sets. Each day, daily household data is collected. The daily household data describes individual customer service transactions occurring during a previous calendar day. The daily household data is processed using the model to determine whether each individual customer service transaction occurring during the previous calendar day is more similar to the positive household data sets or to the negative household data sets. The individual customer service transactions that are more similar to the positive household data sets are flagged for proactive intervention.

An online system, such as a social networking system, generates shared models for one or more clusters of categories. A shared model for a cluster is common to the categories assigned to the cluster. In this manner, the shared models are specific to the group of categories (e.g., selected content providers) in each cluster while requiring a reasonable computational complexity for the online system. The categories are clustered based on the performance of a model specific to a category on data for other categories.