Abstract: A computer-implemented method includes identifying a first set of members on a social network, each member of the first set of members includes a class value comprising one of a positive member and a negative member, each positive member is associated with a target offering, determining a skillset of each member of the first set of members, training a first model based on the class value and skillset of each member of the first set of members, the first model configured to generate at least one of a classification value and a prospect score for a prospect member based on a prospect member skillset, computing a prospect score for the prospect member using the first model and the prospect member skillset, and providing the at least one of a classification value and a prospect score for use in evaluating the prospect member in relation to the target offering.

Abstract: A machine may be configured to determine a predicted share of an online advertising budget to be spent by a company on a marketing product or service provided by a social networking service, in a period of time. For example, the machine performs a revenue prediction modeling process to generate a revenue-per-employee value that represents a predicted revenue amount per employee of a company for a period of time. The machine performs an advertising spend prediction modeling process to generate an advertising-per-employee value that represents a predicted online advertising spending amount per employee of the company in the period of time. The machine performs a share prediction modeling process to generate a sales-per-employee value that represents a predicted share of the advertising-per-employee value to be spent by the company on a marketing product or service provided by a social networking service, in the period of time.