Abstract: A system, a machine-readable storage medium storing instructions, and a computer-implemented method are described herein for a Potential Consumer Engine identifies profile data of a target member account accessible in a social network service during a period of time equal in length to a pre-submission time period. The Potential Consumer Engine identifies channel data and assembles feature vector data for the target member account. The Potential Consumer Engine inputs into generalized linear mix model the feature vector data. The Potential Consumer Engine receives predictive output from the generalized linear mix model. The predictive output indicative of a current probability of the target member account joining the freelancer marketplace.

Abstract: Techniques for searching for generating and using an online activity index for users of an online service are disclosed herein. In some example embodiments, for each one of a plurality of dimensions of online activity for an online service, the system determines a corresponding value for each one of a set of one or more activities corresponding to the dimension for a user of the online service, with the value representing a level of engagement by the user in the corresponding activity via the online service. The system generates a corresponding activity index for each one of the dimensions based on the corresponding value for each one of the set of one or more activities corresponding to the dimension. The system generates content based on the corresponding activity index of at least one of the dimensions, and causes the content to be displayed on a device associated with the user.

Abstract: Techniques for searching for generating and using an online activity index for users of an online service are disclosed herein. In some example embodiments, for each one of a plurality of dimensions of online activity for an online service, the system determines a corresponding value for each one of a set of one or more activities corresponding to the dimension for a user of the online service, with the value representing a level of engagement by the user in the corresponding activity via the online service. The system generates a corresponding activity index for each one of the dimensions based on the corresponding value for each one of the set of one or more activities corresponding to the dimension. The system generates content based on the corresponding activity index of at least one of the dimensions, and causes the content to be displayed on a device associated with the user.

Abstract: A system, a machine-readable storage medium storing instructions, and a computer-implemented method are described herein for a Potential Consumer Engine identifies profile data of a target member account accessible in a social network service during a period of time equal in length to a pre-submission time period. The Potential Consumer Engine identifies channel data and assembles feature vector data for the target member account. The Potential Consumer Engine inputs into generalized linear mix model the feature vector data. The Potential Consumer Engine receives predictive output from the generalized linear mix model. The predictive output indicative of a current probability of the target member account joining the freelancer marketplace.

Abstract: A system, a machine-readable storage medium storing instructions, and a computer-implemented method are described herein for a Classification Engine for identifying, according to encoded rules of a plurality of service models, at least one type of service offered by a target member account of a social network service. The Classification Engine classifies, according to encoded rules of a freelancer inference model, the target member account as a freelancer account. The Classification Engine sends an invitation to the freelancer account to join a freelance marketplace within the social network service. The freelance marketplace includes various consumer accounts requesting to purchase a performance various types of services and specialties.