Abstract: A sender holds a first platform account with an interaction system. The sender selects a content item to be shared with a recipient. In response to determining that a recipient identifier of the recipient is not linked to a platform account, an off-platform communication is transmitted to a second user device associated with the recipient identifier. The off-platform communication is in an electronic format supported by the second user device and contains a user-selectable registration link. In response to detecting establishment of a second platform account linked to the recipient identifier, the recipient is enabled to access the content item on the second user device via a user interface provided by an interaction application. A relationship between the first platform account and the second platform account is established within the interaction system.

Abstract: A sender holds a first platform account with an interaction system. The sender selects a content item to be shared with a recipient. In response to determining that a recipient identifier of the recipient is not linked to a platform account, an off-platform communication is transmitted to a second user device associated with the recipient identifier. The off-platform communication is in an electronic format supported by the second user device and contains a user-selectable registration link. In response to detecting establishment of a second platform account linked to the recipient identifier, the recipient is enabled to access the content item on the second user device via a user interface provided by an interaction application. A relationship between the first platform account and the second platform account is established within the interaction system.

Abstract: Highly user-specific data is used to calculate user intent to make a purchase and the value of such a purchase. User activity and information is aggregated, per user, for a set window of time and real-time data on recent site behavior is obtained. Aggregated and/or real-time data is considered by a predictive intent model (calculating the probability that the user will make a purchase) and a predictive value model (calculating the expected revenue such a purchase may generate). Weights, specific to each model, are assigned to predictor features tracked in the aggregated and/or real-time user data. The most highly-weighted features of the intent model relate to users' viewing history, and the most highly-weighted features of the value model relate to price and market. By these means, a user conversion value can be obtained, guiding the application of user acquisition strategies for different home sharing markets.

Abstract: Highly user-specific data is used to calculate user intent to make a purchase and the value of such a purchase. User activity and information is aggregated, per user, for a set window of time and real-time data on recent site behavior is obtained. Aggregated and/or real-time data is considered by a predictive intent model (calculating the probability that the user will make a purchase) and a predictive value model (calculating the expected revenue such a purchase may generate). Weights, specific to each model, are assigned to predictor features tracked in the aggregated and/or real-time user data. The most highly-weighted features of the intent model relate to users' viewing history, and the most highly-weighted features of the value model relate to price and market. By these means, a user conversion value can be obtained, guiding the application of user acquisition strategies for different home sharing markets.

Abstract: Systems and methods are provided for providing personalized content based on interest levels determined using machine learning. An online marketplace system determines an interest profile for a client user using profile data of the client user as input into an interest extraction model. The online marketplace system selects a content item for the client user based on the interest profile and causes presentation of the content item to the client user via a channel that is separate from the online marketplace system. In response to receiving a request to access the online marketplace system originated from the content item, the online marketplace system selects product recommendations based on interest profile and the content item. The online marketplace system generates a personalized landing webpage including the product recommendations and causes presentation of the personalized landing webpage to the client user.