Abstract: In embodiments of identifying the end of an on-line cart session, an analytics application captures user click inputs on pages of a Web site, where the user click inputs include adding one or more items for purchase to an on-line cart associated with the Web site. The analytics application then utilizes a predictive model, as well as user and session features of the on-line cart session, to predict whether a previous user click input is the last user click input associated with the on-line cart session, indicating an end of the session. A notification can then be provided that the on-line cart session has ended based on the prediction of the last user click input associated with the on-line cart session. The analytics application or the marketer can then retarget a user associated with the on-line cart session, such as with a message pertaining to the on-line cart session.

Abstract: This document describes techniques for identifying suggestive intent in social posts. In one or more implementations, a topic is received and social posts to one or more social networks that are related to the topic are collected. Then, one or more suggestive intent posts expressing suggestions towards the topic are identified from the collected social posts. In one or more implementations, a set of related topics are received and social posts to one or more social networks that correspond to the related topics are collected. Then, aspects corresponding to the related topics are identified, and a sentiment score is generated for each aspect of each related topic that can be used to compare aspects of the related topics. In one or more implementations a suggestive intent model, usable to identify social posts expressing suggestive intent, is built from a training corpus of annotated social posts.

Abstract: This document describes techniques for identifying suggestive intent in social posts. In one or more implementations, a topic is received and social posts to one or more social networks that are related to the topic are collected. Then, one or more suggestive intent posts expressing suggestions towards the topic are identified from the collected social posts. In one or more implementations, a set of related topics are received and social posts to one or more social networks that correspond to the related topics are collected. Then, aspects corresponding to the related topics are identified, and a sentiment score is generated for each aspect of each related topic that can be used to compare aspects of the related topics. In one or more implementations a suggestive intent model, usable to identify social posts expressing suggestive intent, is built from a training corpus of annotated social posts.

Abstract: This document describes techniques for identifying purchase intent in social posts. In one or more implementations, a topic is received and social posts to one or more social networks that are related to the topic are collected. Then, one or more purchase intent posts expressing purchase intent towards the topic are identified from the collected social posts. In one or more implementations a purchase intent model, usable to identify social posts expressing purchase intent, is built from a training corpus of annotated social posts.