7. A computer program product tangibly embodied in a computer-readable storage medium and comprising instructions that when executed by one or more processors perform a method for defining a segment based on interaction proneness, the method comprising: receiving online activity data that specifies instances of presentation for one or more content items, and instances of user interaction detected for any of the content items; training at least one predictive model on the online activity data, the predictive model trained to predict interaction proneness based on a cross product of two characteristics associated with the instances of user interaction; identifying, using the predictive model, the cross product as being associated with the interaction proneness; and generating at least one segment definition that takes into account the identified cross product.
7. A computer program product tangibly embodied in a computer-readable storage medium and comprising instructions that when executed by one or more processors perform a method for defining a segment based on interaction proneness, the method comprising: receiving online activity data that specifies instances of presentation for one or more content items, and instances of user interaction detected for any of the content items; training at least one predictive model on the online activity data, the predictive model trained to predict interaction proneness based on a cross product of two characteristics associated with the instances of user interaction; identifying, using the predictive model, the cross product as being associated with the interaction proneness; and generating at least one segment definition that takes into account the identified cross product. 8. The computer program product of claim 7 , wherein the identification involves determining a coefficient for the predictive model that reflects whether and how the instances of user interaction vary with the instances of presentation.