1. A computer-based method for predicting escalations, comprising: extracting an escalation feature from a webpage; running the escalation feature through a classifier; generating an escalation likelihood result from running the escalation feature through the classifier, the escalation likelihood result comprising at least one of: an estimation that a subsequent search query will comprise an escalation when compared to a previous search query; or an estimation that a subsequent webpage selection will comprise an escalation when compared to a previous webpage selection; and generating a resource utilization intent (RUI) likelihood result from running the escalation feature through the classifier, the RUI likelihood result comprising an estimation that a second subsequent search query will comprise a resource identification query, where a resource identified by the resource identification query comprises at least one of a service or a good related to a prior search query.
1. A computer-based method for predicting escalations, comprising: extracting an escalation feature from a webpage; running the escalation feature through a classifier; generating an escalation likelihood result from running the escalation feature through the classifier, the escalation likelihood result comprising at least one of: an estimation that a subsequent search query will comprise an escalation when compared to a previous search query; or an estimation that a subsequent webpage selection will comprise an escalation when compared to a previous webpage selection; and generating a resource utilization intent (RUI) likelihood result from running the escalation feature through the classifier, the RUI likelihood result comprising an estimation that a second subsequent search query will comprise a resource identification query, where a resource identified by the resource identification query comprises at least one of a service or a good related to a prior search query. 8. The method of claim 1 , comprising extracting a second escalation feature from a user session history and running the second escalation feature through the classifier to generate at least one of a second escalation likelihood result or a second RUI likelihood result.