1. A computer-implemented method, comprising: for each purchase-related electronic message in a group of purchase-related electronic messages selected from a collection of electronic messages transmitted between network nodes and stored in a first networked non-transitory computer-readable memory, segmenting, by a processor, contents of the electronic message into tokens; matching the electronic message to one of multiple clusters of purchase-related electronic messages, wherein each cluster is associated with a respective grammar that recursively defines a respective allowable arrangement of tokens corresponding to structural elements of the electronic messages in the matched cluster; parsing, by a processor, the tokens segmented from the electronic message in accordance with the grammar associated with the cluster matched to the electronic message, wherein the parsing comprises identifying the tokens segmented from the electronic message that correspond to respective structural elements defined in the grammar and extracting unidentified tokens segmented from the electronic message as field tokens; determining classification features from the tokens corresponding to structural elements of the electronic messages in the matched cluster; classifying, by at least one machine learning classifier, the extracted field tokens with respective product purchase relevant labels based on the determined classification features; storing associations between the product purchase relevant labels and the respective extracted field tokens as aggregated data in a second networked non-transitory computer-readable memory; and transmitting data for displaying a view based on the aggregated data on a client network node.