1. A computer-implemented method for developing an advertiser-specific behavioral lift model, the method executed by a computer system having a processor and a data store and comprising: maintaining, by the processor, in the data store a plurality of behavior profiles, each behavior profile including a persistent identifier and a plurality of behavior vectors for the persistent identifier, the behavior vectors indicating occurrences of each of a set of behaviors associated with the persistent identifier, each occurrence having a date; receiving, by the processor, conversion information relating to an advertiser associated with the plurality of behavior profiles, the conversion information indicating responses to an advertisement of the advertiser, the responses associated with user profiles; calculating by the processor a sequence of behavior tuples based upon the behavioral vectors and the conversion information, the calculated sequence including a first position and a last position, the calculation of the sequence of behavior tuples including: identifying, by the processor, a population of behavior profiles for each position in the sequence proceeding from the first position to the last position, the population associated with every position excluding behavior profiles that include behavior vectors indicating occurrences of any behavior tuple associated with any previous position in the sequence between the given position and the first behavior tuple in the sequence; and selecting, by the processor, a behavior tuple for each position in the sequence based on a lift for the behavior tuple relative to the population of behavior profiles identified for the position, the lift calculated relative to the conversion information; and storing in the data store, by the processor, the sequence of behavior tuples as an advertiser-specific behavioral lift model.