1. A computer-implemented method for providing promotion recommendations based on electronic promotion transactions performed by consumer devices using a promotion and marketing service, the method comprising: determining, via processing circuitry, a plurality of promotion clusters from electronic transaction data stored in a memory, the electronic transaction data indicating at least one electronic transaction performed by a consumer device, wherein each promotion cluster of the plurality of promotion clusters comprises at least three promotions; dynamically in response to a promotion recommendation inquiry, determining, via the processing circuitry, one or more correlation metrics for each promotion cluster of the plurality of promotion clusters, the one or more correlation metrics for each promotion cluster indicative of a relationship between a selected promotion of the promotion cluster and a selected pair comprising a first promotion and second promotion of the promotion cluster, wherein the relationship represents a programmatically generated likelihood that a consumer will purchase the selected promotion of the promotion cluster if the consumer purchases both the first promotion and the second promotion of the promotion cluster; storing, by the processing circuitry, the one or more correlation metrics in the memory; generating, by the processing circuitry, at least one promotion recommendation based at least in part on the one or more correlation metrics; filtering, via processing circuitry, the at least one promotion recommendation based on a determination as to whether the at least one promotion recommendation is valid; in response to determining that the at least one promotion recommendation is valid, generating, via the processing circuitry, an electronic marketing communication comprising the at least one promotion recommendation; and transmitting, via communications circuitry, the electronic marketing communication to a consumer device; wherein a correlation metric of the one or more correlation metrics is one of a support metric representing a programmatically generated success rate associated with a promotion in turning promotion views into purchases, a confidence metric representing a programmatically generated strength of the relationship between the selected promotion and the selected pair of the promotion cluster, a lift metric representing a programmatically generated likelihood that a consumer will purchase all three promotions of a promotion cluster by adding the selected promotion to the promotion cluster, or a coverage metric representing a programmatically generated measurement of a number of times an individual consumer purchased each of the three promotions of the promotion cluster.