1. A computer-implemented method, comprising: determining at least one offer from at least one seller to at least one buyer, wherein the at least one seller and at least one buyer are parties to at least one current transaction and wherein the determining at least one offer comprises: determining, by a computer system, a demand for at least one offering from the at least one seller, wherein the demand is calculated based, at least in part, on: 1) at least one transaction composite, 2) at least one product preference function, wherein the at least one product preference function is based at least in part on: i) a plurality of offerings, ii) a price of each offering from the plurality of offerings, iii) a transaction composite class of the at least one transaction composite, wherein the at least one at least one transaction composite comprises: i) at least one seller profile having at least one seller statistical score, wherein the at least one seller profile is independent from the transaction data for the at least one current transaction, ii) at least one buyer profile having at least one buyer statistical score, wherein the at least one buyer profile is independent from the transaction data for the at least one current transaction, and iii) transaction data for the at least one current transaction; wherein the at least one product preference function determines at least one ranked subset of offerings from the plurality of offerings, wherein the at least one ranked subset of offerings identifies a purchasing probability for each offering from the at least one ranked subset of offerings when each offering is being offered with at least one other offering from the at least one ranked subset of offerings, and wherein the at least one product preference function evaluates the purchasing probability of each offering from the at least one ranked subset of offerings based, at least in part, on at least one relationship between the price of each offering in the at least one ranked subset of offerings and the purchasing probability of each offering from the at least one ranked subset of offerings, and 3) at least one price sensitivity function, wherein the at least one price sensitivity function is based at least in part on: i) the at least one ranked subset from the plurality of offerings, ii) the price and the purchasing probability of each offering from at least one ranked subset, iii) the transaction composite class of the at least one transaction composite, wherein the at least one price sensitivity function determines the at least one relationship between the price of each offering from the at least one ranked subset of offerings and the purchasing probability of each offering from the at least one ranked subset of offerings; calculating, by the computer system, a supply prediction for the at least one offering, wherein the supply prediction is determined based at least in part on: i) historical demand data indicating previous fulfillment of the at least one offering, ii) current demand data indicating at least one received but unfulfilled order availability of the at least one offering, and iii) capacity limit for fulfilling orders for the at least one offering; calculating, by the computer system, a revenue prediction, wherein the revenue prediction determines a maximum expected revenue based at least on the determined demand for the at least one offering and the supply prediction for the at least one offering; and providing the at least one offer to the at least one buyer based, at least in part, on: (1) the determined demand for the at least one offering, (2) the calculated supply prediction, and (3) the calculated revenue prediction.