1. A computer-based method of scoring recommendations for potential purchase by a customer, comprising: receiving a recommendation context from a customer; using the recommendation context to identify a plurality of candidate recommendations that match the recommendation context, where each candidate recommendation recommends at least one recommended item; with a computer system, determining a score for each candidate recommendation by subtracting a first expected margin value factor for the recommended item that is based on the candidate recommendation not being displayed from a second expected margin value factor for the recommended item that is based on the candidate recommendation being displayed; and ranking the plurality of candidate recommendations using the score for each candidate recommendation to identify at least a highest ranking candidate recommendation.
1. A computer-based method of scoring recommendations for potential purchase by a customer, comprising: receiving a recommendation context from a customer; using the recommendation context to identify a plurality of candidate recommendations that match the recommendation context, where each candidate recommendation recommends at least one recommended item; with a computer system, determining a score for each candidate recommendation by subtracting a first expected margin value factor for the recommended item that is based on the candidate recommendation not being displayed from a second expected margin value factor for the recommended item that is based on the candidate recommendation being displayed; and ranking the plurality of candidate recommendations using the score for each candidate recommendation to identify at least a highest ranking candidate recommendation. 7. The method of claim 1 , where the second expected margin value factor is calculated by multiplying a margin value factor for the recommended item by the probability that the recommended item will be purchased if the candidate recommendation is displayed.