This study proposes a similar product discovery algorithm for firms engaged in sales and delivery business alliances. Allied firms must share a product classification scheme and define product information that is mutually interchangeable for cross-selling among the firms. The key idea of the algorithm presented in this study is to calculate the range of aggregated utility values for the specification values of products belonging to the same classification level across the products held by the allied firms, and to discover similar products based on the utility ranges of those products. To verify the applicability of this algorithm, a user satisfaction experiment was conducted and its results were presented. The results were compared with user satisfaction from a recommendation algorithm based on distance measures, which is a traditional similarity discovery methodology. Through this experiment, it was confirmed that the proposed algorithm can be utilized as a solution for recommending similar products when the buyer's residence and the recipient's residence differ, and when the buyer possesses only incomplete information regarding the importance of product specifications.