In this paper, we firstly introduce row-products of the soft matrices and investigate their properties and algebraic structures in detail. We aim to show that these row-products can be used in handling decision making problems. We therefore propose two new methods called a soft max-row decision making method and a multi-soft distributive max-min decision making method employing these operations. These methods are utilized to obtain an optimum choice when the decision makers evaluate the objects of disjoint universe sets according to the parameters during decision making. Also, we argue that the first of them can be employed to solve the decision problems handled in [6,16]. The second method that we propose to solve the decision problems involving multi-disjoint universe sets is a generalization of the soft decision method presented in . By constructing them, we pioneer the idea that the soft matrices can be used to deal with decision making involving the multi-disjoint universe sets, which it is shortly called a multiple-disjoint decision making. Moreover, we present the outstanding examples to verify the practicality and effectiveness of the emerging methods. Finally, we give Scilab codes for each step of our methods and put forward that these codes make the process of decision making faster and easier. (C) 2017 Elsevier B.V. All rights reserved.