Strategies to Selecting Most Profitable Products by Price Settings
Abstract
For a company, it is important to know which products to launch to the market that may get the maximal profit. To achieve this goal, companies not only need to consider these products’ features, but also need to analyze how customers make their purchase decisions. For most customers, the price of a product is the most important purchase factor. If the price of a product can be adjusted, the purchase decision of a customer may change. With different price settings, we can speculate on the expected number of customers and the profit of the products. Motivated by this, we want to find the most profitable products among the candidates for the company. A distance-based adoption model can be used to evaluate the expected customers for products at different prices. The computational cost is high in two parts. One is the computational cost of obtaining the most profitable information on each set of candidate products. Another part is that many candidate product combinations need to be calculated. To tackle the computation problem, we propose two strategies. One is to avoid considering all possible price settings. The other is to avoid processing all possible subsets of the candidate products. Experimental results reveal the efficiency of our strategies.
