Price Optimization Algorithm for Small Online Retailers
The problem with smaller businesses using online commerce, is that larger companies have the funds to make their goods cheaper, usually due to wholesale purchases. However, the smaller companies may not be able to have the overhead to supply goods at such a low price without a guarantee of a return. In order for the smaller businesses to have a higher return, they would have to make the prices of their goods look more attractive than those of larger companies. On the other hand, it would be difficult for a company to perform research to determine the competitive prices of all of the other, larger businesses.
What Boomerang Commerce seeks to do, is perform analyses of prices of like goods that other businesses are selling, in order to determine the optimal price to sell at, considering different conditions. For example, sellers can choose to use the best price to optimize for revenue, margin, or customer lifetime value. Being able to change prices of goods with real-time analysis and comparisons is very beneficial, in that other retailers only change their prices every three months. This ability to change prices more often can singlehandedly give smaller businesses the advantage they need to build a customer base, and from there, increase their revenue and profits.
This algorithm corresponds to game theory in that the seller can adjust their prices in order to more successfully compete with other companies. A problem with game theory however, is that the method of measuring value may be different for each business. For example, some retailers may value a large customer base over a large profit. This algorithm seeks to address these issues by utilizing its various optimizations, in order to maximize, what is to the seller, the highest value benefits. Thus, the companies that use this can always eventually gain an edge over competition.