Retail price analytics using backpropogation neural network and sentimental analysis

One of the most important aspects of the marketing is to determine what price is to be fixed to sell your products. Pricing is both an art and science that requires an experimental and statistical formula for creating a profile for the brand and the product in the market. There are minimalistic approaches used for pricing the products and to consider what will work for your business. Neural networks are a computational approach which is more promising in making a better decision among large volume of data. Combination of Machine learning with neural networks forms a new dimension in decision making. Though, it provides more accuracy than regression techniques, they aren't able to keep up with the dynamic growth of the data. Thus, an additional technique is required to handle this dynamic growth. Henceforth, sentimental analysis and Neural networks are combined together in order to provide better precision in decision making. Here, Back propagation neural network classification algorithm is used to classify the data. This approach would be more efficient in decision making in perspective of selling the products.