REAL TIME SALES PRODUCTIVITY FORECASTING IN RETAIL ECOSYSTEMS THROUGH THE INTEGRATION OF CLOUD COMPUTING AND EDGE AI

Abstract

Today’s retail environment is rapidly changing. How customers buy products has changed, as have methods of distribution. It is more competitive. Traditional ways of assessing predicted sales are becoming outdated. We argue that more advanced predictive tools and models that assess the productivity of different types of sales are needed. There is a need to be more efficient to satisfy corporate profit needs and to be more competitive. Advanced predictive models that look at sales productivity can help assess how effective sales are based on the cost of labor and the available sales inventory. Our research shows that the introduction of Artificial Intelligence to retail sales tools can help predict sales and avoid lost sales due to a lack of inventory. There are a number of areas that present new problems, including selling products that are customer specific and making products that customers want to buy. We present new ways of thinking that will allow the customer to secure their information and allow the sale to take place. This research presents the most advanced hybrid Cloud and Edge Artificial Intelligence system. The model is the most advanced and gives the most competitive edge to sales.