The Analysis report proposes a solution that grants businesses complete visibility into their inventory and streamlines sales operations from the distribution center to the store. It is used to determine the balance of existing materials when it is demanded to know the stock balance, control the levels of materials, and daily movement of the materials. Data is gathered from the web application and processed to form a group of charts called a dashboard. This dashboard helps to analyze the sales and performance of every product report. Analysis report deals with the organization’s requirements, performance analysis, sales, and financial problems, and solving them, in addition, to saving all the materials information, and process in a private system database. The quality of wood used in the furniture and performance analysis of furniture based on design are represented in form of charts for a better understanding of the user. Admin can view their financial and sales reports by daily, weekly, monthly, and yearly trends. This Furniture Web Application System is created for the convenience of the customers, of this specific shop. It is not only for users but also convenient for the owner to sell their products online along with analytics reports using machine learning techniques. To analyze reports, the system uses Support Vector Machine (SVM), a supervised machine learning technique. Keywords—furniture, machine learning, analysis report