Prestige Finds a Perfect Machine Learning Solution to Predict Sales and Boost ROI Accurately
About
Established in 1990, the client is a worldwide leader in procuring and selling metalworking machinery, fabricating equipment, and complete manufacturing facilities. It provides online and on-site auctions and liquidations, asset management programs, appraisals, financing, plant turnaround, and business sales. As a full-service stocking dealer, it offers an extensive inventory and consignment selection of more than 1,000 late-model machine tools. They wanted to introduce an advanced machine learning system to predict sales and help them boost ROI.
Project Highlights
The product uses advanced machine learning models to accurately predict future sales based on the previous year’s sales and current market trends. It aims to improve the organization’s operational working and enhance user experience by optimizing marketing effects and reducing bounce rates. The system collects data, runs through, analyzes, and produces accurate results without compromising performance. It also allows a graphical view of the data.
The Challenges
- Sales Forecast:Accurately predicting future sales based on historical data, market trends, and other factors.
- Downtimes Affecting User Experience:Hindered user experience and growth due to slow response times and occasional downtimes.
- Codebase Optimization:Need to optimize the codebase to enhance performance without compromising functionality.
- Inefficient Resource Allocation:The old ML model is not delivering the desired accuracy, leading to inefficient resource allocation.
Tech Stack
CSS 3
JavaScript
Python
HTML
MySQL
Django
Azure DevOps
Azure Board
Result
Accurate Sales Forecasting
The machine learning sales prediction model implementation resulted in achieving several outcomes. The business witnessed more optimized marketing campaigns, better inventory management, effective resource allocation, and ROI measurement, accurate sales forecasting and strategic insights, and reduced financial uncertainties. All of this gave the client an edge over the competition.Enhance User Experience
The client achieved notable outcomes by implementing the Scalability and Performance Optimization strategy. Faster response times and improved performance enhanced user experience, reduced bounce rates, and increased user engagement. Enhanced scalability also allowed handling higher user loads and traffic spikes without downtimes or slowdowns, accommodating business growth and attracting more users.Reduced Bounce rates
Code Optimization strategy implementation helped improve the application’s performance significantly, resulting in faster response times and a smoother user experience. Reduced resource consumption promoted cost savings. Efficient memory use and processing power allowed for handling larger user loads and data volumes, increasing user satisfaction, reduced bounce rates, and higher user engagement.Increase in the Projected Revenue
Improved model accuracy resulted in reliable sales predictions. It encouraged better decision-making, optimized resource allocation, and increased confidence in the projected revenue. It made the project a valuable tool for strategic planning and achieving business goals and helped boost business growth.
