ROAS Master
A web application designed to help businesses calculate and improve their Return on Advertising Spend (ROAS) with actionable insights and growth strategies.
Project Overview
ROASMaster is a user-friendly web application that empowers businesses to optimize their advertising strategies by accurately calculating their ROAS and suggesting actionable steps to improve it. The app provides a clear understanding of advertising efficiency, enabling data-driven decision-making.
Key Features
- ROAS Calculator:
- Users can input their revenue and cost to calculate the current ROAS.
- Real-time calculations and instant feedback for improved usability.
- Improvement Suggestions:
- Fully bilingual platform with English and French versions.
- Incremental improvement suggestions in percentage form, helping users meet their goals within a defined timeframe.
- Future Insights:
- Planned implementation of predictive analysis using machine learning to anticipate future ROAS based on past data.
Design Approach
- Minimalist and Intuitive: Designed with simplicity in mind to make calculations and insights accessible to users without a steep learning curve..
- Responsive Design: Fully responsive, ensuring usability across devices and screen sizes.
- Color Palette: A professional and clean UI with modern design elements.
Tech Stack
- Frontend: Developed with Next.js for optimized performance and TypeScript for enhanced type safety.
- Styling: Tailwind CSS for rapid UI development and design consistency.
- Hosting: Deployed on Vercel for fast and reliable global access.
My Role
- Conceptualized and developed the app from scratch.
- Designed the UI and integrated the core ROAS calculation logic.
- Focused on delivering a seamless and engaging user experience.
Planned Enhancements
- Predictive ROAS Analysis:
- Incorporated components from ShadCN/UI and Aceternity UI to save development time and maintain design consistency.
- Generation of data sets using solver algorithms like A* for more accurate predictions.
- Advanced Suggestions:
- Dynamic recommendations tailored to user-specific data trends.
- Scenario-based forecasting for strategic planning.
- Source Code Available on GitHub.
Conclusion
This project allowed me to merge business logic with technical implementation, enhancing my ability to create tools that provide real value to users. Through ROASMaster, I explored the intersection of analytics, user experience, and cutting-edge web technologies.