Dress2Save is an online clothing price aggregator that helps users analyze historical price data of clothing items and find the moments when the items are on sale.
Dress2Save aggregates historical price data for different items of clothes available on the Internet. Users can monitor price fluctuations and see if the item is on sale or if it’s just another marketing campaign. Based on this data, users can find the items at a time when they are cheaper than usual. It also provides multiple useful filters to find the best discounts.
The project's biggest challenge is gathering all the necessary data daily, so we can use the data later to find the best available deals. We need to ensure that the data collection process is stable and scalable. Then we need to provide a front-end implementation with a user-friendly UI that will help portal users find the best offers and deals.
React Framework is used on a frontend to provide responsive functionality. Some parts of the project required Search Engine Optimizations. NextJS was added as a server-side rendering engine to provide the best SEO results. ExpressJS framework has been used for a backend. Multiple NodeJS web scrappers were added for daily data gathering processes. All the gathered data is stored in a simple MySQL database.
React-based app with server-side rendering capabilities has been implemented and deployed. Multiple web scrappers of popular websites have been deployed and scaled to collect the data daily and store it in our local database. The whole infrastructure has been deployed with the help of AWS and can be additionally scaled on-demand.