Audi Ribeirão Preto

Audi Ribeirão Preto
ReactNextjsTailwindTypescriptShadcn UINode.jsPostgreSQL

Institutional Website and Product Catalog

This platform was developed to offer a quick and intuitive car shopping experience for the Audi brand in Ribeirão Preto and the surrounding region, updating the dealership’s legacy project to the latest technologies. The project includes the following features:

  • Product catalog with filters and search
  • Institutional pages about the company and its services
  • Integration with CRM for customer and lead management
  • Integration with the inventory management system API of Audi
  • Administration panel to manage promotional banners and the dealership’s linktree

Challenges and Solutions

One of the main challenges was implementing a complete catalog system while upgrading the framework to the new Next.js 15 version. We solved this by refactoring the legacy code and updating the programming language to TypeScript. Additionally, we implemented a caching system to improve application performance.

Technologies Used

  • Frontend: Next.js for server-side rendering, improving SEO and application performance.
  • Backend: Node.js with Express for data management and integration with Audi’s inventory management system.
  • Database: PostgreSQL for data storage and integration with Audi’s inventory management system.
  • Integration: Integration with Audi’s inventory management system and the dealership’s CRM.
  • NextAUTH: Authentication and user management for accessing the administration panel.

Results

After launch, the platform saw a 15% increase in client conversions compared to the previous solution. The homepage loading time was reduced by 60%, significantly improving user experience. Additionally, there was a 20% increase in organic traffic compared to the previous solution.

Lessons Learned

This project taught us the importance of responsive design and scalable architecture. We also gained valuable insights into performance optimization for large-scale Next.js applications. Moreover, we learned how to optimize SEO for a large-scale Next.js application tailored to the automotive market.