CASE STUDY

City traffic management

Predicting congestion and optimizing routes with high-accuracy models.

City traffic management

Traffic operations needed predictions they could trust during incidents. We designed a management surface that pairs model output with actions operators can take.

Challenge

Congestion insights were buried, and route recommendations arrived too late to help.

Our solution

A live map-first layout, clearer incident queues, and recommendations operators can accept or override.

Before

  • Manual product recommendations with limited personalization.
  • Generic marketing campaigns lacking customer insights.
  • Slow response to market trends and customer behavior changes.
  • High cart abandonment rates due to poor user experience.
  • Inventory and pricing decisions made from guesswork, not data.

After

  • Hyper-personalized product discovery that boosts conversions.
  • Data-driven marketing powered by predictive analytics.
  • Real-time adaptation to customer preferences and buying patterns.
  • Smarter checkout flows reducing cart abandonment.
  • Optimized inventory, pricing, and supply chain efficiency.

Technologies used

Driving the rebuild with a modern stack

  • Design: Figma, design system, prototype testing
  • Commerce: Headless storefront, Shopify integrations
  • Analytics: Google Analytics 4, conversion tracking

Client feedback:

James Okonkwo

James Okonkwo

VP of Ecommerce

The Nexsas team transformed our storefront. We have never seen such fast, impressive growth. James Okonkwo, VP of Ecommerce, Orbit Commerce
CTA

Ready to take control of your work?

  • No credit card required
  • 14-Day free trial

Join thousands of teams already scaling faster

436 reviews on

5.0 Rating

Trustpilot