"Deal!" is an innovative e-commerce app that enables users to exchange items with others while only covering shipping costs. The app reimagines traditional selling by transforming it into a fun, effortless, and sustainable activity. By swiping through a curated selection of items, users can find matches and complete exchanges in a playful, streamlined process.
At its core, "Deal!" promotes circular economy practices, encouraging users to extend the life of their belongings rather than discarding them. It focuses on reducing waste, particularly low-value items that are often trashed despite their potential for reuse. This approach not only helps minimize environmental impact but also makes sustainable choices accessible to everyone.
The app is designed to foster a collaborative, eco-conscious community where trading is simple and enjoyable. With its bold branding, dynamic swiping mechanics, and engaging interface, "Deal!" creates an entirely new way of trading, blending entertainment with environmental responsibility. By making sustainability easy and enjoyable, "Deal!" empowers users to be active participants in a more circular economy, fostering responsible consumption habits in a vibrant and friendly environment.
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99 percent of the stuff we buy is trashed within 6 months.

This alarming trend reflects a linear consumption model—create, use, discard—that depletes resources, increases pollution, and contributes to the global waste crisis. The growing need for circular economy practices has become critical to address these challenges by minimizing waste, reusing resources, and creating sustainable systems.
To design an engaging and efficient experience, a thorough mapping of typical journeys in existing e-commerce platforms was conducted. The analysis explored user interactions from the perspectives of sellers and buyers in both Customer-to-Customer (C2C) and Business-to-Customer (B2C) services. Platforms such as The Real Real and Vestiaire Collective (B2C) and Vinted, Subito.it, Gumtree, Tutti.ch (C2C) were used as benchmarks to understand the strengths and challenges of these models.
