Overview
In November 2019 I attended the biggest hackathon in Europe: Junction Ltd Helsinki. Together with my team, we were able to win the Digital Retail track! Out of more than 350 projects in the hackathon, our project made it to the finals as 1 of only 8 teams. Our idea was based on Machine Learning and an adaptive UI in order to stop online mispurchases and to reduce the number of items that are returned by customers.
My role
Our team consisted out of 5 students. My role was focused on creating and implementing the design for a webshop together with one other designer in our team. Because we had only 48 hours to complete the product we just created a few Hi-Fi prototypes in Figma and then immediately started developing the webshop using HTML, CSS, Angular, and TypeScript.
Solution
In the pictures of the design below you can see that the check-out process consists out of 4 steps or 5 steps. The extra step is only added to the process when the consumer is considered to have a high possibility of returning a product. By using the consumer's behavior on the website and comparing this to existing data, the machine learning algorithm will decide if the consumer is likely to return the product or not. If yes, the 3rd step will be added in the check-out process to remind the consumer of a few important features of the product and to give the consumer the possibility to discard or change the product. This way the consumer will be extra sure about the purchase without scaring them out of the purchase. Because the main goal was to reduce the number of mispurchases without scaring off customers that would have bought the product and not send it back.
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