Inspiration - To deliver the best user experience in shopping

Inspired by Migros, we want to revolutionize the shopping experience in the supermarket. What if you could easily know everything about a product in your hand and get personalized recommendations for the best fitting products? We have no other goal than that. And that is highly needed in our modern times. When doing online shopping, you can compare millions of products around the world. If local stores want to defy that competition, they must also offer real time possibilities to compare the products in the store with others and to access additional data.

What it does

With our app, you can go into the supermarket and scan the bar codes of many tens thousands products in Switzerland. We will show you a lot of additional information about that product in the app, including where exactly it comes from and what carbon footprint it has. We show you alternative products that might be interesting for you. You can also search in the app for products and we will include only products that are relevant for you - considering your allergies, meat preferences, organic and sustainable food preferences and more.

How we built it

In the beginning, we used different Design Thinking strategies in order to organize our brainstorming. During the weekend, we did several short sprints, according to Scrum and regularly met with all onsite and our remote participant. We wrote all our tasks on colorful post its and posted them on a Kanban board so that everybody had the overview what the others were working on.

On the front end side, we used the ionic framework with Angular to create an Android-App (that can also be directly compiled to iOS). For the Backend we developed a REST API with Flask. A crucial part of our application is the Migros product API, which provided us with rich information about food and retail.

Challenges we ran into

One of the biggest challenges was time management. Even developing small features can consume a lot of time, especially if unexpected problems arise. In particular, the Migros product API was more complex than we anticipated.

Accomplishments that we're proud of

We successfully constructed a working Android-App, which builds on the product API of Migros. Using the provided data we were able to design an approach for a more customer centered shopping experience.

What we learned

A lot! And we had a lot of fun :D Mostly, we learned that sleep is overrated.

What's next for Xplora

There is already a large amount of data about the shopping behavior of retail customers. Machine learning can be used to bring individual recommendations to the next level. In particular, the current user profile can be refined by considering past shopping decisions. The architecture of Xplora naturally allows for embedding such advanced recommendation approaches.

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