Choicebia

Inspiration

It used to be so easy to distinguish the forbidden fruit. Nowadays however everything has gotten much more complex. Every fruit has a forbidden version. Imagine you're doing your weekly grocery shopping and are standing in front of a shelf full of different tomatoes. Which tomato should you choose? The cheapest one or the premium version? The regional one or the world-traveler? The organic one or the conventional? A label? Which label: Bio, Demeter, Fairtrade, Vegan, TerraSuisse, Alnatura ... ? Or is your current focus actually to become your healthiest you - which is the healthiest decision? We're spoilt for choice.

We know your struggle.

And that's why we built Choicebia! We help you get over your fear of making the wrong choice by suggesting the right product based on what's important to you.

Challenge #1, Challenge #2 and Challenge #18

What it does

Firstly, you create your profile by telling us what you care about: Sustainability, healthy eating, saving money. Or all of the above.

Then it's up to you, when you're in the Migros shop you can scan any product you're interested in and we will suggest the product which is best suited for you by comparing it to all other similar products based on the profile we have of you.

How we built it

Firstly, we made a prototype with Figma.

Then we built an IOS App (Swift) and used the Scandit SDK to read the Barcode of the products. A request to our python Backend (Flask) is being triggered, fetching the best suitable product for the user. The Backend connects to the Migros API to receive the underlying product information to calculate the scores and product comparisons which are returned and displayed in the UI.

We chose sustainability, healthiness, and cost as the most important factors for the customer.

We computed our own sustainability score because we wanted it to be product specific which wasn’t possible using 3rd party APIs. The score takes into account distance travelled and sustainability certificates and we would enhance this in the future.

It's deployed on the IBM Cloud (cloudfoundry).

Challenges we ran into

We wanted to use the Eaternity API suggested by IBM, but sadly they didn't provide the data we needed. For this reason we calculated our own sustainability score.
Not enough sleep

Accomplishments that we're proud of

Built a full working product in Python and Swift
Got the goodies we wanted - ALL the ovo rocks ;)

What we learned

Deployment IBM Cloud
Design Thinking Tools

What's next for Choicebia

Team up with Migros to publish an application which can be used in any grocery store to help find the best product for you.
The Migros App already contains the possibility to scan products. The next logical step would be to combine it with our functionality and include the possibility to pay the scanned items directly via the app.
Integrate analytics - challenge yourself and friends to become more sustainable.