Value Vision | Devpost

Inspiration

We wanted to tackle a pressing problem that could move closer to resolution through a creative application of code by getting the users actively involved in their everyday lives and choices as we believe in the power of small steps compounding over time. The endless consumer loop fueled by fast fashion intrigued us as a challenge that requires a multi-faceted approach, and we decided to focus on honing in on the minutest aspects of user experience to drive conscious change in the users as their lifestyle changes with time.

What it does

Our web extension, Value Vision, collects data on the price and material from the individual product page of a brand and calculates an estimate for the number of times it can be worn while retaining close to original quality through a discretionary approach (which we expect to replace with machine learning in time). This wear count is then used as a divisor for the price of the item, and the resulting cost per wear replaces the price text on the individual product page to reshape the user experience. This shift from purchase value to cost per wear creates a deeper understanding of sustainability, durability/wearability, and true value, thus creating a more mindful consumer that would be more likely to actively choose slower alternatives to fast fashion.

How we built it

We explored front-end web development for the project and utilized our knowledge of HTML, CSS, JavaScript, and the web app Manifest to build this project. The discretionary formula used to calculate number of wears was formulated through an observed understanding of brand product quality and clothing item type wardrobe-life from personal experiences and published data on the general durability of the materials used commonly.

Challenges we ran into

Our biggest challenge was the lack of available data to commit to the ideal machine-learning backed approach for the project, so we had to improvise and come up with our own subjective dataset to finish building our web extension. We tried substituting our cost per wear prices in the bigger grid views of the websites but that was not a success as there was no way to extract the needed material data in any other view besides the individual pages. We also struggled to create universal code for all sites as they have different HTML, but hopefully we can work to resolve these in the future and improve the overall functionality of the extension.

Accomplishments that we're proud of

Almost all of us had limited experience with front-end web development and had never built a web extension before, so learning together and coding one was a major accomplishment! Our understanding of the intersection of tech and sustainability has also increased significantly in the duration of the hackathon.

What's next for Value Vision

Lots of research to compile a dataset that can be used for machine learning! We want to improve the accuracy and reliability of our predictions, and also provide more educational background to the consumer on the importance of considering the true value of their wasteful fast fashion purchases.