Small businesses have struggled to compete with large companies in the current pandemic. We wanted to build something that would benefit both small businesses as well as local consumers. ProxiMerch achieves this by giving business the opportunity to sell more and providing fast delivery to the consumers. Consumers also have the chance of discovering a local store that they might not have tried out before.

What it does

ProxiMerch connects local businesses to consumers in their vicinity. When users come to the website, they only need to enter their location and what they want to buy. The website then searches for local shops in the users’ vicinity that sell that product, boosting sales of local small businesses.

How we built it

We used HTML, CSS and JavaScript for the front-end along with Python Flask for the web app. Using Google's Places API, we first search for small businesses that are located in the user's neighborhood. Our algorithm then does a web scrape to determine whether those businesses contains items that are requested by the user. With a mix of machine learning and proximity of a shop to a user, a list of recommended local shops are returned to the user.

Challenges we ran into

We faced some trouble finding a platform that was compatible with the front-end as well as the back-end. We initially created prototypes using Figma and Wix but ultimately decided on using Python Flask web app.

Accomplishments that we're proud of

We managed to create something that has the potential to actually be used in the real world and benefit those who use it.

What we learned

  • React
  • Figma
  • Wix
  • Webscraping
  • Google APIs
  • Machine Learning

What's next for ProxiMerch

  • A feature that automatically picks up the users’ location after asking for permission
  • A ‘recommended’ section inspired by past searches

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