• Shopping is a habit. You tend to go to the same store for the same things.
  • In-store stock level becomes more stable as Singapore's COVID situation improves.
  • Upon the reopening of the economy, queues are everywhere.
  • Queues bring uncertainty yet encourage more to join the lines.
  • The admiration of small businesses in Singapore that supports and create convenience to the local community.

What it does

ShopAid is on a mission to bring people back to the street smartly and sensibly, connecting shoppers to big and small businesses to explore an unparalleled shopping experience. It incentivises good behaviours of shoppers and stores that contribute to a better, strong economy as a collective.

ShopAid is an application to help you get essentials efficiently based on your travel time, and the collective intelligence of stock availability and crowd level.

  • You list the items required on ShopAid. This helps you plan well and avoid panic buying.
  • Based on your location, ShopAid shows the approximate stock availability of your items in all stores (big and small) nearby.
  • There’s also live information on how busy the stores are, and the travel time using different modes of transport.
  • You can decide which stores to go to based on these valuable insights, all on one page.
  • When you are checking off your shopping list in the store, you can provide stock and queue/crowd level information easily.
  • To recognise your contribution to the local community, when you provide stock and queue/crowd level information and/or shop at off-peak, you earn points and badges that can be exchanged into vouchers for freebies and discounts provided by the stores.

Stores are motivated to use ShopAid to indicate estimated queue time and stock level, as they earn opportunities to launch promotion to shoppers (e.g. new products, reduced to clear, etc.)

In the long term, we will continue contributing the local economies by encouraging people to shop responsibly and locally. We would also like to roll out the application in other sectors to suit their context, e.g. sourcing healthcare supply from manufacturers and general facilities management.

How we built it

We conducted several rounds of user survey and usability to validate our understanding of shoppers' needs.

  • Wireframe: Figma
  • Backend: Python framework Flask
  • Frontend: React.js
  • Database: PostgreSQL
  • Deployment: GitHub Pages, Docker

Accomplishments that we are proud of

We built our first iteration of MVP (GPS location detection, store listing, route calculation, shopping list, check-off and indicate approximate stock level).

What we learned

  • Good features: stock levels, prices, distance, crowd levels
  • Let-go features: taking photos, budgets, recipes
  • Motivation and benefits we can bring to the stores
  • Using Google Maps API can be expensive, but there are alternative ways to calculate travel time

What's next for ShopAid

In the next 2 months

  • Integrate the stock level information to our web app prototype for a combined view
  • Reach out to more stores and shoppers
  • Perform further app usability testing with shoppers

In 4 months

  • Connect with stores' inventory and POS systems
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