Introduction

We vote with our dollar. That means when we make the decision to make purchases from companies and business that are making conscious steps to be mindful of the environment, community health, and employee well-being, we are telling businesses that their mission and actions align with our ethics. Even more, it signals to companies that have yet to take such actions that the average consumer cares what the business is doing internally, and that a purchase is not simply the end product but also a compilation of everything it took to make it.

Challenges

As we were creating our application, we realized that there was not one centralized location that informed consumers about what positive steps companies (big and small) were taking when producing their products. We also found that most of the time, it was the prerogative of the company to describe how their products were produced, what resources they utilized, and what conditions the employees worked under. This made the web-scraping a lot more challenging as the information provided was not consistent. Another challenge we faced was building the actual mobile app, all the members on our team were pretty unfamiliar with app development. An area that was particular issue was connecting the app with the python script.

What the app does

Currently, users can access the app by clicking on a category of products that they are interested in buying from. Then the app moves to what issues the consumer would like to see addressed in the making of the product that they are purchasing, they can select whichever issues, and then the app will present the best matching product.

What's Next?

We want expand so that we have a wider array of products to choose from, and better recommendation. We would also like to eventually add a profile feature, where users can input products they are currently using, and the app recommends more conscious alternatives using a recommender system potentially built through machine learning. Users may also earn incentives through buying more ecologically friendly products, potentially through credits or discounts. Furthermore, we would like to integrate location services so that the algorithm makes smarter recommendations, where the product is available for purchase near the customer.

Who we are.

Tannavee is a fourth year Genetics and Genomics major, computer science minor. Celine is a third year Computer Science major. Bonnie is a second year Biochemistry and Molecular Biology Major. Saghi is a third year Biophysics graduate student.