Good On You
Good On You (GOY) is a Sydney-based organization that has rated thousands of fashion brands on their ethics and sustainability, available on their website and app. They also write articles and produce thought leadership regarding sustainable fashion.
Role: Data and Communications Intern
Date: April 2021 — June 2021
Objective: I had three main projects for my internship.
SEO: Updating existing blog content based on SEO guidelines and researching search keywords where GOY had the potential to rank higher. I ultimately optimized 10 articles for search and researched recommendations for improving GOY’s rank for 16 search terms.
Internal rating accuracy: Improving the accuracy of their Airtable scoring formula, which calculated an initial score for brands applying for a rating so that the team could prioritize brands that were likely to be more sustainable. Because GOY’s audience is already fairly informed about fast fashion brands to avoid, it’s a higher priority to introduce brands that are sustainable and ethical.
Data reporting UX: GOY was in the process of designing a user interface for brands to submit their own sustainability data, which would increase the efficiency of the rating process. This was done using Stacker, a tool that creates a front end for data sources like Airtable. I helped plan the data architecture by looking at GOYs rating criteria, mapping out the respective Airtable fields and Stacker interface elements to be included, and writing out the questions that brands would answer to correspond to each data input.
Skills: Airtable, Stacker, WordPress, SEO, Writing, UI/UX Design
Formula Improvement Process
I documented GOY’s existing initial brand rating formula, cleaned up Airtable views to include only the fields relevant to scoring the sustainability data submitted by brands, and suggested improvements to the formula. When comparing the predicted and actual total sustainability score, as well as individual section scores (Environment, Ethical Labor, and Animal Rights) for the most recent batch of brands rated, using the new formula improved accuracy for 75% of original predictions.
Stacker User Interface Planning
I created a hypothetical brand in GOY’s existing Stacker interface to 1) plan out which questions should be asked in the interface in order to collect the necessary data to generate an accurate initial rating (and the formatting of the questions, as well as any conditionals that needed to be added based on responses to prior questions), and 2) make suggestions for how to improve the user experience for brands planning to submit their sustainability data. This project was my first time using Stacker.
