EcoTicker

See the Impact. Shop with Purpose.

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Inspiration

We saw that there was a real need for online consumers to be able to shop sustainably, and not fuel the fast fashion phenomenon. Hence problem statement 1 of theme 3 really stood out to us.

What it does

Hence we created EcoTicker. EcoTicker is a Chrome extension that empowers users to make more sustainable shopping choices by providing real-time sustainability scores and actionable insights for products and brands as they browse e-commerce sites. It displays a clear A–F sustainability grade for each product, suggests greener alternatives using AI and ESG data, and rewards users with EcoPoints for sustainable purchases, which can be redeemed for eco-friendly rewards.

How we built it

Frontend: Built as a Chrome extension using JavaScript, HTML, and CSS, with content scripts that scan product pages for sustainability keywords and material percentages (e.g., “recycled,” “organic”). The UI includes a popup with Home, Rewards, and About tabs, and a banner displayed on product pages.

Scoring System: The sustainability metric is inspired by leading frameworks (Eco-Score, Higg Index, The Sustainability Consortium) and uses weighted categories: Materials Sourcing (40%), Manufacturing Impact (20%), Product Durability & Use (15%), End-of-Life & Circularity (15%), and Packaging Sustainability (10%). If no info is found for a category, it will say there is a lack of information.

Backend Integration: Initially, we attempted to use AI to directly webscrape product data, but this approach was unsuccessful. We then implemented scraping using Axios and Cheerio to patch the contents and extract necessary information for scoring.

Data Handling: We considered whether to create a backend database of all products but realised that product listings and details frequently change. Instead, we focused on real-time extraction and analysis.

Challenges we ran into

Web Scraping Limitations: Directly sending requests to AI for webscraping did not work due to technical and security restrictions. We had to pivot and use Axios with Cheerio for server-side scraping and patching of product content.

Backend Data Management: We were initially unsure whether to maintain a product database, but the dynamic nature of e-commerce products made this approach impractical. We opted for real-time scraping and analysis instead.

Data Consistency: Ensuring that the sustainability score remains accurate as product details and availability change was a challenge, especially when product pages lack complete information.

Extensibility: Designing the extension to be robust for Nike while remaining flexible for future expansion to other platforms required careful planning of selectors and scoring logic.

Accomplishments that we're proud of

Robust, Transparent Metric: Developed a clear, research-driven sustainability scoring system inspired by industry best practices, making the results trustworthy for users.

Seamless User Experience: Created a modern, non-intrusive UI with real-time scoring and actionable suggestions, enhancing the shopping experience without disrupting it.

AI-Powered Suggestions: Integrated OpenAI’s API to provide a sustainability score, even when product data is incomplete.

What we learned

Web Scraping with JavaScript: Using Axios and Cheerio is a reliable method for extracting product data when direct AI-powered scraping is not feasible.

Dynamic Data Handling: E-commerce product listings are highly dynamic, so real-time data extraction is more practical than maintaining a static database.

Backend-Frontend Communication: Efficient use of Chrome’s messaging and storage APIs is essential for seamless data flow between content scripts, background scripts, and the popup UI.

Metric Design: Building a weighted, modular sustainability metric allows for flexibility and future expansion to other platforms and product types.

What's next for EcoTicker

Model Improvement: Implement a system that leverages user interactions and feedback to refine the sustainability scoring model, making it more accurate and adaptive as more users analyse a wider variety of products.

Weight Optimisation: Continuously tune the metric’s weights based on real-world data and user feedback to better reflect the true sustainability of products.

Platform Expansion: Extend support to additional e-commerce sites like Amazon, IKEA, and Adidas, updating selectors and logic as needed.

Enhanced AI Integration for product recommendations: Improve the AI-powered suggestion system to provide relevant and diverse alternative products, especially as product data coverage grows.

Reward System Integration: Implement a gamified EcoPoints system that incentivises sustainable shopping and offers tangible rewards.

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