Featured Case Study

EcoTrack: Redefining Sustainable Shopping

A comprehensive mobile solution helping users track and reduce their carbon footprint through real-time purchase analysis and AI-driven sustainability scoring.

Role

Lead UI/UX Designer

Duration

3 Months (2023)

Tools

Figma, Adobe CC, Notion

Understanding the Challenge

error

The Problem

Users struggle to quantify the environmental impact of their daily shopping habits due to fragmented data and a lack of transparency in supply chains. Existing apps are too manual and time-consuming.

check_circle

The Solution

An integrated API-driven dashboard that categorizes purchases and provides actionable sustainability scores instantly, using machine learning to recommend eco-friendly alternatives.

User Research & Insights

After interviewing 15 environmentally conscious shoppers, three key themes emerged that guided the entire design direction.

01

Convenience is King

85% of users stop tracking after 3 days if they have to manually input data. Automation was non-negotiable for retention.

02

Data Overload Paralysis

Users felt overwhelmed by raw CO2 numbers. They needed relative scores (e.g., "Good", "Average") to take action.

03

Community Motivation

Users were 2x more likely to stick to sustainable habits when they could see the collective impact of their social circle.

The Design Process

1
Discovery

Stakeholder interviews & competitive analysis.

2
Ideation

User flows, information architecture & wireframing.

3
Execution

High-fidelity UI design & visual systems.

4
Testing

Usability testing & iterative feedback loops.

Visual Identity

Color Palette

#0D59F2

#101622

#10B981

#94A3B8

Typography

Inter Bold

Inter Medium

Aa Bb Cc Dd Ee Ff Gg Hh Ii Jj Kk Ll Mm Nn Oo Pp Qq Rr Ss Tt Uu Vv Ww Xx Yy Zz 1234567890

Feature 01

Seamless API Integration

We connected directly with major banking APIs to allow for automatic purchase categorization. Users don't need to manually enter data; the app learns their habits and provides real-time impact assessments as they spend.

  • verified 99% accuracy in merchant categorization
  • verified Secure OAuth 2.0 banking protocols
Feature 02

Smart Substitution Engine

Instead of just showing the damage, we focused on the solution. Our recommendation engine suggests local, sustainable alternatives for frequently purchased items, calculating exactly how much CO2 the user could save.

"The substitution feature alone helped me reduce my footprint by 15% in the first month." — Beta User

Results & Impact

4.8

App Store Rating

1.2M

CO2 Tons Saved

65%

User Retention

200k

Active Users