Interactive Dashboard:
SustainInvest
Project Type
solo project
Duration
3 Weeks
My Role
Product Designer (Research, UX Design, prompt engineering, Usability Test)
Project Overview
Simplifying ESG and financial data into actionable investment insights
Sustainable investing is growing rapidly, yet ESG (Environmental, Social, Governance) data is often fragmented and difficult to interpret. Investors currently need to cross-check ESG reports and financial metrics across multiple sources, typically in long PDF reports or static documents.
The goal of this project is to design and prototype an interactive ESG Investor Dashboard that brings together ESG performance and financial metrics into a single, user-friendly interface, enabling investors to make faster and more evidence-based decisions.
Main Dashboard
Provide an at-a-glance overview of portfolio performance, top movers, and sector-level ESG insights.
Company Portfolio
Provide a portfolio-style overview of multiple companies’ ESG and financial data.
Company Comparison
Support direct comparison of multiple companies across ESG and financial metrics.
Performance Analytics
Reveal trends and positioning over time. Provides narrative-driven understanding of how a company’s ESG and financial performance evolves relative to its peers.
Background Research
From Interest to Action:
ESG’s Usage Gap
Through secondary research, I examined how investors perceive and apply ESG factors in their decisions. The findings revealed a clear gap between the growing interest in ESG and its practical use, highlighting challenges in data accessibility, reliability, and integration into investment processes.
Insight 01
ESG Investing Goes Mainstream
Recent research and market analyses confirm that ESG (Environmental, Social, Governance) has become a significant mainstream factor in investment decision-making globally, driven by rapid growth in ESG assets under management, stronger investor reliance on sustainability scores, and tightening regulations.
Insight 02
Information Access Gap between Institutional and Retail Investors
Institutional investors use ESG reports and platforms like Bloomberg or Sustainalytics, while retail investors—despite high interest—face poor access and complexity. Many turn to Yahoo Finance for integrated snapshots, but no platform yet provides truly reliable, decision-ready ESG and financial data in one place.
Problem Statement
Retail investors struggle to turn ESG interest into action without clear, accessible metrics.
Despite growing enthusiasm for ESG, retail investors face significant barriers in applying it to real investment decisions. The absence of clear, decision-ready ESG indicators—combined with fragmented and complex data—makes it difficult for them to translate sustainability goals into actionable portfolio choices.
User Requirement
From Brainstorming to Defining Core Requirements
To address the problem defined, I began by brainstorming a wide range of possible user needs and product features. The goal was to explore what kinds of solutions could meaningfully reduce the current gap between ESG interest and actionable investment decisions.
Through affinity mapping, these ideas were then organised into categories. This process clarified the direction of the product. In doing so, I was able to shape a clear product vision and determine the essential requirements that will guide prototyping.
Hypothesis
If ESG performance and financial data are presented together in an integrated
view, investors will be able to make more sustainable and informed investment decisions.
Product Requirement
From Requirements to AI-Generated Prototypes
After defining the product requirements, I translated them into structured prompts for the AI design tool Base44. The goal was to see how well AI could interpret detailed specifications and turn them into a usable dashboard prototype.
This step not only accelerated the design process but also provided an opportunity to iterate quickly, testing how different prompt variations shaped the layout, visual hierarchy, and data presentation.
Prototyping & Iteration
Iterating Design through Prompt Engineering
By refining prompts step by step, I was able to iteratively shape the dashboard’s layout, hierarchy, and visual consistency. Each adjustment—such as correcting data accuracy, aligning color systems, or improving chart readability—was the result of testing prompt variations and learning how the AI interpreted them.
Reflections
What I Learned
Redesigning MindDoc deepened my understanding of how design can support emotional well-being. Key takeaways from this project include:
01
Bridging Complexity with Clarity
ESG and financial data are inherently dense and technical. I realised the importance of translating this complexity into accessible, actionable visuals. Designing for clarity meant balancing data richness with intuitive hierarchy and narrative flow.
02
Prompt Engineering as a Design Tool
By iteratively refining prompts in Base44, I learned how precise instructions, structured context, and clear rules can directly influence AI-generated interfaces. This process showed me that prompt engineering is not just about asking, but about designing the language that guides outcomes.
03
Iterative Prototyping with AI
Working with an AI design tool allowed me to test, adjust, and validate design decisions quickly. I discovered that an iterative loop—prompt, output, refine—mirrors traditional design sprints, but with accelerated feedback cycles.
Works
Sustaininvest
Waymate