Overview
In this project, I worked on Ada Analytics, an AI-powered platform designed to help users make more informed investment decisions.
My focus was on research, understanding how people interact with financial data, and identifying where things start to feel overwhelming or unclear.
Many financial tools present information in ways that are hard to interpret, which can lead to confusion and low confidence.
The goal was to present AI-driven insights in a way that feels clear, trustworthy, and easier to act on.
My contribution
User research
User interviews
Persona development
Insights synthesis
UX strategy & definition
Scope
John M., UX/UI Lead
Selene D., UX Researcher
Lu F., UX/UI Designer
Dr. Ray H., Founder
James, Data Eng.
Year
2025
Process
Research & Insights
I spoke with users and looked at existing financial tools to understand how people interpret and act on financial data.
A key insight was that users often feel overwhelmed by complex information and need clearer, more structured insights they can quickly trust and act on.
Strategy
Instead of adding more information, I focused on making things easier to understand.
I defined principles around simplicity, transparency, and reducing cognitive load through clearer hierarchy and more concise content.
Concept Development
I explored how AI-generated recommendations could be presented in a way that feels more approachable and easier to use.
This included shaping key moments like risk selection, recommendation clarity, and follow-up actions.
Outcome
The final concept shows how AI-powered financial insights can be presented in a clear and more digestible way.
By focusing on simplicity and structure, the experience helps users better understand recommendations and feel more confident in their decisions.
It demonstrates how complex financial data can be turned into something more approachable and easier to act on.