Case Study I

DecidED Webapp

A tool built for students and advisors to simplify the financial aid decision-making process. DecidED analyzes financial aid award letters and provides real-time affordability feedback for students. 

The Problem

Our Approach


Moneythink (MT) started as an education non-profit that sought to help students build financial skills.

Over time, we honed in on a critical understanding: The first major financial decision that almost every student engages in was about college — whether to attend and which to attend. 

MT developed and launched a college coaching program to support students in making informed decisions. 

And then we came across what everyone in non-profits or education faces: scale and limited resources.

The Problem

Because financial aid award letters are so varied, complex, and confusing, existing college affordability tools could only focus on college cost or relied on manual assessment.

Existing tools couldn't provide students with the other half of the equation: personalized, structured data using their financial aid.

How might we deliver the value of direct college coaching to students in a scalable digital format?

We found inspiration from an unlikely source: tax filing.

Specifically, automated tax software that takes paper documents and processes them digitally. 

How might we bring that same data automation to financial aid award letters?

While engineers explored OCR tools, I designed the logic and context used to convert outputs into usable, structured data.

In tandem, I collaborated with the UI/UX designer to test different ways to display college affordability data to students.

Through a series of paper prototypes and user testing, we deepened our understanding of how students defined affordability and also validated a way to present data to students that felt accessible and intuitive.

The next phase coincided with the team's Product Director transitioning to part-time. I became solely responsible for leading MT's engineering and design resources, writing user stories, QA testing, and implementing product analytics.

We brought DecidED into the hands of students and advisors in time for the 2020 award season. 

Our Approach

11 sec.

Time to process each letter. Down from avg. of 3 min from manual processing. 


letter accuracy rate


Average letter upload per student


User growth in Year 2 of operation


Users who took at least 1 desired action after sign-up


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