Compare profit or cost of ownership based on different combinations of properties and investment scenarios.
A case study that demonstrates my ability to solve business problems with a financial background.
Tasked with solving a specific user segment's problem as our semester project, my classmates and I chose to help home buyers. Purchasing property is stressful and confusing. Current tools are limited to calculating only the specifics like monthly payments. In reality, these investment decisions are based on a number of factors that should be considered together as a whole.
Completeness
Loan and payment tools only show a fraction of the full picture.
Flexibility
Calculating each scenario one at a time makes options difficult to compare.
Uniqueness
Different properties and financing options are assumed to use the same variables.
We combined previously independent calculations into one, providing a more complete view. This includes not only mortgage payments, but also additional variables that are often afterthoughts such as income tax, maintenance and even commission fees. Investors should be made aware of these hidden costs! With all relevant factors in mind, they can be confident that they are making the best possible decision. In addition to this, the ability to mix and match properties with various financial scenarios makes comparisons quick and easy.
If order to provide insights to potential buyers, first we needed a deep understanding of what went into these calculations.
Trying out existing tools further convinced us that we could fill a real gap given that they simply did not provide enough information. Mortgage payments are only half of the story!
So, what else is missing?
To answer this, I suggested we specifically dive into Montreal's market. Narrowing our scope meant we could actually find all possible conditions our app needed to include, allowing it to be truly dynamic. It needed to provide an accurate investment outlook for very specific inputs. This was a necessary step as we realized that it's far from a cookie-cutter calculation.
For example, a condo has additional fees compared to a house. A revenue property has tax benefits over a non-revenue property. Neighbourhoods have varying growth rates which should be reflected in future selling prices. Location also deals with differences in commission percentages and welcome tax. These are all things we had to consider.
To test the concept itself and the actual calculations, I made a fully functioning prototype in Excel. This served as the base for our actual web app.
Getting the calculations right took a lot of time and some serious tinkering. My future self is thankful for not having done this initially with JavaScript.
I used Figma and Webflow to create and refine the UI I had originally sketched. Webflow proved to be a great intermediate step as it helped me reverse-engineer the design and learn how to build a clean looking site with HTML and CSS.
At first the front-end was designed with fake data. Then came the hard part... making the site functional with dynamic calculations and DOM manipulations to display them in real-time.
One by one, we recreated the Excel functions with JavaScript and connected them to their placeholders in the HTML. Last step was to connect to the database and finally we had a working calculator!
Interchangeable inputs — Home buyers can compare and find the best combination of options by quickly selecting different sets of properties and financial scenarios.
Interchangeable inputs — Home buyers can compare and find the best combination of options by quickly selecting different sets of properties and financial scenarios.
Detailed calculations — Everything you should be aware of as an investor is presented to you in an easy to read summary table.
Detailed calculations — Everything you should be aware of as an investor is presented to you in an easy to read summary table.
User-specific data — Purchasing a property can span weeks or even months. Saving your inputs means you never have to re-do an analysis every time you want to revisit it.
User-specific data — Purchasing a property can span weeks or even months. Saving your inputs means you never have to re-do an analysis every time you want to revisit it.
