Inspiration
What it does
Our project divides existing Airbnb data into cohorts and gives them percentage of our total investment (to diversify risks)
How we built it
We divided our investments into 3 cohorts into short term (less then 7 days), long term (30+ days) and hybrid (uses the seasonal deviations to optimise the revenue)
Challenges we ran into
We had a big issue with lack of data about property cost, so we decided to go around and work with what can enhance the revenue.
Accomplishments that we're proud of
We were able to find optimal neighborhoods for each cohort based on their revenue Transit datasets (bus stops and SkyTrain stations), census and estimated population data were used to find a correlation with a good spots.
What we learned
We learned how to act when usual "data tricks" don't work and to work in the extreme lack of time.
What's next for DataJam 2026
Make a magnificent presentation and hope to get to the final
