The housing prices vary enormously in Finland. This story gamifies the reader’s experience and reveals the huge differences in housing prices in Finland. Fill in the blanks and let the story decide what could be your new hometown, learn how much homes cost there in average and, for the very first time, explore in real time the current housing offerings in that municipality.
With the same money, you can buy a huge house by the lake in countryside or a tiny studio flat in Helsinki.
In the beginning of the story, the reader is asked to tell their current hometown. Story then proceeds to ask how much money they could spend and how big apartment they are looking for. The story then decides a new hometown for the reader by drawing lots. Reader can then continue by exploring both housing data and houses that are available for sell in that new hometown, real time. If they are not satisfied with the resulting town, the story lets the reader to draw lots again. In addition to all this, the story tells facts about housing prices in Finland and also a story of two persons with completely different kind of homes that has cost exactly the same amount.
By combining these facts, personal stories and the gamified experience, this story gives totally new tools for the readers to really understand the vast differences housing prices in Finland. It helps readers to do informed decisions on where to live and how the price differences effect on not only their lives but also on the society as whole.
Intro animation’s model is done in Cinema 4d and then exported to ThreeJS as GLTF. Intro’s scroll triggered animation is done by ScrollMagic.
In first part, by readers choice of municipality, housing prices are shown and compared to national prices. Data is prefetched from Statistics Finland.
In second part, reader is given a chance to place a budget and size of an apartment. With these parameters and JS, random municipality and apartments, fitting the budget, are drawn from housing listing site Oikotie’s service in real time.
What was the hardest part of this project?
Getting the data. We started negotiating with multiple housing listing sites already couple of years ago with very little success. We wanted to have access to their database in real time, so that we could show journalistically relevant content in our strories in real time. Finally, we found a listing site we were able to agree on terms with.
The story was groundbreaking in combining both official statistics and real time housing listing data to provide better understanding to readers.
What can others learn from this project?
Good data is worth waiting for. Of course, we reported on the housing market in the meantime as well, but we constantly kept our negotiations going and tried to find a solution to make this specific story with real time housing data.