AirBnB is one of the many examples of companies that took full advantage of the exponential rise of the tech industry over the past 25 years. It has transformed itself, since its founding in 2008, as a convenient option for people looking for nice, big places to stay without overpaying for a hotel room.

In a case of a host, he/she is allowed to list their own prices and availability times which would seem to conclude that AirBnB gives a substantial amount of power to its consumers. However, this also sets a problem for a host, for when, at times, they don’t have the expertise of setting a reasonable price customers would go for.

I took part in a 9 person team to try and construct an app or website that would help hosts increase their profit with each booking. Our team consisted of a frontend, backend, data science and marketing team. I contributed mostly to the data science activities of our team.

This website uses our self-created smart pricing API that takes a listings’ size, location, amenities and market value to generate an optimal price for a unit. Within a few minutes a person can get be suggested a price that will be high enough for the host to make the most profit, but not too high so that customers will be interested.

Being a part of the data science team, we were assigned to construct an API that would predict a price for a unit by training a model on past data which would let the model know what the most optimal price would be.

To see the website and test some of its functionalities, click here To see methods the data science team used to derive our results, click here