Median revenue from NYC AirBnB’s is $57.90 per night. Revenue skews low
with many low revenue listings.
Price per night seems to be somewhat important.
There are a few hot spots where average revenue is very high, while the rest of the city has low revenue listings.
After breaking down profitability by neighborhood, we want to see how
many listings are profitable in each neighborhood. (Using each of the
neighborhood’s average revenue.)
This paints a different picture from before. Neighborhoods in have higher overall average revenue, but only a few of those listings are profitable per neighborhood.
In order to, as an investor, decide where to invest and either create
a listing or improve an existing one, I want to understand which
features are important. I will use a decision tree:
## price occupancy
## 27986051.06 23689265.93
## neighborhood accommodates
## 7416795.01 6184157.88
## room_type bedrooms
## 5514525.75 4188340.68
## beds host_response_rate
## 3591480.05 1061904.63
## bathrooms longitude
## 599566.26 514768.33
## reviews_per_month minimum_nights
## 454425.88 317738.36
## host_since maximum_nights
## 112384.66 64776.29
## latitude review_scores_rating
## 43966.88 34670.49
## review_scores_communication review_scores_cleanliness
## 28366.77 26790.84
Some listings can be improved based on the changeable factors in the importance hierarchy generated by the decision tree. We can plot those locations to see what neighborhoods they belong to:
There are certainly a few places in the city where there is a high chance to have a profitable listing, but it would require some work on some of the modifiable characteristics of the listing such as price, minimum nights, and reviews for cleanliness and host communication. As an existing host I would take this into consideration and make the appropriate adjustments. As an investor I would see these as long-term fixer-upper projects.