I am looking for help in identifying what is the best statistical approach to address the following market research question:
(1) I have a dataset from an online website that helps users rent their vacation homes.
For each vacation home I have information on:
- Their attributes (predictor variables): location (city and distance from city center), # of rooms, guest rating (10 stars),price, etc.
- Their sales performance (dependent variables): conversion rate, # of nights sold, sales volume in $
(2) The website rents vacation homes mainly for US and Canada customers
Question: I would like to be able to identify which combinations of predictor variables are associated with better performance, in order to be more targeted in gathering new homes for the site. Because most of the website users (renters) originate from the US and Canada (and I have a sense that they have different preferences) I would be especially interested in understanding which combinations of attributes work best for each country?
I imagine that for Canadian customers you could have 3 combinations of attributes that would work best. For instance, one combination could be: price $50-$75/day, 2 rooms, far from the city center, etc...
Any help would be really appreciated.