So you have to be careful when just looking at data. 

Brian Davis: @Eric LoweThere's a company called Rental Property Refund that does cost segregation studies virtually, based on self-reported data from you.

file=/secure/pabulletin/data/vol54/54-46/1644.html

Just go through them, select the renovated/closely matching ones, and enter them into a model.Here's my fix & flip model, you can see the comps entered and some quick stats below them: Then I use that comp data to adjust the Sale Price in the model to what I estimate it will be (double check the resale $/sf is in-line with the comps), then adjust the purchase price until I hit my desired return level. 

So it became a long-term action of repeating that cycle to achieve decent LT tenancy base. 

I also like to cross-reference that data with Facebook marketplace, craigslist, Zillow and apartments.com listings to get a really good idea of expectations for rent in a specific area.

How do you navigate that challenge in a market like Utah, where achieving that kind of rent-to-mortgage coverage is becoming nearly impossible?

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