Aug 29

For years I struggled with setting rents. Too much under market rents and the properties did not perform as well as they could. Too much over market rents, they sat vacant and do not perform as well as they could. There seems to be a theme developing here. 😉

To succeed you need to know what others are charging for rent in your very specific market. To that end, we spent a lot of my time, my staffs’ time and effort trying to collect comparable rents.

Ten, fifteen years ago our team manually enter details from for rent ads in the local papers, Craigslist, Zillow and anywhere else we found them. Then we would combine that information with city property records, trying to get an accurate view of what the market rent was for a particular unit. This was expensive and annoying.

We tried freelance data collectors through oDesk (now UpWork) to collect and correlate the records. Better, but still costly and the results still were not exactly what I wanted.

Then I saw promise in AI and Machine Learning, using tools like BlockSpring. Better results, but then Craigs and others started blocking automated collection tools.

We went back to manual data collection where we had to and automated what we could.

We were doing the rent surveys once or twice a year due to the hassle and costs. Quarterly would be better to catch trends.

I had looked at Rent-O-Meter in its early days. It seemed promising but had far less data than even our rudimentary data set.

Last October I relooked at Rent-O-Meter. Wow. We have been using it ever since.  They have both a free version and a free trial of the “Pro” version that goes for about $200 per year.  Setting one rent wrong will cost you more than that. You may want to take a look.

Note: while this may sound like an ad for Rent-O-Meter, it is not.  I’m just a happy, paying customer of theirs.

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