Data, oh my data. Any of these sounds familiar?

• Crime stats (everyone’s favorite)
• Population trends
• Who’s moving where
• Neighborhood statistics
• Sales comparables
• Rent comparables
• Average income
• Median housing prices

If you’ve ever started doing a rental property market analysis, you’ve probably assumed you need to start with the data. That’s a fair assumption!

But it’s a wrong assumption.

While data and statistics are important for the success of any real estate investment, it’s unlikely you’re at a stage where you can properly analyze data on its own and come to a meaningful conclusion. This goes for new investors and even for more experienced investors.

I’m an experienced investor and I very rarely look at data and statistics when I’m analyzing a possible market or deal.

The reason I rarely focus on those is because I’m very aware of my ignorance in understanding their true meaning. I can read data and statistics until the cows come home, but it doesn’t mean I’m going to be able to accurately interpret it.

Here’s a breakdown of what’s needed for data to be useful:

Data without context is useless. Data with context still has to be interpreted, or it’s useless. We can all get the data, but whether we know enough to properly put it into context or interpret it is another story.

And most of us don’t know how to do that.

Aside from not properly knowing how to use data in our analyses, there are other common problems with real estate data:

• Relevance

My favorite example of when relevance is important is when I constantly see news articles talking about “The Top 10 Cities for Real Estate Investors” and that article lists out ten random cities and the author’s reasoning for why they’re a top investor city. In exactly zero of those articles have I ever seen the author specify what real estate investing strategy they’re referring to. The best city for a flipper, for example, may not at all be the best city for a cash-flow investor. If someone wants a solid cash-flowing rental property, investing in one of those “top cities” may be incredibly risky. Not all data is relevant to your particular goal and strategy, so you have to be really careful which data you focus on.

• Source

If you go to a government-published website and pull data from there, great, it’s probably pretty accurate. But I see countless articles and blogs out there that spew all sorts of data and statistics but they either don’t say where they got that data, or they credit some miscellaneous source that may or may not have any clue what it’s talking about. It’s the idea of “you can’t trust everything you read on the internet” that applies here. Not only can you not trust every real estate statistic the internet gives you, but you can’t (or shouldn’t) trust everything everyone tells you. Even if the data they’re giving you is accurate, then it goes back to that Relevance thing again where it’s, while accurate, not applicable to your situation.

• Skews

I mentioned that everyone’s favorite statistic is crime. It’s kind of like why we love watching murder shows on TV, right? It’s adrenaline-inducing, exciting, and mysterious. Don’t get me wrong—crime stats can be incredibly important in a real estate analysis! You actually don’t want to invest in a crime-ridden neighborhood or the worth of your property is likely to suffer. But I can use crime stats to explain how data can be skewed. I live in Venice Beach in Los Angeles. If you look up the crime stats for Venice Beach, you might be concerned about me living here. When I look them up, it’s clear to me that I should’ve been beheaded a long time ago (literally, we had a few span of beheadings in my earlier years living here, not sure why). The crime stats here are real; there’s a lot of crime here. But I also have no problem walking around by myself late night, and I very rarely feel like I’m in danger. I live here and walk around here like there is no crime. And on top of me feeling super-safe, rents and property values are through the roof here. Owning property in Venice Beach, despite the crime, is insanely advantageous (as long as its appreciation and not cash flow you’re after). But if you look only at the crime stats, you’d never touch this place. Data can be skewed, and there’s really not a way for a non-expert to differentiate skewed from non-skewed data.

• What’s included in the data

It’s almost impossible to know exactly what goes into a particular piece of data or into a statistic. This may be because the source left something out or took into account only what they wanted to, or it could be that there are relevant facts that are unintentionally not clarified. The most common real estate investing market statistic I see this happen with is population trends. So many times a major metropolitan area reports a steady population decline over several years, which is an issue for investors, but the reality is that the population didn’t leave the city for another state, they just shifted around to different areas of town. For example, a lot of residents in St. Louis left the city of St. Louis for the outskirts of St. Louis, not more than 20-30 miles away. So when looking at St. Louis as a possible market to invest in, is it fair to say it’s been a declining market, and therefore you shouldn’t invest there? While the population trend shows a decline, that’s actually not the full truth, and St. Louis as a whole (and surrounding areas) has had a lot of growth, and continues to experience growth. Bad place to invest? I don’t think so. Another favorite example, having nothing to do with real estate, is I once heard a statistic that 95% of car accidents happen within 20 miles of people’s homes. The conclusion the author came to is that you’re way more likely to have an accident when you’re within 20 miles of your house than if you’re further out. The part that was left out of that statistic is that most people don’t drive further than 20 miles away from their home (at the time of this study), so of course most accidents would occur within that range, hello. This idea of missing or inaccurate information being included in the data isn’t far off from the issues of Relevance and Skews. They all boil down to the possibility that certain data isn’t exactly accurate for what you need or should be using.

• Reality

Then, it all comes down to reality. This is exactly the situation for me living in Venice Beach—the reality is that I feel perfectly safe and this is a highly desirable place for people to live, despite the crime statistics suggesting that everyone living here is bound to get murdered (if not murdered, at least stabbed… that happens a lot here). Outside of that example, reality more generally comes into play with rental property market analyses for things like—how rentable is a particular property, and how likely is it to be profitable? One of my most profitable rental properties in Atlanta is on a street that I’m not at all safe to get out of my car on. I’ve literally never gotten out of the car on that street. There’s even a homeless encampment next to that property. I’m not at all saying those things never cause problems, but the reality of that property and the street it’s on is different than what the logistics would suggest. On the contrary, one of the nicest rental properties I ever bought has been one of the hardest to rent out, and not one of the most profitable ones.  The best way, in my opinion, to find out the reality of any particular area or property when doing an analysis is to talk to professionals local to that property (property managers especially!) and hear from them their experience with rentability, vacancy rates, crime, and the quality of the typical tenant pool. Those things are going to tell you way more about the prospect of a profitable rental property than individual stats, in my opinion.

Data and stats by themselves don’t tell you everything you need to know. Instead, focus on learning the realities of what they all mean and what they’re telling you about a particular market or neighborhood.