Real Estate Data Is Only As Good As The Source AND The Interpreter
The cleanest data is found in the actual MLS. Any reliance on a data provider that is not the actual MLS may cause mistaken conclusions. Correct data in any reporting process is important. It is especially important when looking at reports that are generated by data sources that have filtered it themselves, or that received filtered data.
How can I say this? Because I look at the cleanest data - the MLS data - and I see flaws in that data all the time. That MLS data is not always correctly entered. So if that data is being acquired by a non-MLS user and then filtered and compiled further, it will be even more skewed and corrupt when it is published for some other user down the line.
The problem with basing real estate buying and selling decisions only on data, is that if the data has flaws, you may be led to a flawed decision. Having a real estate professional look at the data and help verify, explain, or even correct it, becomes very important to most savvy consumers. Professionals who are in and out of homes every day, who are daily watching sales and listings, and who are running MLS reports often, learn to understand the flaws in the data, what to look for, and what to rely on - and what not to rely on.
Once any compiled data is produced in a readable form, like a graph or chart, the results need to be looked at by someone experienced and who can see flaws quickly. Sometimes that same person can provide explanations and solutions to mis-information, and/or provide clarity for anomalies and mistakes in the data. And then there are just those bits of data that are called "... within a 3%+- margin."
I provide the two real estate graphs based below as examples. Look over the first copy of the graph. Do you see any flaws?
The flaws can be from things like data entry errors, or from programming glitches, or even from insufficient data. This graph came directly from the MLS, and I knew there would be flaws in it - because I am working with real estate and MLS data every day.
(You can find my comments about the immediate flaws I see, below the second graph.)
Did you find anything that doesn't look right? What if you had to base a buying or selling decision on this report for a property in the $300K-$400K range? Would you be confident just using this report?
The flaws I see are in the colored boxes. You can see the assumptions that appear to be anomalies, mistakes, and bad conclusions. In the yellow box, there is a data entry error. There was not a property sold for $299.00 in 2004. It may have sold for $299,000.00, but not $299.00.
In the red boxes in the right most column, there are Sale Price to Original Price Ratios (SP:OP). Some of those ratios are clearly "outa whack," as Vinny Gambini would say. Why? Are those data entry issues? Are they programming issues? What?
The bad data causes the summaries to be incorrect, too. The two bottom most red boxes show how bad data causes bad conclusions.
I rest my case: Real Estate Data Is Only As Good As The Source AND The Interpreter.
When you want good data, get help from a true professional.
I'd be glad to help. I work on Cape Cod. But, wherever you are, there is a professional who can help you. I know true real estate professionals all over the country.
You only have to ask. email me at : firstname.lastname@example.org