by Wendy McPherson
The newest buzz words in real estate are analytics, statistics and metrics. All of a sudden the industry has discovered charts and graphs. Agents now have statistical tools that even the most dyed-in-the-wool English major can master. You can plug in areas and price ranges that you want and presto, a chart appears.
Thus, I embarked on sending my Woodside friends the very latest metrics churned out by the handy online formulaic plug-and-play chart creator. Both the real-estate trade association and most local real-estate companies make available sites that spit out these glorious-looking, full-color charts about average prices, price per square foot and other random data.
In a few minutes at the computer, I got this great-looking chart all put together with a few keystrokes and pressed send, confident of my data, knowing computers know their stuff when it comes to numbers. My friends called soon after and started asking questions about my chart. Thank goodness for voice mail because their first question was: "Ah, Wendy, do you think we should even look in Woodside since the average price there is $7.2 million?"
What!!!! How could this be? I started to actually study the chart. Yes, there it was. Woodside average price is currently $7.2 million. I knew instinctively that the average was closer to $4 million. I was now intensely poring over the chart and the data behind it and becoming a full-fledged beginner nerd. I was beginning to discover a few things about data. You cannot talk about "averages" (or even medians) when the amount of data is so small that one large sale skews your entire chart as happens in our local towns of Woodside, Atherton and Portola Valley. Yes, Woodside had one sale reported at $24 million, making the year-to-date average sale price $7.2 million. There were only 14 closed sales year to date at that point in Woodside.
Price per square foot is another chart favorite and can be a black hole of data that, improperly researched and displayed, can be very misleading. Palo Alto is a good example of this one-size-fits-all compartmentalization. If two houses were right next to each other and on the same size lot and contained the same house square footage (which can be tough to find in Palo Alto anyway) then theoretically the price per square foot would be the same if these very basic programs are used. Rarely is age, condition, location taken into consideration. The most useful information you are going to get from these paint-by-number statistics are general long-term trends. Between the paucity of data and the limitations of their structure, use these charts and graphs to look at the broad overview of the area.
All this is to say, beware of current statistics and the extremely basic and elementary data on which they are based. This is still a very human business that takes experienced and intelligent humans to give you counsel on this important pricing decision.