If you do not happen to be deeply immersed in the real estate industry, you probably do not realize that there is a war going on. The war is over whether and how to make real estate agent performance data available to the public.
Agent performance data, gleaned from actual agent transactions, would provide very specific and objective information on the past performance of individual agents. The information could include things like…
- The number of homes an agent sold in a year
- The average sell price of those homes
- The average number of days it took the agent to sell those homes
- The average percentage of the asking price the agent got for those homes
This would really be fantastic information to make available to consumers to help them in choosing an agent. Far better than the more subjective rating systems available today. But like most things in the real estate industry, progress does not happen without a fight.
The consensus quickly forming in the real estate industry is that eventually this information is going to get out (like somehow it is in prison). The question now becomes, how best to do it? And the answer is, it depends on who you want it to benefit.
The first shot in this war was actually fired by NAR, the National Association of Realtors, which represents about a million real estate agents nationwide. They came up with this idea called AgentMatch. The idea behind AgentMatch is that consumers would go to the site, enter information about themselves and the home they are buying or selling, and AgentMatch would come up with the best real estate agent for the consumer, based on agent performance data. This idea was met with such venom from the real estate community, that it was quickly abandoned, as it should have been.
Regrettably, there are now some for-profit companies (here, here and here) doing the same exact thing. And where does that profit come from? The agents, who are willing to pay to be at the top of the list when a consumer searches. It makes you wonder why they even need (or use) the performance data. At least AgentMatch was attempting to be objective.
These “matching engines” highlight the worst possible use of agent performance data: letting someone other than the consumer use the data to decide who should be the right agent. Making the agent choice for the consumer is filled with troubling questions. What are the criteria being used to decide? Is it biased in some way that is detrimental to the consumer? Are the results influenced by paying agents?
Only time will tell how and when the real estate industry finally liberates agent performance data. Their biggest concern seems to be that if they make the raw data available to consumers, it could be misinterpreted. By misinterpreted, I supposed they mean it will be used to choose an agent other than themselves. But this fear is unfounded, and also a little insulting. It assumes that consumers are not smart enough to interpret the data on their own and make a beneficial decision for themselves. Is it possible that a consumer will make a bad choice after reviewing the data? Of course. But that is no different from making any bad decision in the market place with an abundance of information. The real estate industry is not in a position to protect consumers from themselves. They should make the raw data available, letting the smart consumers make intelligent choices while letting the inexperienced ones learn from their mistakes.
So what is the best use of this data? As one input in the agent selection process. Ideally, the consumer can use this data as a final filter when deciding on an agent to work with.
Suppose a home seller finds three agents they might like to list their home. One of the ways to narrow the choice might be to conduct interviews. A second selection criteria might be online reviews. And a third deciding factor might be to compare the raw data of these three agents side-by-side. This is no different from when someone applies for a job and a combination of their past performance (i.e., their resume) and their job interview are used to select a candidate.
The above idea not only mentions the best use of the data, but also highlights the best way to use the data: for comparison. I agree that the raw data for a single agent is almost useless. What does it mean that an agent sells homes for 95% of asking price on average? Is that good? Is that bad? In isolation, the numbers are meaningless. But use that same data to compare three agents selling similarly priced homes in the same neighborhood during the same twelve month period, and now you have very useful information.
I do not know how long it will take for this data to become freely and easily available to the consumer. The information actually exists right now, piece-meal, on the various third-party web sites, but I doubt many consumers will take the time to sift through it. Here is hoping that an industry that purports to encourage consumers to shop around for the best agent, makes the data available for them to actually do so.