Maybe more than you would think. There appears to be an interesting correlation. According the Bureau of Labor and Statistics (http://www.bls.gov/k12/money05.htm#pay), the distribution of income in between agents looks like this:
• The highest-paid 10 percent earned more than $111,500 a year
• The middle half of all real estate agents earned between $26,790 and $65,270 a year
• The lowest-paid 10 percent earned less than $20,170 a year
According to a recent data analysis for session activities by real estate agents, we noticed the following:
• The most active users of an MLS (upper 10%) originated 38.2% of all sessions
• The average active users (middle 50%) originated 31.9% of all sessions
• The least active users (bottom 10%) originated 0.3% of all sessions
This was a fairly simple analysis made possible by Scout Analytics, but without much more crunching of numbers, it would certainly be easy to correlate agent performance to utilization of an MLS. Now extrapolate that out to understanding not only performance of the agent to the use of one tool but to the use of multiple tools. The potential for associations, brokers and agents to better understand which tools and which usage profiles lead to improved productivity has the potential to help them change their own practices and increase revenue. Often overlooked as a resource, usage data of an online service has the potential to give new insights into the dynamics of markets and best practices.
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