Below is some recent research on visual data mining.
Personalization in product recommender systems in industries outside of real estate will soon impact how consumers choose—or will want to choose—real estate professionals on brokerage sites. The basic concept: How would Amazon.com recommend a real estate professional? To answer this there are two basic sides to consider: customer behavior within a system (and increasingly outside of the system; see what RETargeter is doing) and attributes and behavior of the real estate professional.
At a very basic level, recommender systems track and log consumer behavior and then match appropriate products and services based on this behavior. The key is that these products and services have particular attributes that “match” the behavior of the consumer. For example, assume Consumer A purchased five historical novels over the past five months, a recommender system likely would recommend another historical novel as a next purchase. So how could this impact real estate professionals?
First, assume a brokerage has a system that logs consumer behavior (login times, locations searched, favorite properties, map searches generated, etc). Second, assume a brokerage has segmented its agent base by basic factors (such as top neighborhoods serviced by the agents, top 10 zip codes serviced by the agents, lifestyle attributes, designation, luxury expert, waterfront expert, client service satisfaction ratings, MLS performance, etc). Next, the real estate professional recommender system could work similarly as to how a book recommender system works. And I know that some listing aggregators already offer this type of service, but these services on generally pay-to-play. What I am suggesting is that brokerages need to do something similar with their system and offer it free-of-charge to their agents.
For example, lets assume Consumer B registers and saves a luxury property overlooking a lake, the system could automatically “recommend” agents who work the zip code of luxury property AND are luxury agents AND are waterfront specialists. Next, let’s assume Consumer B clicks the profiles of each of the recommended agents, he or she will then see overall performance ratings, specific testimonials, and specific customer satisfaction ratings. The benefit to the consumer is that they’re presented with the “best” professional based on their interest, which supports customers-for-life marketing best practices. The benefit to the real estate professional is that they’re in front of the consumer faster and in context to the search process. This type of a process promotes a personalized experience which is key factor in capturing consumer mindshare. And, indeed, there is research that supports this proposition.