How Do Consumers Choose An Agent, Part II: The Tyranny of Ordered Lists

Mar 14, 2008 Michael Wurzer

In Part I, I discussed how (and if) consumers’ search for listings is related to their selection of an agent.   Questions were raised about whether leads from listings are converting to customers, especially from an MLS listing portal like or any site that promotes the listing agent, given the challenge of single-agent dual agency and (or any listing agent).  What does the consumer want?  What is their natural decision-making path to selecting an agent?

According to the NAR 2007 Survey of Home Buyers and Sellers, “Forty-one percent of sellers found their agent as a result of a referral, while 23 percent used the agent in a previous home purchase. Similarly, 43 percent of buyers relied on referrals to find an agent, while 17 percent of repeat buyers used an agent from a previous transaction.”  In a year earlier survey, “7 percent [of buyers] found an agent on the Internet.”  These stats would need to have changed dramatically to avoid the conclusion that consumers don’t choose agents based from listing searches or from the Internet at all.   Rather, as then NAR President Pat Coombs said, “Real estate is very much a face-to-face people business”.

At the same time, the web undoubtedly is providing new ways for people to meet each other and the value of a relationship is often being tested by data.  More sites are exposing consumer reviews, pricing, and other data to the consumer to help them make decisions about which agent to choose.  There are sites like HomeGainHomethinking, Agent Scoreboard, Agentopolis, and Incredible Agent that provide a variety of agent search capabilities.  Some sites, like HomeGain, provide ways to compare agents on criteria like commission rates, years of experience, and consumer feedback. Others, like Homethinking, focus on productivity statistics, like homes sold and price ranges.

With little question, sites that provide more information to consumers are a good thing.  Consumers clearly are looking for short-cuts to decide which agent to choose and, as noted above, the current short-cut is the personal referral, born of trust, whether deserved or not.  The efficiency of the personal referral appears hard to beat.  With just a few words, backed by personal trust, your friend or relative is able to communicate a wealth of complex information into a decision.

As web 2.0 companies slice and dice the data, however, I wonder if that efficiency can be matched?  Is there an algorithm that will truly help consumers find the right agent?  The 2006 NAR survey referenced above found “the most important factors in choosing an agent for buyers are honesty and integrity, followed by the agent’s reputation. Other important qualities buyers value in an agent include knowledge of the purchase process and responsiveness. For sellers, the most important factor in choosing an agent is reputation, followed by honesty and trustworthiness.”  Given this, one would think sites providing consumer feedback about their experience with an agent would be very valuable, but does the wisdom of crowds math apply when the number of referrals an agent may get on-line in any given time-period is pretty low?  Will one or more sites gain enough critical mass that this data can be aggregated in a meaningful way?

Perhaps more importantly, is it possible to synthesize this data into a “score” or “rank” in order to provide the consumer with a recommendation?  This is what I’ll refer to as the tyranny of the ordered list.  Whatever the method is for the agent search, the output is an ordered list, with someone coming out an top, just like we see with Google search results.  The search algorithm is designed to bring the “best” match to the top.   Even leaving aside the fact that many of the sites linked above have revenue models that create conflicts of interest to place certain agents near the top of the search results (or at least to the side like Google AdWords), the reality is that matching a specific consumer’s needs to a specific agent’s qualifications remains ridiculously complex.

Are these ranking sites really helping consumers?  They are providing more data but is the data useful?  The power of a ranked list is daunting, because it provides an easy short-cut.  Why look at agent two or three when there is a number one?  Yet is that ranking really anything more than arbitrary given the complex factors involved?  Does the ordered or ranked list cut off due diligence when it really should just begin?

Perhaps the natural path for agent selection on-line is through social networking.  From general sites like Facebook, LinkedIn, and MySpace to real estate specific sites like Trulia, Zillow, PropertyQube, ActiveRain and many, many others, the opportunities to meet people on-line is growing at a rapid rate.  To this end, however, I think many are seeing panaceas where none exist.  Just the other day, Dustin linked to a post from Curbed about a consumer being freaked out by their agent trying to befriend them on Facebook.

In this regard, the social networking tools Trulia and Zillow have provided surrounding listing content seem like a promising way for agents to build trust among consumers, but that brings us right back to the tyranny of the ordered list.  Jonathon Dalton and Jay Thompson have been posting for some time about the ranking Trulia provides (or provided?) based on the highest number of answers, which resulted in a bunch of agents providing lots of answers of questionable quality in areas they knew little or nothing about.

In the end, modeling the consumer selection of an agent on-line is tricky business at best, and the personal referral is likely to dominate for some time to come, and, in many ways, I think this is a good thing.  I consider, for example, brokers like Jay Thompson who just went independent and is building a great brand on-line through his blog and other sites the cream of the crop as to how an agent can communicate their value proposition to consumers.  That value proposition will be very difficult, if not impossible, to measure or rank, but the web makes it possible for consumers to connect anyway.