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MACHINE TRUST: The secret reason why AI will re-invent Real Estate
By Purlin

WE HAVE STRONG OPINIONS on the subject of the effect of artificial intelligence (AI) on the real estate industry.  It might be one of the last steps in the quiet but insidious take over by the Machines – first, it was our music, then our movies, then our purchases, our homes, and soon it will be all over when they take control over our drones.  We’re living the apocalyptic AI cliché of Hollywood (and Elon Musk).  

OR, however naïve it may sound, AI might be the thing that saves the real estate industry.  Some companies already use AI as a financial vehicle to arbitrage housing inventory.  There are others that are pursuing AI as a way to automate the process in an attempt to make the agent better.  We believe the highest and best use of AI is helping buyers find the right home, which has everything to do with trust.   

To us the most troubling statistic in real estate today is that post-purchase most consumers experience buyer’s remorse (over 2/3 of Millennials).   The below-scribbled chart, which will frame the rest of this piece, describes the real estate market and the inverse relationship of Trust and Remorse, overlaid on our relationship with data over time.  We believe it frames how we got here and where we could go.  Despite its rough and humble appearance, this chart is not just the stuff of water-cooler spit-balling, but actually a working theory based on real data (much of it from the National Association of Realtors, 2018 Home Buyer and Seller Generational Trends Report). 

Prior to and through the Data Access era (which began with the advent of the WWW), trust in the real estate space was still placed in the real estate agent.  He or she proffered access to a proprietary database, knowledge of a confounding process and wisdom about neighborhoods and listings.  The agent would show the best options to the buyer who would ultimately be satisfied with picking the best of those options.  Trust was high, remorse low.  

When Zillow cracked open the Multiple Listing Service (MLS) in mid-2000s, granting the world access to every listing, we entered the Transparency era.  The old script was flipped, “the customer doesn’t know what they want, until you show  them,” became, “the more you show the customer, the more likely they’ll know what they want.” More listings, more pictures, and more agents meant more control, a better experience, and a better home.  That’s still the lure, and over 90% of homebuyers use online search services like Zillow.  Others like Redfin have joined the conversation with promises of using technology to make the process cheaper and easier.  Despite these promises and market penetration of these companies, buyer’s remorse is reaching new heights.  What gives?  

What buyers want most from their agents is “Helping find the right home to purchase” (4X as often as pricing and process).  When choosing an agent on this mission, homebuyers care most about trust (over 5X as much as their use of the latest technology). However Agents are unsuccessful at finding homes 70% of the time, and 80% of buyers report having to compromise when they purchased.   

Real estate technology companies are built around agents, but their solutions have taken away the agent’s core value to consumers which is still trust.  Zillow’s old school disintermediation model has turned agent selection into referral bidding, commoditizing the role and diminishing the relationship, experience and service level.   

The inaptitude of agents in finding the right home means most buyers are on their own sorting through countless poorly-suited listings and images, at the mercy of the Paradox of Choice.  They have two options: do their own trade-off analysis weighing the relative values of key attributes amounting to over 20gb of information to be processed by an average homebuyer, or take what meets the minimum for important criteria.   The complexity and emotion of the exercise make effective trade-off analysis humanly unlikely.  The latter is by definition settling. 

The new era of Data Intelligence offers hope by way of trust through personalization by AI (see scribble chart again).  The new convergence is not around a device but around the individual.  AI has quietly invaded other facets of our lives but we trust it implicitly because the suggestions made are surprisingly satisfying, frequently enough that we can let go of decision-making anxiety and the accompanying self-doubt.  Eighty percent of consumers are more likely to purchase a brand if it’s personalized (Epsilon report, 2018).  It does the trade-offs for the buyer, delivers on preference not need, and is the ultimate antidote to too many (or mismatched) options.  

“What if the home search started with the homebuyer’s perfect home and not a zip code?” 

Personalization by AI will re-invent how homebuyers find homes.  The killer AI application for real estate puts the process in reverse, focusing on what makes the home perfect, not how to make the home search better.  It trains AI to get to know the buyer early on, starting with what styles and floor plans and furnishings they like, where they are in life and lifestyle, where they spend time and need to be, and what they like to do.  It uses advanced machine learning and image recognition to fine tune its understanding of what homes, features, windows, and neighborhoods they like, through behavioral cues in addition to user interaction.  It takes preference algorithms to whole a new level by deriving preferences from uploaded favorite photos and collecting feature-level inputs.  As with personalization predecessors, all of this could be rolled into one trusted Match Score.  

AI will revolutionize real estate because it will bring back trust, and reduce remorse, by focusing on the buyer’s future happiness, not agent effectiveness.