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Big Data Is Watching: How Companies Predict Your Real Estate Moves

by Editor | ezLandlordForms

“Just because you’re paranoid doesn’t mean they aren’t after you.” -Joseph Heller, Catch-22

Ever feel like you are being watched?  You’re not the only one.  More reliance on digital technology means more data available to corporations and governments to analyze, predict or even manipulate your behavior.

Realty companies and consulting groups have been using public – and not so public – information to build profiles on potential buyers and sellers.  Public information such as age, marital status, court records and how long one has owned a property are used to analyze who is in a position to sell a high-value property.  More personal information, such as pregnancy, income, net worth or a child graduating high school and leaving for college can also indicate a homeowner is open to selling their home and moving.

These predictive marketing tools collect massive amounts of data.  One company claims to have 1.3 million gigabytes of data on nearly every homeowner and property in the United States.  Companies like this one will use algorithms to target which homeowners may be likely to consider selling.  Factors include property owners’ hobbies and interests, past buying behavior, age, marital status, income and real estate equity.  Companies compile these small pieces of information and analyze it in aggregate to make predictions about what homeowners are likely to do in the future.

This data is also analyzed according to which variables are most relevant for selling in a specific geographic region.  For instance, one company has identified that in San Jose, seller triggers are homeowner age and LTV ratio.  Yet in Manhattan, household income and the sale price of neighboring homes are the most predictive factors.  While this information is useful for real estate brokers and corporations, it may feel like an invasion of privacy to homeowners.

These companies are creating profiles on individuals, some of which are incredibly detailed.  An example of this, is a profile of a potential seller including information about his topiary collection and where he proposed to his wife.  Companies will then create advertisements designed to lure these folks to consider selling.    Companies can use “big data” to track your behavior,  lifestyle, and finances to predict when you may sell or buy a property.

This is not inherently devious or malicious.  Many companies merely use data anonymously to predict trends.  Even when it is used to identify individuals for marketing, “big data” can be used to custom cater to landlords and real estate investors, perfectly fitting their selling and investing needs.  If you are looking to buy or sell a unique property, this data can be used to match you with a perfect Realtor, who can help match you with the perfect buyer or seller.

While this makes the process of buying and selling more efficient, this level of data compilation comes with serious risks.  One such risk is that large caches of personal data will be stolen by hackers, with more nefarious plans than mere advertising.

But even being the target of too-personalized advertisements can feel invasive.  In 2012, Target analyzed data to identify specific customers who were expecting a baby, then sent those customers advertisements for pregnancy and baby products.  These advertisements were how one man discovered his teenage daughter was pregnant.

In the creepiest scenario, advertisers may have enough data on consumers to directly manipulate their behavior.  Imagine the following situation: a couple’s youngest child leaves for college, and one parent loses a job, temporarily shrinking their income.  In steps a persuasive real estate broker, urging them to sell their high-value home by preying on their insecurity over the loss of income combined with hefty tuition payments.

Another troubling example: a corporate property management and investment firm uses data to identify desperate property owners with equity, who are vulnerable financially.  Their algorithm highlights a landlord with low income who recently filed for divorce, and who is extra vulnerable because their tenant is not paying the rent (known because they just filed in court for eviction).  They then approach the desperate landlord with a quick cash offer, to buy their rental property for 70% of its value.

So how can you protect yourself and your information?  Public information used for big data is just that: public.  But other information can be better protected by exercising the opt out option for various companies that collect data.  Sometimes, the best defense is simple common sense and skepticism: don’t make any large financial decisions (such as selling real estate) without thoroughly doing your homework and collecting multiple opinions.

Related Reading:

Landlords’ Privacy Guide for Safety, Lawsuit Avoidance & Anonymity

Is It Legal for Landlords to Install Video Surveillance Around Rental Properties?

The Growing Specter of State “Exit Taxes” as Residents Abandon High-Tax States

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