Personalization For The Win!

Redi Match blog - personalization

As general consumers in the US, people have been trained to believe that products and services should be built for them and customized to their unique needs and preferences.  This carries true across a wide variety of industries, including much of offline and at this point almost all of online.  From selecting an automobile, to the content you see online, to the food you order, the theme is your option to choose the right fit for you and to customize the options available.  Choices abound.  Many things that started out as a privilege, like owning a car, have turned into a bevy of choices and a product or service that is customized to your precise specifications.  For the example of car ownership, in today’s environment you have the option to have brokers search the nation (in some cases the globe) to find the car you are looking for that meets your exact criteria with hundreds, if not thousands, of different options for each car model.  Gone are the days when you show up at a local dealer and feel privileged to pick one of the twenty cars on the lot and settle (or walk away happy) with that one in twenty.  Today, at any budget level, thanks to online brokers – eBay, craigslist, CarMax and many others – your available options are almost limitless.

Much of this evolution of personalization comes from the advancements in data and technology.  As data has become more readily available and widely collected, and as technology has allowed for the manipulation of data with quick application of models, personalization can be on demand and predictive analytics can make the personalized product or service available before you even know what you want.  Whether it’s custom playlists for your listening pleasure or stock portfolios custom built to your risk tolerance and interests, personalization is here to stay and is only getting more mature.  

Personalization and customization has been prevalent in real estate for decades.  When searching for your home you have preferences for style, design, architecture and of course location.  This is what your agent or broker will use as parameters to determine what properties they will show you.  Of course, their ability to match you with the best properties on the market is what makes any agent or broker successful, along with service.  

As investing in single family residences becomes more commonplace, this same matchmaking process has been redefined.  From start to finish, how do investors find the right match for their investment needs?  They are likely not as location restricted as homeowners; they care about many of the same property characteristics; and then much much more.  After all, they will be renting the property, therefore it needs to appeal to the future tenants.  Further, property investors need an in-depth financial analysis and comprehensive insights into the neighborhood, the city and even the county in order to make a successful investment.

The number of attributes considered when evaluating residential property go up exponentially when you are looking for an investment. Two of the most important factors when considering investing in real estate are timing and location.  When you are buying a home to live in those two factors mean something completely different than they do to an investor who is purchasing homes as rentals.  Timing for investors does include things such as where interest rates are at at a given moment in time, but it’s typically not as critical as it is for a homeowner who is evaluating what they can afford and locking in a rate for 10-30  years.  Investors are thinking more about timing from the perspective of possibly flipping the property, or adding it to my long term hold portfolio.  In either scenario, how much time will it take to get the property flipped, to rent it, or to rehab it then list it for rent.  And, how do you determine vacancy rates in a particular neighborhood?  In terms of location, homeowners are often familiar with an area and rely on local knowledge and time spent.  For investors, local knowledge often plays a role but as a fund grows and as diversification or expansion becomes critical, investors need to commit to research.  Further, from a location standpoint, economics comes into play.  Economic factors such as employment rates and sectors, household incomes, vacancy rates, housing supply, new home building statistics and more.  The importance of these data points are only one level of research that needs to be done before an investment is executed upon or even before a zip code or neighborhood is selected.  

This all leads back to personalization.  Economic trends or neighborhood characteristics that appeal to one investor do not necessarily appeal to the next.  Time horizon, location and economic outlook are unique to each investor or fund and they have the luxury (and tall task) of selecting from properties across the country.  This is where data and technology will again dramatically disrupt another industry.  Investing in residential real estate, specifically single family residences, is difficult.  Every property is unique and neighborhoods can be vastly different from one block to the next.  If you look at what Zillow has done for home searches, what Google satellite images have done for street views you can start to imagine how much data is available that can be harnessed to provide decision intelligence that is personalized to individual investment strategies.  Redi Match has begun to scratch the surface of personalizing property matches to your investment strategy, leveraging robust sets of data and machine learning technologies.  Our upcoming releases will provide the personalization and matching technology that, to date, has not been available to investors within residential real estate.  We continue to see technology make huge strides in real estate and believe that it will be beneficial to a much wider audience as personalization becomes more pervasive in real estate technology.  We are pushing the boundaries and bringing these advancements to every corner of residential real estate.  The sector is (finally) changing quickly!

#machinelearning #AI #realestate #investing

 

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