The whole of the real estate sector has definitely changed, going through a thorough digitalization first, then moving into far more technologically advanced features, like hyper targeting and, recently, data-oriented features. Is data, therefore, the new trend for the real estate sector? Let's find it out in this guide for the real estate professional who's looking to add a powerful and useful technological flair to his/her business.
What Is Data In Real Estate?
Data may be perceived by a lot of people as an extremely complicated matter but, in the end, it isn't really. Data within the real estate sector can be covered from 2 precise points: processing and acquisition.
With data processing, we intend the data which is used for automation, marketing, audiences targeting and similar. This data is the one which is generated via cookies on websites, by online surveys and so on. This form of data is used, also, for risk management when approving mortgages or other forms of loans and it's the more technical part of what's known as the modern "credit score". Companies like Paypal, Amazon and similar are using this very data for these purposes.
With data acquisition, instead, we intend the usage of programs, native applications or marketing strategies which are made to associate a user to a numerical value (a keyword, a specific behaviour on the site, and so on).
How Can Real Estate Professionals Use It?
If your company or agency offers a number of services ranging from the commercial to the residential sector, having some sort of data acquisition process would be ideal to perfectly plan your user funnel, specifically on your website. Here's how it works.
1. Find a software which works with your CMS (Wordpress, Magento, Shopify, Umbraco.)
2. Precisely set up the software just so users who land on a specific page can be redirected (upon their consent) to another property page, which is very likely to convert their click into a sale. This very process is known as Jupyter personalization mainly because it heavily relies on Jupyter Notebook, a Python library for data science and machine learning.
3. Acquire the user email address
4. Include the address in your email database for future remarketing events/word of mouth.
Doesn't sound complicated, doesn't it? Well, those four steps are (in fact) a brief guide to neural networks being built for retargeting purposes. Data acquisition and processing isn't an extremely technical subject, overall. A company in the UK who focuses on commercial properties for sale has been able to increase their profit margin by over 300% by using Jupyter Python features.
Costs: Should I ACTUALLY Consider This?
Costs for data-oriented strategies aren't low. Even those pieces of software which operate on CMS are falling under a monthly fee which surpasses the "thousands" region. With this in mind, it's very safe to say that having a dedicated data strategy (even minimal) is something which not every business can handle from an economic perspective. It is indeed possible, though, to use minor data strategies (aka retargeting and data control with tools like Jupyter or more simply Google Analytics) to ensure great user experience and potential conversion rate optimisation.
Approaching data for real estate professionals definitely applies to the ones who are able to understand and funnel pieces of data software into a working architecture. Surely related to the digital field of real estate, if you're a professional with highly analytical skills and you're willing to learn a bit of Python, then choosing this path may be the right choice for you.
Paul Matthews is a Manchester-based business and tech writer who writes in order to better inform business owners on how to run a successful business. You can usually find him at the local library or browsing Forbes' latest pieces.
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