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In the 21st century, data is, literally, everywhere. It’s generated every time you buy groceries, surf the Web, or even just drive down the street. Nearly everything you do creates data. That data you create gets used to give you coupons on new products, suggest a Web page, or how to bypass traffic. You, as an individual, create tons of data with every card swipe, button push, or browser click. All that data is the foundation of what many refer to as “big data.”
A whole consumer picture
Big data is the basis for business intelligence, which is about taking all that information and turning it into knowledge to drive better business decisions. Whether it’s data about retail consumers or homebuyers, it’s all the same game.
The business intelligence industry has been analyzing large data sets in corporations for years — decades, really. It’s only now coming to the real estate industry. Wal-Mart had one of the first terabyte data warehouses (big data repository) in the late 1990s — one of the largest in the world at the time. The concept of the data warehouse was a subset of product sales and customer profile data that allowed Wal-Mart to know what to sell and whom to sell it to. It helped shape the course of its business and make billions. That’s big data and how it’s used.
Big data is all about being informed — about who we are, what we do and why — 24/7.
If you look up the definition of the term “big data” on the Web, you’ll see it defined as a data set so large that it’s difficult to analyze using readily available tools. Don’t believe it. The amount of data used in the real estate industry isn’t that large. A single major retailer will generate more sales data in a year than the entire real estate industry will in a decade. However, it’s all relative, and the real estate industry is still trying to figure out what data it has, let alone how to use it.
The point is that big data in real estate is about presenting a “whole consumer” picture. It’s about using data to find out who buys what, when, where, why and how. It’s about finding out who will sell a house — when, where, why and how.
Analysis makes the magic
The presence of big data itself is not where the magic exists. That happens with analysis. The real estate industry today is just evolving from spreadsheets and simple reports. While useful, they’re so 1980s. Right now, we’re on the edge of rapid evolution.
All that data can be used to create tangible insights into consumer behavior using forecasting and modeling software. You may hear the term “predictive analytics” passed around from time to time. Well, it’s already here and you don’t even know it. The companies offering to send postcards to home sellers they “predict will sell their homes in the near future” are using a combination of big data and analysis to create a list of those sellers.
It’s the analysis that makes the magic happen, and by magic I mean identifying customers or providing them better services. For now, the analysis of big data is likely to stay with those who gather it and companies willing to pay for access, such as the lead generation companies. What real estate agents need to know now is that the data is there and it’s available, in some form or another, to those who are willing to use the right tools. Those tools will be in your hands sooner than you think.
The importance and future of big data
Analyzing the data to gain insight into customer behavior will have profound impact on the industry. Even the most basic analysis could be used to increase the accuracy of mailings and emails, which reduces business costs. There are many other advantages, including better customized services, discovery of lucrative market segments, and faster time to decisions.
As big data is used more, agents who put the analysis into practice will see revenue rise, costs drop and market share increase. Those agents will squeeze out those who ignore the data and tools (or fear them). The real estate industry will evolve much more toward corporate practices in the use of customer and business information.
The next term we’ll start to see used frequently is business intelligence (BI). This is the analysis side of big data and where information is turned into actionable answers. There are myriad other terms and concepts coming that are related to BI. My advice is not to get mired in the technical details but in the business applications that use the information to make better decisions. Learn the concepts and how to put them into practice. Doing so will be necessary not just to thrive, but to survive.