Data And Digital Disruption In The Investment Property Industry

Data And Digital Disruption In The Investment Property Industry

Data and digital disruption in the investment property industry

The central tenets of property investing have generally been, and will likely always be: where to acquire property, when to develop, and when to sell. While industry expertise and experience has been able to make a successful venture out of it for many, the modern reality is that big data and digitalisation are a necessity for good investing in the 21st century. Data and technology has had a role in property investing in the past, but it was traditionally used for the transaction alone, for evaluating the property and finding its value, with relatively rudimentary figures that didn’t take much of the guesswork out of the process. Nowadays, data can have a positive impact on nearly every stage of the property investing, and in ways that have never been thought of. 

Granted, anyone thinking about relating numbers to property investing would see that the intricate and multidimensional nature of property leads to millions of data points that are difficult to filter through. This has created a need for tools and methods to guide property investors and lead to smart, evidence-based decisions - and that need is slowly being satisfied. Not only has the property world changed in terms of what data is available, but innovative products to break that data down are also appearing every year. Data and digitalisation have sped up the decision-making process, allowing investors to consider and chase opportunities at a much faster rate than in the past. 

A new way to invest

Where 10 years ago a property investor might have been given general data or information about the project or area that they’re looking into, today that same investor can get access to much more granular and contextualised data. Whether it’s rent figures, comparisons to similar projects, or market demand data, these days the investor is getting much more specific and relevant data.

Furthermore, there are better tools and analytics to make more informed decisions than ever before. There’s a wealth of options available online, and any modern investor is behind the eight ball if they don’t integrate some element of data analytics into what they’re doing. They can choose to engage with companies that offer premium AI and machine learning tools to find patterns and opportunities in the market, or they could take their own data and find the variables that are important to their aims, even building proprietary predictive models to find value. The cost of these options - from in-house data processing and analysis to using a paid tool or platform - may be high, but the benefits should be fully considered from greater risk management, lower transactional/operating costs in the long-term, and of course, better returns from investments.

The rise of non-traditional data

With modern technology and capability to track new types of data, “non-traditional data” has become an important part of property investing. It’s an ever-expanding field of variables that differs from the traditional data points that most people would associate with property investing and real estate. The traditional data includes things such as market performance (household incomes, renter numbers) and the physical features of the property (square metres, stories, etc).

The non-traditional data points can be as varied as the proximity to a supermarket or popular chain store (think McDonald’s or Starbucks), the average Yelp/Zomato rating of cafes in the area, or even the potential number of permits/assessments needed for things like swimming pools or renovations. Analysis from McKinsey has shown that these non-traditional data points, if used with the correct weighting and mix for the specific project, can be much more predictive than traditional measures.

Ultimately, having these non-traditional data points on-hand can give investors a predictive tool, and an advantage, by seeing opportunities early and often. Tools such as Skyline AI leverage these non-traditional data points - collecting and analysing everything from nearby restaurant data to crime statistics for over 400,000 properties - and provide users with predictions of property value and other insightful outputs. Investors could even collate their own non-traditional data in areas of interest to them, and apply that to the valuation and discovery process. The non-traditional data points represent a promising new frontier for evaluating a potential property investment. 

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