Many people fear the risks involved with real estate investing. However, those who are uncertain about making real estate decisions can use supportive real estate data, which can now be accessed through various online platforms.
For real estate data to make sense and be useful for decision making, it needs to be properly analyzed. Data analytics for real estate have had a huge influence on real estate investing in recent years, especially when it comes to finding an investment property. While most of the decisions in real estate investing were once determined greatly by first impressions and hearsay, real estate data analysis is rapidly becoming the primary factor in the process of decision making.
Real estate data analytics can be used to accurately predict future market trends and risk. So by using analytics, beginner real estate investors can find low risk investments with high returns, putting them on the path to success. Let us look at the types of real estate data analytics and how they can reduce the risk of buying an investment property.
Types of Real Estate Data Analytics
There are two types of real estate data analytics, both of which should be used when finding an investment property:
1. Traditional Real Estate Analytics
Traditional analytics is where real estate data is collected and analyzed so as to get a retrospective view of what went wrong with an investment property and why. For example, if real estate investments in a particular neighborhood were not profitable yet the real estate market was booming, real estate investors can investigate why that was the case with traditional analytics. This will help them figure out the changes that would need to be made for it to be successful. Even though traditional analytics are helpful, they are usually not the main focus for real estate investors.
2. Predictive Analytics
When it comes to real estate investing, identifying past trends using big data is critical. But what about figuring out how an investment property will perform? That’s where predictive analytics comes in.
Predictive analytics breaks down past real estate data to predict future trends. It has greatly changed the approach to real estate investing and significantly improved the game. Since predictive analytics create a reliable forecast of the future, it also takes into account the risks. It helps a real estate investor to assess future risks and property values. This provides the investor with insight on whether to invest in a particular property or not. Many real estate investors are now using predictive analytics to predict future trends in real estate markets and find low risk investments. This greatly increases their competitive advantage.
How Real Estate Data Lowers the Risk of Investing in Property
Real estate data helps investors to improve their decision making and lower risk in the following ways:
1. Understanding real estate markets
Real estate markets are quite complicated and always changing. Being able to predict the future of the real estate market is, therefore, critical. Through real estate market analysis, real estate investors can understand housing markets. They see the markets that are doing well and why. Real estate market forecasts provide investors with information about the future potential of a particular market. Therefore, investors can put more focus on the best real estate markets and steer away from those that are failing. This is done through analysis of factors such as appreciation rate, return on investment, and the predicted job growth of various markets.
2. Finding the best neighborhood
After finding a suitable real estate market, you can use real estate data analytics to find the best neighborhoods in that market. Not all neighborhoods in a housing market will be lucrative. You may have the best investment property but if it is in a bad area, it won’t be profitable. By performing neighborhood analysis with reliable data analytics, you will be able to find the best neighborhood to invest in.
3. Finding the best investment property
Once you have settled for a specific neighborhood, you can use residential real estate data to find your ideal rental property. Investors can get projections of their expenses, income, and expected appreciation. By conducting investment property analysis with this kind of real estate data, you will be able to find a positive cash flow property that is in line with your rental strategy.
4. Identifying target tenants
A rental property investor can also use real estate data to identify potential target tenants. Through predictive analytics, you can determine the makeup of your target tenant, reducing the risk of vacancy. This will help you know the target groups you need to be focusing on for your rental properties, i.e. young families, single professionals, university students, etc. In addition, this information allows you to do focused marketing when finding new tenants.
You can also learn about the possible changes in the future when it comes to tenants. Will the neighborhood have a consistent flow of potential tenants? Will the composition of the future tenants change completely or remain the same? You can even predict the occupancy rates of specific neighborhoods in the coming years and the vacancy risks.
Where Can You Find Real Estate Data?
Mashvisor can help you lower the risk of investing in property with real estate data analysis. With Mashvisor’s predictive analytics, you will be able to make wiser investment decisions, identify the most profitable neighborhoods, find the best investment properties, and reduce risk.
To start looking for and analyzing the best investment properties in your city and neighborhood of choice, click here.
Bottom Line
Real estate investing, like any other investment, is not free of risk. However, real estate data is having a huge influence on property investing as far as lowering risk is concerned. Proper analysis of data can provide you with a detailed and accurate picture of the real estate market you want to invest in. This will help you find low risk investment options and give you a competitive advantage. It is all about finding real estate data and analyzing it to fit your specific needs.