We use predictive analytics every day and probably don’t know it. You go on Amazon, they recommend items you might like, you ask Siri what the weather is tomorrow, you take a quiz and it tells you what you should major in – you get it. People use predictive analytics to perform better and serve better. So why can’t real estate agents do the same?
Predictive analytics in real estate serves different scenarios. It can help companies and investors find the best locations for their properties based on past performances. It can help sellers identify the criteria needed to appeal to buyers. Buyers are exposed to data on Zillow when they receive emails that include search results similar to previous searches. Real estate investors can use predictive data to estimate their investment property returns. So how can real estate agents play into all of this?
How can an agent used predictive analytics?
We know that agents serve sellers, buyers, investors, and advise anyone about trends, pricing, location, tenants, and more. An experienced agent might know an area like the back of their hand but that doesn’t mean they can’t use data to reinforce the feedback they provide to clients.
Let’s look at an example. The average real estate investor spends three months just deciding on where (as in, city and neighborhood) they should buy an investment property. This is because investors either don’t know a market well enough, don’t want to consider areas outside of their comfort zones, and/or so worried about picking an area that will not provide the returns they’re looking for. This is where agents should come in with data. An agent can speed this process for an investor by presenting an area’s investment performance which can put an investor at ease.
Why do investors care about real estate analytics?
The usual questions an investor might have about a city or neighborhood is the average rental income, cap rate, cash on cash return, and property tax rate. A comparative and predictive analysis of a neighborhood can provide these key calculations. An agent can address these specific questions with specific numbers, “the average rental income in this neighborhood is X.”
A smart investor will inquire about real estate comps but one of the most popular questions in real estate investing is “how do I find real estate comps?” An agent can usually help a lot with this by having access to other agents’ listings. This is another piece of information that predictive analytics can provide and potentially reduce the amount of work for an agent. By combining local rental properties and estimating the amount of rental income based on location and number of bedroom and bathrooms, viewing comps can be made simplified.
A new player in the real estate game
There is also now the vacation rental business which has made its way into the world of real estate investing. Some are buying properties solely for the purpose of listing it on vacation rental websites like Airbnb or VRBO. This might be a new aspect of real estate to agents which is why in this case, they’re better off using predictive and Airbnb analytics. The first question an investor who is contemplating between a traditional or vacation investment properties is, “which strategy will make me more money?” Predictive and comparative data can provide a rental strategy comparison which compares expected traditional and Airbnb rental income and other returns. If agents can become more investor-friendly in addition to having an understanding of the vacation rental market, they can better attend to all kinds of investors.
For those who question the necessity of agents, they should come to realize that the logistics alone are a full-time job, such as making and taking calls and showing the property. The house sells faster, buyers see more options, and there’s a middleman for the negotiating.
The data helps investors and helps agents to help investors
Investors are better off consulting an agent but that doesn’t mean investors can’t explore the data themselves. The use of predictive analytics in real estate does not just help agents to excel but also helps investors get a head-start. Should an investor buy a property outside of their area, they probably won’t have an agent right away but they still have the option to analyze an area and property. By having access to predictive analytics, investors can understand what it’s like to invest in an area without having to visit or be familiar with the area. This is a huge relief and asset for absentee investors, especially for those living in pricey cities and investing in smaller, surrounding cities.
The use of predictive analytics is certainly helpful for everyone in real estate from brokers to a couple looking for their first home. Agents have the opportunity to use such information to reduce their workload and provide meticulous answers when getting a wide-range of questions. Investors can also make intelligent, faster decisions with the numerical data backing them up. Predictive data helps decision making everyday and investors need that type of assistance the most.