As real estate agents, we know that marketing is an integral part of our job. It’s our number one tool to draw new clients in and keep current ones!
With over half of all home sales happening before a listing even goes up for sale, being aware of which types of marketing work and how well they work is crucial to success as an agent.
That’s why I’m sharing my most successful strategies here free of cost or at least very cheap. You get my best advice with no risk!
I’ve tested almost every tactic there is out there and only include things that actually work. And I update this article regularly to refresh the content so you don’t have to worry about that either.
This article will help you do three things:
Understand what predictive analytics means
Discover effective ways to use predictive analytics for real estate
Find out how to add this powerful technology to your own business
Predictive analytics has been getting a lot of attention in media and industry these past few years. But many people don’t really understand what it is or how to apply it properly.
So let’s fix that by learning some key points first. After that, you’ll be able to perform predictive analysis yourself and reap the benefits it can offer your business.
What is predictive analytics?
Prediction is the act of estimating the outcome of a situation based on known information.
How can predictive analytics help real estate?
The field of predictive analytics has experienced a significant rise in popularity in recent years. Companies are creating applications that leverage computer algorithms to predict what actions users will take, or how likely they are to perform a specific action.
These applications then use this information to influence future behavior by giving targeted guidance or alerts. For example, if someone is about to run out of credit cards, an app may suggest avoiding loan applications until these checks have been addressed.
With respect to real estate, there are several ways predictive analytics can be applied. A growing number of companies offer tools that analyze past performance data to forecast whether your house will sell soon or not. This helps you make informed decisions with regard to listing and selling strategies.
Another area where predictive analytics could prove helpful is predicting which potential home buyers are more likely to close on a property later. By identifying such individuals, brokers can begin negotiating from a position of strength, as well as add some incentive for buyers who might otherwise move onto other properties.
What do the numbers tell us?
The most important thing about predictive analytics for real estate agents is that it does not matter whether you are just getting started or have been working in this field for years – there will always be new ways to apply it.
Predictive analytics can seem like very complicated science, but what really matters in the end is how well it works. That is why professionals use it all of the time-you get results!
There may come a day when every agent has access to powerful predictive tools, but until then we must find other ways to hone our skills and predict future behavior.
That is where experience comes into play! A lot of people with less experience tend to think that using predictive analytics would automatically make their job easier, but actually the opposite is true.
By applying common sense to your business and understanding human psychology, you will achieve the same result without relying too heavily on technology.
Who uses predictive analytics in real estate?
Most major real estate firms use some form of predictive analytics to determine if you will be successful as an agent. This is not only for hiring decisions, but also to see what types of agents you would make as colleagues or potential teammates.
Some of the more common applications include determining if someone has overpriced their house, whether or not they are incentivized during listing, if they represent most of the houses around them, etc.
These apps look at all sorts of data points to determine how likely it is that someone will sell their home and why. It becomes very clear when someone may need to consider other professions – perhaps they are in the market to move away from this area or field. Or maybe they just don’t seem like they want to stay in this area long term, which could mean they plan on moving soon.
All these things contribute to predicting when someone will list their home for sale, so your business can get a head start on theirs. These tools have become much less intuitive than telling if someone will definitely buy or sell, but they can tell us something about whether or not people are in a position to buy or invest in homes.
What are the limitations?
A major limitation of predictive analytics for real estate is that it can only predict what will happen next, not give you any insights into why things are happening now. This makes sense because predicting where people live and how much money they have is already difficult as it is!
Analyzing data to determine if someone will pay off their mortgage or not is an excellent example of this. If we looked at past behavior, say five years’ worth, then we could make predictions about whether they will be able to stay within their budgeted amount for another year but we would never know why they ran out of money earlier than planned.
Similarly, analyzing historical patterns of home buying and selling gives us more information about whether someone will buy or sell a house, but nothing about why they might want to do so at this particular time.
These types of applications of predictive modeling use algorithms and statistics to identify trends in large amounts of data. So instead of looking at individual pieces of information, the software looks at how well these patterns match up with other similar situations to determine meaningful conclusions.
What should you do?
The best way to use predictive analytics for real estate is by doing two things: applying it directly to business decisions and using advanced features that require more technical knowledge.
Directly incorporating predictive analysis into business decisions makes sense because this type of data mining is already integrated into how businesses function. Using predictive modeling software, you can create models or equations to predict future outcomes (e.g., whether an individual will remain loyal to their employer), as well as finding patterns in past behavior (e.g., what types of cars individuals purchase).
By analyzing past behaviors, we are able to determine who is at risk and possibly need help with financial obligations or employment. Companies have been using predictive analytics to make business decisions for years, and now it’s time to apply those techniques to your industry!
Using complex math formulas, predictive analytic tools can evaluate different factors to come up with predictions about events or consequences. These tools can be very hard to understand without some background knowledge in statistics, but once applied they can have significant impacts.
What are the results?
Recent developments in predictive analytics for real estate include strategies to determine if you should invest, or begin the process of investing, in a rental property.
This is significant because most people who start their real estate career as investors eventually shift into owning a home. It’s just too expensive to keep renting!
Using predictive analytics, companies have been able to develop algorithms that can tell if someone will be more likely to buy a house in six months than in one year. If it looks like you’re going to purchase a car within the next month, they test out whether you’ll actually do it.
With enough data, these programs can predict when someone will spend money effectively creating incentives for them to do so. This is called reinforcement learning and it works by giving people credit for good behavior.
Why is this important?
In our hyper-connected world, people are spending more time looking at what everyone else is doing online than ever before. This has led to a rise in competition through the use of social media, smart phones with large screens, and now, personal computers for every person.
With all these ways to connect with others, it makes sense that real estate agents will be investing more time and resources into staying connected via the most popular channels. Technology has made it easy to access and implement predictive analytics software products in your business.
What is predictive analytics?
Predictive analytics looks forward to see what things you want to happen next. For example, if you wanted to buy a house, then predictive analytics would determine other houses like yours that have recently sold to predict when or if that sale will occur. It predicts when the sale will happen by looking at similar situations and determining how long it took to sell after buying.
It also determines whether the sale will happen by analyzing factors such as square footage, number of bedrooms, and lot size. All of these things contribute to the price of the home so it can factor into its prediction.
What are some hot markets using predictive analytics?
One of the hottest real estate markets to emerge is in high-income, tax-paying areas with large populations. Properties here typically stay very competitively priced due to strong demand and limited supply.
While this may seem like an adverse situation for potential buyers, it can actually be quite valuable if you know how to use predictive analytics to determine which properties will remain untouched for a while.
Real estate agents and brokers who understand what types of indicators matter most when pricing a house recognize that there’s usually not much change before people purchase property. In fact, they sometimes don’t even look at many other houses until after their own sale!
By identifying important predictors of whether or not a home sells quickly, real estate agents and professionals can learn something about the market by studying how well these markers perform on a previously sold home.
These tools can help them figure out how long it will take to sell your home, and thus what price should be set.