Tag: Real Estate

The real estate industry has traditionally been a technology laggard, with antiquated systems, ad-hoc processes and manual documentation ruling the roost. However, things are changing, with innovation and tech disruption set to change the fundamental paradigms of the real estate sector.

Can real estate technology advances actually predict property prices?

Leveraging Machine Learning Algorithms to Predict Real Estate Property Prices

Smart purchasers and investors look at the value of the property rather than the price. Just as the price of a stock denotes nothing about its inherent value, and one needs to delve into the PE and other ratios to estimate the value of the stock, the price of a property says little about its actual worth, and one has to dig into the underlying data to get to the true worth of a property.

The opacity and lack of access to underlying information surrounding property hitherto inhibited a proper and objective analysis of the true worth of property. Often, the only information available to the stakeholders is the prices at which previous properties of a similar nature, in the same locality were sold. As such, the asking price for properties has always been subjective, depending on what the seller thinks the property is worth, with a loose estimate of the prices other properties have sold in the locality and other subjective insights constituting the basis for asking price.

However, things are changing, and changing fast. Real estate data sets are growing larger and larger with every passing day, every single day, thanks to the ever-improving computing power and cloud storage capabilities.  Smart retailers and other stakeholders have already deployed several new tools and services that leverage such data, and many more tools and services are in the offing.

The National Association of Realtors estimates about 42% of buyers looking at property online as the first step in their home buying process. Most of them now delve into further details, such as the crime rates in the neighborhood, availability of public transit, the profile of local businesses such as gyms, groceries, restaurants, and several other factors.

It gets better. Machine learning now infuses objectivity and transparency in property pricing, besides promising a scientific basis into price fixation of property.

Machine learning models, comprising of hundreds of explanatory variables, offer insights into almost every aspect of a specific property, to a very a high level of accuracy and objectivity. Such models scour through piles of data and are capable of not just identifying an accurate price for the property, but also identifying hidden gems among the swathes of properties available for sale. Buyers and may use such insights to quote a fair and accurate price for the property, Sellers may likewise quote a fair price and sell their property faster, without the risk of under-selling themselves. Banks and financial institutions may use the insights to offer loans based on the predicted future value.

Related Reading: How Top Real Estate Companies Leverage Technology to Soar New Heights.

Identifying Correlated Variables

Home buyers and investors often end up making unscientific comparison among two properties and are often deluded by a lesser price for a property, oblivious to the far inferior value on offer.

While the obvious variables such as the number of bedrooms and square foot area may be obvious and explicit, some variables remain hidden or not too obvious.

Some variables are also closely correlated with others. Some pairs, correlated by nature, such as “Basement finished area” and “Basement unfinished Area,” and other pairs, correlated by deduction, such as “Overall condition” and “Year built” help to identify the true worth of a property relative to the asking price.

Machine learning models not only factor in such variables but also give proper weight to each variable. For instance, two homes may seem similar while considering the obvious variables, but property A may offer far better value owing to the superior quality of plumbing materials used in construction and availability of groundwater compared to property B.

Related Reading: Find how Fingent developed a customized solution to streamline all the processes in a property management life cycle. Check out the case study – Rentmoji: All-In-One Property Management Platform.

Unearthing Seasonal factors

Seasonality has an impact on property prices, but the impact may be subtle or hidden. Crunching historical data makes explicit trends in sales prices associated with seasons. For instance, sales may be more surfing summer months, when the new school year starts, leading to a spike in prices. Such seasonal prices help property investors leverage their buys, property sellers price their property more accurately, or postpone their sell for a few months to get a better price, and more.

Related Infographic: Major Challenges of Big Data in The Real Estate Industry

Identifying the True Value of Extraneous Factors

Buyers always consider the neighborhood of the property, in terms of crime rates, the quality of grocery shops in the vicinity, the proximity of schools, and other factors. However, such analysis is often done ad-hoc, and on a generic basis. The “devil” in the detail may often be overlooked. Machine learning models factor in the extraneous factors at a much deeper level, correlating factors such as frequency of power cuts in the locality, unemployment in the locality, frequency of transportation links, school ratings and more, all of which not only offer an objective and scientific basis on the true worth of the property, but also have an immediate bearing on the property prices.

However, the true value of machine learning is the ability to derive valuable trends and insights from the data. For instance, analysis of police arrests and the chemical compounds in sewers indicate the use of crack cocaine, indicating that gentrification could soon arrive. When the crack is replaced by cocaine, it may indicate that gentrification may already be complete. Such insights may not be available at plain sight and may be impossible to decipher without the analysis of such underlying data.

While real estate technology now makes it easy to predict property prices with a high level of accuracy and objectivity, the challenge is creating the underlying data models in a robust way. The machine learning system is only as good as the algorithm which powers it. Success depends on creating linear models, co-opting all possible categorical variables and historical data associated with each variable.

Related Reading: Read through to find how trending technology is disrupting the real estate industry.

What would it be like if you looked like one of the early men, wearing animal skins for clothes and using flint stones for a fire to cook food over, in the 21st century? Not quite a scenario that you can imagine yourself in, right?

Let me take you to a similar scenario. Several recent surveys* have proved that almost 53% of property managers relied on manual methods to manage all their property. This included paper records or spreadsheet software. Another 9% of property managers did not even have any method at all. Now, why is this not a good thing?

When you know you have a million things to do and you don’t follow any method to organize them in any way, there is every chance that you may mess up the whole thing. In the same way, property managers may have a million things to do and there has to be some method that they can use to organize their activities. They also need to be able to do it in the most efficient way possible. In other words, they need to manage all their property in an efficient way.

Property management involves a range of functions from the time a property is lease-ready. Eg. rental or lease management, listing management, tracking prospects etc. It is important to integrate all these functions into a single solution. Using different methods to manage each of these functions would only lead to further confusion.

The solution!

A single property management system that has specific features to integrate all the functions related to property management would be the most appropriate solution. One that is cloud based and that can be accessed through a browser or a smartphone.

If you look at the advantages of having such a property management system you will wonder why anyone would consider doing things otherwise.

• Ease of access – when all verticals of property management such as leasing and rental management, lead management, maintenance etc. are handled from a single solution through separate modules, it makes it easy for the managers to access information easily.
• Better integration and transparency – when all the processes related to marketing, sales, accounting etc. are handled in one platform there would be better integration and transparency between the departments.
• Aid to on-the-go managers – integrating with mobile platforms as well, it enables on-the-go managers to access information, make or accept payments etc.
• Cloud features – being cloud based, it has advantages like real-time availability of information & communication, lesser chances of loss of data, reduced time & effort in managing properties on the whole, all contributing to effectiveness and efficiency.
• Wider reach to your property – syndication with listing partners and other third party engines makes the processes of listing and accounting etc. much easier and gives your property a much wider reach.
• Provision of useful insights – easy generation of reports provides necessary insights for management.
• Reduction in expenditure – minimizing the use of manpower and/or deployment of separate management systems for each vertical, the overall expenditure is reduced.

Customization is the key

These advantages or features may be customized further to suit the different requirements of businesses. As a matter of fact, customization is the key to any management system becoming successful. Eg. the different modules may be customized to have extensive features depending on the workflow.

Thus, I would say, a good property management system will have the above mentioned general qualities plus the necessary customizations. A regular Property Management System is something that is available easily, but the best one would be, one that can be aligned with the business structure of an organization or property manager and not one that would necessitate the alignment of the business structure, with the system.

* Source – Apartment Management Software BuyerView 2014 from Software Advice

From a recent survey conducted by the National Association of Realtors (NAR), it was found that only 27% of agents and 21% of brokers have invested in technology in the last 12 months to improve their business efficiency. Some of the major areas of investments were for updating existing software systems, databases, CRM solutions or purchasing hardware such as electronic tablets.

So, there is a lack of usage of technology among real estate companies, as is evident. This could be the reason why most companies lack efficiency.

Using appropriate technology for the various activities in your business could make a huge difference. If you still depend on traditional methods of management for your processes, you could be making a big mistake.

Here are some mistakes you might be making in your real estate business:

In Marketing and Sales

• Lack of a proper method for management and aggregation of leads – Leads get generated from various directions in a real estate company dealing with sales and marketing of properties. They make use of several listing sites like Trulia and Zillow and other MLS sites. So the leads generated are all over the place. There is no proper method to aggregate these leads. This causes confusion and even loss of opportunity sometimes. This is where technology could be used to manage the leads generated and ensure that the right leads are followed up.
• Too much time being taken for conversion of a lead into a sale – There are 2 areas of concern in this regard.

One is the time taken to reach the prospective client after generating a lead. Most companies take too long to contact the lead. You should contact them as quickly as possible or else your competitor is going to get them.

The second concern is the lack of a proper method to show the client all available options of properties to choose from. For most companies, there is no proper database of properties to show the clients, as and when they require. The lack of a proper database causes delays in finding other options for the clients in case they are not satisfied with one.

Again, technology could solve these two issues. There could be a mechanism to automate contacting the lead once generated and there could also be a mechanism by which the prospective clients get to see options at their convenience, preferably on a mobile device or tablet.

After Contacting a Prospective Client

• Inefficient handling of initial paperwork – Most companies make the mistake of making it difficult for the customers to fill out the application etc. If the process is complicated, chances are that the customer might ignore it. Technology can help make the whole process faster and easier for the customers. Online information capture can be a quicker way. Of course there are others.
• Lack of a proper method for keeping track of leads contacted – As the leads are contacted, there should be a proper way to keep track of the ones engaged with and the ones not contacted at all. Most companies fail to keep track. As a result, they do not know whether they are losing out on contacting any or whether any client should be followed up with. Organizations must utilize advanced technologies to keep this on track. Once the process of paperwork is also made quicker, then the whole process of initial engagement with the clients also becomes faster. There will be lesser chances of losing out on leads.

Collection Of Payment

• Lack of a proper method to manage collection – Whether it is leasing out or renting, the collection of the payments from the tenants, when they become due, is something that has to be managed with utmost care. All payments have to be collected on time and if there are defaults, they have to be followed up effectively. Most companies fail to do so. There could be a mechanism to keep track of all this.
• Lack of an efficient payment method – The tenants need to make the payments on time and for that, they need to have an easy and efficient method by which they can make the payment from wherever they are, preferably from a mobile device. There could be a mechanism to facilitate that and integrate it with the tracking system for better efficiency.

Maintenance Management

• Lack of a proper method for management of maintenance issues – As and when maintenance issues arise, they need to be solved as soon as possible. Otherwise, it will lead to dissatisfaction and complaints on the side of the tenants. Most companies make the mistake of taking too long to address an issue mainly as a result of not notifying the right people on time. Since there are several people involved in the whole process, it can cause further problems. There could be a mechanism to automate the whole process right from the raising of a ticket by a tenant to contacting the relevant vendor to fixing the problem. For this purpose, there should also be a proper database of vendors available to the companies, again something which most companies ignore.

Credit Verification

• Inefficient methods of carrying out verification – Before choosing the tenant, the credit verification has to be done for the prospective tenants. Most companies follow the manual method of having the pre-tenancy form filled out by the tenant, then subscribing to a credit checking agency and then requesting for the credit report. If all these processes are automated, it would be much simpler and would save a lot of time.

MIS and Reporting

• Inefficient management of various departments – For the management to look into all these aspects in a real estate company, may be a difficult task. Most companies fail to make use of Management Information Systems for this purpose. If the manager has a system to keep a check on the different areas of the company and generate relevant reports on the activities of each department, it can easily be made sure that efficiency is maintained at all times.

Cloud Computing

• Not making proper use of the cloud – Cloud computing makes it possible for any concerned person to access their relevant information, from anywhere, at anytime. Most companies do not make use of this facility. All the information is usually stored in several places to make it accessible. As a result, there would be confusions. To avoid this and to cut overall costs of storage, cloud computing is an efficient method.

Technology is slowly, but definitely becoming mainstream. According to surveyed respondents of the PwC, the overall fear factor about technological disruption is easing. Most issues faced by real estate companies can be solved with technology. Life of a real estate professional would be much simpler if technology is used.