Real estate has come a long way from its days of unreliable data, unscrupulous brokers, and lack of transparency. Today, technology is increasingly playing a vital role in real estate to optimize investments and maximize returns. For example, ProspectNow uses predictive analytics to identify properties that will be for sale soon. This gives brokers, agents, and investors a leg up over their competition. Not familiar with predictive analytics? This page breaks down commonly used terms in modern real estate.
ProspectNow has been around since 2008. Ever since its inception, the platform is dedicated to providing reliable real estate data that helps you close more deals. Easy to use, trustworthy, and at the cutting edge of real estate technology, ProspectNow helps you make more money from your investments. Get access to residential and commercial real estate data for free today!
Real Estate Glossary of Terms
This is the branch of analytics that uses data modeling, data mining, and machine learning to predict future events. Predictive analytics uses current and historical data to predict future outcomes of events. For example, with the help of predictive analytics, ProspectNow can identify the properties that are likely to be for sale soon. Typically, a data mining approach can be categorized as predictive analytics if the focus is on prediction instead of description and the outcomes are of immediate business relevance. For instance, analyzing if a particular ad set will resonate with your audience is an example of predictive analytics.
Property data is information pertaining to physical property in the real world. For this definition, we define a property as a piece of land or a building that belongs to a person or entity. A typical property data set will have the following information:
- Location of the property (i.e. the physical address)
- Type of property (e.g. residential, commercial, or mixed-use)
- Ownership details
- Age of the property
- Market value
- Sale price
Property data helps make informed decisions when buying or selling properties. It is also useful for predictive analysis in real estate.
Loan origination is the process of purchasing a mortgage loan from a registered lender. Typically, the process of loan origination involves the following steps:
- Loan application
- Submission of relevant documents by the borrower
- Screening of the documents to verify the borrower’s credit score and financial history
- Negotiation of loan terms
- Processing of documentation
- Loan approval
The process is called loan origination because it’s completed by a loan originator. A loan originator might work for a big lender, such as a bank, or work independently. Independent loan originators can help borrowers find the best loan terms in the market.
Artificial intelligence is a branch of computer science that is concerned with building smart machines capable of mimicking human intelligence. It solves problems without human intervention, thus increasing business efficiency and reducing costs. Artificial intelligence is also helpful in reducing human error and optimization of human resources. Chatbots are a good example of artificial intelligence in use. Modern chatbots can handle routine customer queries with ease. This allows customer care teams to focus on more complex cases. Machine learning and deep learning are subsets of artificial intelligence that are useful for predictive analytics.
AI-powered research uses artificial intelligence to gather intelligible insights from data. These insights can be useful for businesses, governments, or public enterprises. Artificial intelligence allows the automation of various repetitive manual tasks. For example, with the help of robotic process automation, machines can scan documents and validate them, thus eliminating the need for manual intervention. Similarly, it can also mine relevant data from large datasets. With the help of machine-learning algorithms and predictive analytics, mined data is used to derive important insights.
Machine learning is a subset of artificial intelligence that allows machines to learn from past experiences and improve on their own, with no additional programming. Some prominent examples of machine learning are digital assistants that respond to our voice, self-driving cars, and recommendation engines for movies and music. ProspectNow’s predictive analytics also uses machine learning algorithms to accurately predict the properties that will go on sale in the future.
Machine Learning Models
A machine learning model is a program that is trained on a specific data set. The program learns from the data set and then makes predictions for a dataset that it has never seen before. At their most basic, machine learning models can be categorized into supervised and unsupervised learning models. You can further break supervised machine learning models down into regression models and classification models. Neural Network and Random Forest are examples of supervised machine learning models. Clustering is an example of an unsupervised machine learning model.
Public domain is content that is not protected by any copyright law. Works in the public domain can be freely shared, copied, or republished by anyone. The content might enter the public domain when:
- The duration of copyright expires
- A content creator puts work in the public domain with no copyright restrictions
- Data deemed important for public transparency. For example, quarterly reports of companies listed on the stock market are available in the public domain.
TCPA stands for Telephone Consumer Protection Act. The act came into effect to eliminate intrusive calling practices by telemarketers. To be TCPA compliant, telemarketers need to have express consent of the dialed party. TCPA prohibits telemarketers from using auto-dialers, pre-recorded messages, and text messages as a marketing outreach strategy unless they have consent from the dialed party. Users can file lawsuits against companies that fail to comply with TCPA.
CAN-SPAM stands for Controlling the Assault of Non-Solicited Pornography and Marketing. The CAN-SPAM Act came into effect in 2003 to establish the rules for commercial emails and messages. Every email that violates CAN-SPAM compliance can attract a penalty of up to $43,792. Here are the dos and don’ts for CAN-SPAM compliance:
- Don’t use misleading information in the header
- Don’t use misleading subject lines
- Include your physical address in every email you send
- Provide a simple way to opt-out of your emails
- Handle opt-out requests promptly
MLS or Multiple Listing Service is a database of available property listings created by real estate brokers. It is a shared database that has to comply with the rules set by the National Association of Realtors. Real estate agents need to pay a membership fee to gain access to an MLS. Typically, an MLS will have important property data such as location, neighborhood details, photos, and square footage. An MLS is useful for buyers and brokers. The consolidated database allows buyers to quickly search through available properties. Therefore, it also levels the playing field for real estate brokers.
A motivated seller is a property owner who has a strong need—not just a desire—to sell their property. Very often, motivated sellers will settle on a much lower price or flexible financing terms, which makes these properties more lucrative to buyers. Several factors can drive property owners to become motivated sellers, such as the following:
- The property owner is in foreclosure
- A property owner cannot keep up with property taxes
- The property is in poor shape and needs extensive repairs, which are beyond the means of the property owner
- A property owner has inherited the property and has no inclination to spend any money on repairs or upkeep
- The property owner is in the process of purchasing another property and their financing is contingent on the sale of their own property
LLC or a limited liability company is a corporate structure where the owners are not personally liable for the company’s liabilities or debts. An LLC has a more formal structure than a partnership or a sole proprietorship. It also offers owners more protection against liabilities compared to a publicly listed enterprise. By default, LLCs don’t pay federal corporate taxes. Instead, profits and losses are shown as individual incomes of owners in their tax returns because an LLC is not a recognized tax status.