Insight Investing Strategies

As it has been said, time is the great equalizer, and as the arena of big data refines, companies that learn to utilize the information correctly have begun to emerge as leaders.

Real estate is an industry that is undergoing drastic changes. A big data revolution is on the horizon. This massive industry that boasts an annual revenue of $235 billion with over 200,000 residential brokerage companies and over 1 million loan officers has been overdue for a major shift. But while the debate rages on about varying commission structures and diverse business models, the real change is coming in the form of big data. Spend any amount of time at a real estate conference these days and you’ll hear about big data. It’s as much of a buzzword as climate change — and just as misunderstood.

As theoretical physicist, Stephen Hawking said, “We are all now connected by the Internet, like neurons in a giant brain.

Data is everywhere and much easier to collect. Every time you swipe a card, push a button or browse a Web page you leave bread crumbs behind. A trail easy to follow if you know how to put the pieces back together.

Big Data Spaghetti Test

Therein lies the problem. Most data companies are nothing more than list optimizers. Looking backward to predict behavior. Much of the data is highly siloed, rendering it ineffectual. Still other companies have residually gathered data from their core product, and, while realizing it has value, have insufficient knowledge of how to use the information. Neither one of these are sustainable business models.

These types of companies continue to change their business approach and modify their practice with the virtual spaghetti test — throwing questionably cooked big data products at the wall in hopes they will stick.

As it has been said, time is the great equalizer, and as the arena of big data refines, companies that learn to utilize the information correctly have begun to emerge as leaders. Data points need to be connected, like puzzle pieces that lead back to the larger picture. Improvement comes in the form of refinement. Using multiple data points and tying them together to target the right buyers is a matter of knowing who they are, when they want to buy and how you can reach them. It sounds simple, but the sheer volume of data requires something more than basic integration and human interaction.

The Promise of AI

One of the most promising solutions lies in the integration of Artificial Intelligence (AI) into data gathering analysis. In the simplest of terms, it can be thought of as automation on steroids. As a result of the recent rise of AI, especially supervised learning and machine learning, the amount of processes that can be automated has risen exponentially.

New Vantage Partners, a strategic advisory firm that guides many

Fortune 1000 companies’ technology initiatives, conducted a survey earlier in 2018. The primary findings of this survey was that 97 percent of C-level executives report that their companies are investing in building and launching big data and AI initiatives. From this survey there was a growing consensus that AI and big data are becoming closely intertwined, if not synonymous.

The corporations surveyed report that they have direct access to meaningful volumes and sources of data that can feed AI algorithms to detect patterns and understand behaviors. The integration of AI into big data analysis produces a range of business benefits and results in much more accurate ability to predict consumer behavior. In the past year, companies such as American Express and Morgan Stanley have publicly shared stories of the successful use of their AI-analyzed data.

In a recent keynote address, a prominent executive within Mellon Bank stated that the availability of big data technology, combined with the volume of information, is unparalleled to what was available via paper in the past. He further punctuated his speech by saying with the additional mixture of artificial intelligence analysis, businesses are going to see an unprecedented accuracy in predicting customer behavior.

Likely.AI’s Big Data Approach

Likely.AI is an artificial intelligence company specifically designed for the real estate and mortgage industries that leverages our patent to utilize AI and big data to build schemas to meld the data for better, proven results.

We have assimilated data for 155 million properties with a 225-million-record demographic dataset that includes micro and macro market influencers and a unique mix of individual and household-level demographic data. We have used this wealth of information and automation to create several lead-generating products for the real estate industry, the initial one was consumers with a desire to sell. Using this technology, Likely.AI scores every property in the U.S. based on the likelihood of a sale in the near future. Once the property reaches a certain confidence threshold in our deep learning models, we provide this valuable lead to real estate professionals. Using this strategy, Likely.AI can provide solutions leveraging its proprietary database to effectively generate new business for real estate lenders and other professionals.

Likely.AI has been developing the most effective ways to generate business with AI and big data for real estate professionals and mortgage originators. Our proprietary data lake allows us to offer solutions others can’t. Some leverage AI and others just utilize big data in very creative ways. At Likely.AI we offer intelligence as a service.

So, as you develop out your strategy with big data in the near future, consider those organizations that utilize artificial intelligence and deep learning to produce results.

As Peter Sondegaard from Gartner Research said, “Information is the oil of the 21st century, and analytics is the combustion engine.”