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Real Estate Big Data

5 ways AI is shifting real estate and how to capitalize on it

(REAL ESTATE BIG DATA) Artificial intelligence is bringing a seismic shift to commercial real estate in everything from investing to sales to property management. Hold on!

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Woman working at desk with multiple desktops open to AI tools.

Forget about that location thing. Now real estate – especially commercial real estate – is about data, data, data. As in, Really. Big. Data. And AI is owed a large part of the credit for that.

A dizzying amount of data is being crunched and sorted and searched by artificial intelligence-enabled tools that are changing how deals get done and who will still have a job in the future.

The promise of AI to use data to predict the future is massive – and it promises to do that with more accuracy and efficiency, greater productivity, and less cost for commercial as well as residential real estate.

So, what, exactly, can AI do for commercial real estate? Let’s break it down.

What AI is

To put it simply, artificial intelligence is what lets Amazon’s Alexa talk to you and cars drive themselves. Its algorithms use data to mimic human intelligence, including learning and reasoning. Then there’s machine learning, where algorithms analyze enormous amounts of data to make predictions and assist with decision making. We’re putting them both under the same AI umbrella.

There are four main areas where AI is remaking the commercial real estate industry: development and investing; sales and leasing; marketing; and property management.

Development and investing

With its ability to quickly analyze a staggering amount of data, AI lets investors and developers make better data-driven decisions. More responsive financial modeling helps identify ideal use cases and project ROI under multiple scenarios using real-time data. Pulling in alternative data – say, environmental changes or infrastructure improvements – goes beyond traditional data points and can identify investment opportunities, such as neighborhoods beginning to gentrify. In fact, alternative, hyper-local data has become even more important as COVID-19 continues to upend property valuation models.

AI’s crystal ball comes from recognizing patterns in the data and continuing to learn from new information. It can forecast risk, market fluctuations, property values, demographic trends, occupancy rates and other considerations that can make or break a deal.

And it does all of this more efficiently, more accurately and less expensively than manual methods.

Sales and leasing

There’s a big question looming over AI and automation: Will technology put real estate brokers out of business? The short answer is, “No, but brokers need to step up their tech game.”

Keeping up with – and being open to – tech trends is essential. Clients’ ability to use online marketplaces to search for or list property will only grow, but there still is no substitute for expertise and the personal rapport that builds trust. Chatbots can’t negotiate (yet). Robots can’t show a space and weave details about the property into a story. (If you want to know more about using storytelling in real estate, check out this great marketing guide.)

But Big Data is such a powerful tool that brokers need to know how to harness it for themselves. Having more, and more nuanced, data about clients and properties means brokers can better match the two. They can be more confident in setting sales prices and rental rates. Becoming a “technology strategist” to help clients design an automation strategy for a property would be a great value add to their services. Even just starting out with a website chatbot to answer common questions would add a level of tech-savvy efficiency to communication with clients and prospects.

Marketing

Also a boon of Big Data for brokers: more sophisticated, targeted marketing for themselves, as well as for client properties.

Integrating AI with customer relationship management (CRM) tools brings a richer understanding of clients and prospects that can make choosing marketing channels and personalizing targeted content more precise.

Then there’s data-driven lead scoring. Property intelligence firm Reonomy says its commercial data mine – 52 million properties, 100 million companies, 30 million personal profiles, and 53 million tenants – can be searched in multiple ways to create custom prospect lists. (Check out Forbes.com’s “5 Ways Artificial Intelligence is Transforming CRMs” for a fascinating list of what AI can do, including analyzing conversations for sentiment analysis.)

Property and facility management

The Internet of Things (IoT) is already helping property and facilities managers control and predict energy costs, as well as proactively address maintenance issues. Integrating smart technology like thermostats and sensors with AI also means more efficient space planning. Smart security cameras and wi-fi tracking can create “people heat maps” that can identify underutilized or overcrowded areas.

IBM’s TRIRIGA does that and more. Part of the Watson project, TRIRIGA offers AI-driven insights to show how people are actually using a space and ensure a company has the right amount of space in the right areas. It can also analyze common questions from a chat log, then use that data to create an AI virtual assistant to automatically answer those questions – and update itself as it learns new data. Maintenance requests, room reservations and more can be fully automated.

Strategic space planning has become even more important during the pandemic, as work-from-home trends and safety concerns reshape offices as workers return. (Need ideas for your office? IBM’s Returning to the Workplace guide might be a good place to start.)

Barriers to adoption

There’s no question tech-enabled commercial real estate companies will have a competitive edge. The question is, when will more of them agree enough to adopt AI more widely?

PropTech with and without AI has exploded over the past few years – and that’s part of the problem. In an Altus Group survey, 89% of CRE executives said the PropTech space needs significant consolidation before it can effectively deliver on industry needs; 43% said that is already underway or will occur within 12 months.

Then there’s the undeniable learning curve that comes with any tech tool – an investment of time as well as money. The survey also showed concerns about regulatory requirements for data collection and management, having enough internal capacity, and nonstandard data formats.

Despite those perceived barriers, there’s also no question that innovation and disruption from AI are moving at a dizzying pace – and that commercial real estate needs to keep pace.

Real Estate Big Data

Housing starts stagnate, market conditions are rapidly shifting

Housing starts for April stagnated, marking the second consecutive months of declines, and more renters being left out of this shifting market.

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construction home growth housing starts

Housing starts stagnated in April, down 0.2% from the prior month, according to the U.S. Commerce Department.

The sentiment appears to be that although this marks the second straight month of dips, most are seeing today’s news as a positive, especially as construction of new homes was expected to fall 2.4% in April.

Further, housing starts are up 14.6% from April of last year, driven primarily by multifamily construction.

But it’s worth not getting overly excited, given that permits dipped 3.2% in April which is a forward-looking indicator, so expect starts to continue cooling in a time where we quite need the inventory.

Demand for housing inventory remains high, but the National Association of Home Builders reports today that confidence in the single-family housing market fell dramatically in May, marking the lowest level in two years.

Dr. Lawrence Yun, Chief Economist at the National Association of Realtors said in a statement, “The worst of the housing shortage is ending, but market equilibrium between supply and demand is still some ways off.”

He notes that as mortgage rates increase, builders “are chasing rising rents, with fewer homebuyers and more renters being forced to renew their leases,” noting that even prior to the interest rate increases, rents were rapidly rising and vacancy rates rapidly declining.

Pointing to another market shift, Dr. Yun notes that “Some degree of a return to the office is also fueling back-to-city living where high rises are concentrated.”

That’s a problem.

“Even as home sales look to trend back to pre-pandemic levels after the big surge of the past two years,” concludes Dr. Yun, “inventory will not return to pre-pandemic conditions. That means home prices will get pushed even higher in the upcoming months, albeit modestly, given the supply-demand imbalance.”

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Real Estate Big Data

Home prices jump double digits in majority of American metros [report]

(REAL ESTATE) Housing affordability was already a widespread challenge before current economic pressures were applied, but now home prices are skyrocketing.

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homeownership home prices

As home sales slide and mortgage rates rise, home prices in 70% of 185 measured metros saw a double digit annual increase in Q1, according to the newest data from the National Association of Realtors (NAR), up from 66% in the previous quarter.

The Southern region accounted for 45% of home sales in Q1, and experienced a 20.1% increase in annual home prices (compared to 14.3% just the quarter prior). Home prices in the Midwest jumped 8.5% annually in Q1, while The Northeast rose 6.7%, and the West increased 5.9%.

The median sales price of a single family existing home has now hit an astonishing $368,200.

“Prices throughout the country have surged for the better part of two years, including in the first quarter of 2022,” said NAR Chief Economist, Dr. Lawrence Yun. “Given the extremely low inventory, we’re unlikely to see price declines, but appreciation should slow in the coming months.”

Yun expects supply levels to improve, and for “more pullback in housing demand as mortgage rates take a heavier toll on affordability,” given that “there are no indications that rates will ease anytime soon.”

At first blush, price appreciation sounds lovely to anyone that owns a home, given that it is the largest investment most Americans will ever make.

But regarding today’s report, several homeowners told us that they now feel trapped, and that if they sold their current home, even if they purchased a new house at that same price, they would likely have to downgrade.

Affordability is an ongoing problem weighing down the housing sector. NAR reports that the monthly mortgage payment on a typical existing single-family home with a 20% down payment rose to $1,383 (up $319, or 30%, from one year ago). Families now typically spend 18.7% of their income on mortgage payments (but only spent 14.2% one year ago).

“Declining affordability is always the most problematic to first-time buyers, who have no home to leverage, and it remains challenging for moderate-income potential buyers, as well,” Dr. Yun observed.

Map of how home prices are behaving nationally

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Real Estate Big Data

Office occupancy is on the rise, but its knocking down morale

(BIG DATA) Despite work from home policies still in place and the flexibility some employers are offering, office occupancy is increasing steadily.

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Empty startup office with open floor plan, abandoned while working from home.

As coronavirus numbers dwindle and some officials begin calling for a fourth COVID-19 shot, more and more people previously working at home after being kicked out of shuttered office buildings are returning to the bullpen.

The National Association of Realtors reports that more than 80% of metro areas in the United States have seen an increase in in-person working.

Boston saw the largest office occupancy growth over the past year. Chicago, New York and Washington, D.C. have the most open space.

NAR researcher Scholastica Cororaton says office occupancy is also increasing in areas with a big tech presence. San Jose, San Diego, San Francisco and Seattle lead those areas.

“The rising occupancy in these tech metro areas indicates that tech companies are contributing to the demand for office space,” Cororaton wrote. “Even as nationally, 45% of mathematical and computer workers work from home for at least some part of the time.”

The way companies are returning to work vary and are sparking anger. For instance, Google employees must now be in the office three days a week. On the other hand, Apple begins its return to office plan next week. It starts with employees coming back one day a week which will eventually grow to two days and then three days a week. Apple employees have revolted against the idea and are have threatened to quit.

Many in leadership are pleased with the return to the office to boost productivity and collaboration. However, employees are finding they’re showing up in person to just log in to Zoom again, which has stirred up even more frustration.

On top of the redundancy of work that could be done at home, a study shows only 3% of white-collar employees want to work in the office all week. 86% want to stay home for at least a few days.

Plus, the return to the office drives up costs, with gas prices seeing soaring and inflation at a 40-year-high.

Since the second half of 2021, 30 million square feet of office space has been taken up, however, about 100 million square feet remain.

NAR reports filling that space up again could take through the end of 2024.

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