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Real Estate Big Data

Surprise nuggets in the 2020 home buyer, seller generational trends report

(REAL ESTATE) You may think you know generational behaviors, but there are interesting trends emerging as millennials begin to behave more like the Silent Generation.

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Everything you assumed about annoying millennials like me is apparently wrong. Sure, I had avocado sprouted grain toast and local fair-trade coffee for breakfast, but don’t let that ridiculous exterior fool you… it turns out that millennials are increasingly behaving more like the Silent Generation than any other.

According to the National Association of Realtors’ (NAR’s) 2020 Home Buyer and Seller Generational Trends Report, there are some shifts in consumer behavior that are worth noting, to better serve the market.

Dr. Jessica Lautz, VP of Demographics and Behavioral Insights emphasizes that “it is really important not to pigeon hole a buyer just based on their age,” and that it is important to remain informed of the trends.

For example, the aforementioned millennial generation behaving like the Silent Generation. Dr. Lautz notes, “when buying a home, they want to be close to friends and family,” a behavior typically emphasized by retirees, and that “they’re buying at affordable price points, and using referrals to find agents at high rates.”

Additionally, it’s not just Boomers that stay put – millennials want to own homes, and they intend on planting deep roots, Boomer style. The study also indicates that millennials are relying more on savings to purchase their homes than past generations.

Another surprise gem in the data amassed by NAR? Dr. Lautz observes that while most people think millennials want to bebop around inner cities, “lots of younger millennials are moving to small towns and suburbs where they can find affordability.” #MythBusted

In 2020, the real estate referral method looks a lot like 1920 in that there is a high level of trust in personal referrals. That’s worth noting if you’re spinning your wheels to attract new clients when business is likely to come from your existing clientbase.

It’s not all avocados and sunshine, though.

Dr. Lautz said, “there is a sad data point in that Gen Xers are still struggling to come out of the recession when it comes to home buying trends. They’re back on their feet financially, but many were underwater, which stalled the selling of their property, and they’re now recovering, but they have a longer period of time they have to wait before their finances are in order to do that.”

In other words, the recession has had a lingering impact on this middle child of a generation.

The 2020 generational trends report is something every industry practitioner should spend time getting to know (at least, practitioners that prefer to make money).

Below are the highlights – read them first, then dig into the full report here.

Characteristics of Home Buyers

  • 21% of homebuyers between the ages of 22 to 29 are unmarried.
  • 22% of homebuyers between the ages of 65 to 73 are single females.
  • 31% of homebuyers between the ages of 40-64 purchased a multigenerational home (will home adult siblings, adult children, parents, or grandparents).
  • 33% of homebuyers between the ages of 22 to 29 stated that they lived with parents/relatives/friends who paid and did not pay rent before their living arrangement.

Characteristics of Homes Purchases

  • The oldest and the youngest age groups (74 to 94, and 22 to 29) were most likely to purchase a new home for the amenities of new construction communities (though a small share of buyers aged 22 to 29 purchased new homes).
  • 25% of homes purchased by homebuyers within the ages of 22 to 29 were located in a small town.
  • 43% of homes purchased by homebuyers between the ages of 55 to 64 were located in a small-town or rural environment.
  • 64% of homebuyers between the ages of 22 to 29 stated the overall affordability of the home as a factor was influencing neighborhood choice.
  • 53% of homebuyers between the ages of 22 to 29 and 74 to 94 stated convenience to friends/family as a factor was influencing neighborhood choice.
  • 46% of homebuyers between the ages of 30 to 39 noted the quality of the school district as a factor influencing neighborhood choice.
  • 38% of homebuyers between the ages of 30 to 39 stated convenience to schools as a factor influencing neighborhood choice.
  • 29% of homebuyers between the ages of 65 to73 reported convenience to a health facility as a factor influencing neighborhood choice.
  • 36% of homebuyers between the ages of 74 to 94 stated convenience to a health facility as a factor was influencing neighborhood choice.
  • The median expected length of tenure in homes purchased between the ages of 40 to 73 is 20 years.

The Home Search Process

  • 63 % of homebuyers between the ages of 22 to 29 stated finding the right property as the most challenging step of the home buying process.
  • 60 % of homebuyers between the ages of 30 to 39 reported finding the right property as the most challenging step of the home buying process.

Home Buying and Real Estate Professionals

  • 92% of homebuyers between 22 to 29 and 30 to 39 bought a home through a real estate agent or broker.
  • 85% of homebuyers between 22 to 29 used a real estate agent to help understand the buying process.
  • 51% of homebuyers between 22 to 29 found a real estate agent through a referral from friends or family.
  • 45% of homebuyers between the ages of 30 to 39 found a real estate agent through a referral from friends or family.

Financing the Home Purchase

  • 27% of the homebuyers between 22 to 29 stated gift from a relative or a friend as the source of their down payment.
  • 6% of homebuyers between 22 to 29 stated loan from a relative or a friend as the source of their down payment.
  • 46% of homebuyers between 65 to 73 stated savings as the source of their down payment.
  • 56 % of homebuyers between 65 to 73 stated proceeds from the sale of the primary residence as the source of their down payment.
  • 39% of homebuyers between the ages of 74 to 94 stated savings as the source of their down payment.
  • 52% of homebuyers between 74 to 94 stated proceeds from the sale of the primary residence as the source of their down payment.
  • 30% of homebuyers between 22 to 29 stated saving for a downpayment was the most difficult task in the buying process.
  • Home purchases delayed at a median of 5 years between the ages of 40 to 54, due to difficulty saving.
  • 7% percent of homebuyers between 40 to 54 reported having their buyer application rejected by a mortgage lender.
  • 15% of the homebuyers between 50-54 stated they’d sold the distressed property.
  • 82% of homebuyers between the ages of 22 to 29 reported they view their home as a good financial investment.
  • 84% of homebuyers between the ages of 30 to 39 stated they view their home as a good financial investment.

Home Sellers and Their Experience

  • 28% of home sellers between 30 to 39 stated their home was too small as the primary reason for selling their previous home.
  • 21% of home sellers between 40 to 54 indicated their home was too small as the primary reason for selling their previous home.
  • 19% of home sellers between 55 to 64 stated the primary reason for selling their previous home was to move closer to friends and family.
  • 28% of home sellers between 65 to 73 stated the primary reason for selling their previous home was to move closer to friends and family.
  • 33% of home sellers between 74 to 94 stated the primary reason for selling their previous home was to move closer to friends and family.
  • 17% of home sellers between 74 to 94 stated home was too large as the primary reason for selling their previous home.
  • 11% of home sellers between the ages of 40 to 54 who lived in the home or rented their home to others while living elsewhere, stated they wanted to sell earlier but waited or stalled because the home was worth less than the mortgage.
  • The median tenure of home sellers between the ages of 55 to 64 in the previous home is 12 years.
  • The median tenure of home sellers between the ages of 65 to 73 in the previous home is 12 years.
  • The median tenure of home sellers between the ages of 74 to 94 in the previous home is 12 years.

Home Selling and Real Estate Professionals Methodology

  • 21% of homebuyers between the ages of 30 to 39 stated helping the seller find ways to fix up home to sell it for more as the most wanted service from real estate agents.
  • 20% of homebuyers between the ages of 40 to 54 stated helping the seller find ways to fix up home to sell it for more as the most wanted service from real estate agents.
  • 23% of homebuyers between the ages of 55 to 64 stated helping the seller market home to potential buyers is the most wanted service from real estate agents.

Real Estate Big Data

Shadowmap shows where the sun and shadows are at any property, any time

(TECHNOLOGY) It seems like such a small detail, but for a client desperate to know where the sun and shadows are for energy efficiency, gardening, or what have you, Shadowmap is your tool for an immediate answer.

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For something that we all experience daily, sunlight can feel oddly personal – especially if you don’t feel like you’re receiving enough of it at the right time in your house. If you’ve been in the market for new data or a tool to help draw in real estate clients – or just appeal to your current ones – Shadowmap may be your saving grace.

Shadowmap, a tool from creators George Molzer and Simon Mulser, is a deceptively simple product with some really cool applications: It allows you to map out solar shadows in any environment using “3D data in a worldwide interactive maps app.”

The base program itself is free for online use, and it’s extremely easy to use. Simply typing in an address will take you to the property in question, at which point you can drag a slider to simulate the passage of time throughout the day.

Shadowmap’s “Pro” subscription comes at around $10 per month (or $100 per year) and allows you to select specific dates (both past and future) as well as view high-definition visuals; you’ll also receive updates as they come.

Adding this to your toolbox could help convince clients who are on the fence about purchasing certain properties, and it makes for a powerful discussion piece when taking on new clients.

Being able to tell someone exactly how the sun will illuminate certain sides of their property after only a few seconds of research is impressive, and it entails information that many consumers will want to hear whether or not it is at the forefront of their minds.

There are plenty of applications for developers and casual designers, too. Product Hunt cites several different users proclaiming their joy at the creation of Shadowbox, from people who are excited at the idea of Feng Sui to relieved developers positing that the tool will make compliance easier to achieve.

Employees who work in the elements are similarly intrigued: “As I work with Wine Imports the use-case for weather-sensitive products such as Rosé are clear,” says Andreas Bøggild.

Of course, the technology is only as accurate as past weather conditions can dictate, but Shadowmap is a welcome alternative to standing in the garden and looking up at the sky for hours to see when the sun will finally hit the living room window.

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Real Estate Big Data

After four months of decreasing home sales, there’s a 1.4% blip upwards

(REAL ESTATE) With massive annual gains and slight monthly gains, existing home sales rise 1.4% in June, but the market remains plagued by tight inventory levels.

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Between May and June, existing home sales (contracts signed) rose 1.4%, after fourth consecutive months of declines and a 22.9% increase from June 2020, per the National Association of Realtors (NAR). The average days on market nationally was only 17 days.

After months (years) of restricted inventory levels, and an entire sector holding their breath for any relief, inventory levels rose 3.3% in June. The market remains blue in the face while holding said breath, but even this slight improvement is a sign of hope.

Meanwhile, the median home price hit $363,300, rising 23.4% over the year, the second highest increase on record since January 1999. All-cash transactions are increasingly common as folks increase their wealth by cashing out of the stock market and/or their housing equity, continuing to nudge out many first-time buyers who rely on traditional mortgage options (despite interest rates remaining historically low).

NAR’s Chief Economist, Dr. Lawrence Yun said, “Supply has modestly improved in recent months due to more housing starts and existing homeowners listing their homes, all of which has resulted in an uptick in sales. Home sales continue to run at a pace above the rate seen before the pandemic.”

Dr. Yun noted that home prices won’t decline with still-tight inventory conditions, but expects price appreciation to slow by year’s end. “Ideally, the costs for a home would rise roughly in line with income growth, which is likely to happen in 2022 as more listings and new construction become available.”

Existing home sales in the Northeast rose 2.8% in June, 3.1% in the Midwest, 1.7% in the West, and remain unchanged in the South.

So what’s next for the housing sector with rising prices and restrictive inventory levels?

“NAR continues our conversations with policymakers and leaders from across the industry in an effort to boost housing inventory and increase access to safe, affordable housing for all Americans,” said NAR President Charlie Oppler. “As the nation’s economy continues to recover from COVID-19, securing policies that are in the best interest of U.S. consumers and homeowners remains NAR’s priority.”

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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.

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