Big Data’s Potential for the Real Estate Industry: 2021

REAL ESTATE DATA FOR FINANCIAL INVESTMENTS

Fueling Real Estate’s Big Data Revolution with Web Scraping

After a slight dip in 2018, the US real estate market had started stabilizing. However, the global pandemic shattered the world order, and the US real estate suffered its biggest blow since the latter half of 2020. Real estate’s new normal is also creating vast swathes of opportunity. Dozens of cities and counties that were once considered too small, too southern, too flat, or lacking in amenities, culture are now finding themselves being swooned to the top of the real estate desirability lists.

It is mainly because people seek warmer, healthier, less dense, better educated, and more mobile places to live that offer closer access to the outdoors, better hospitals, smaller schools, and more open space

The shift to remote working arrangements for people in whitecollar jobs meant that households all across the country could rethink where they lived. This caused a surge in interest in vacation towns, as wealthier Americans opted to purchase second homes.

Meanwhile, the prospect of living in close quarters for months on end while waiting out the pandemic, coupled with recordlow mortgage rates, drove millennial households to leave their abodes in significant cities for suburbs across the country.

Despite the steep downturn during the second half of 2020, home sales rebounded in 2021. The US real estate market is expected to grow from $2687.5 billion in 2020 to $2774.5 billion in 2021 at a compound annual growth rate (CAGR) of 3.%. The growth is mainly triggered by rising demand for shared office space, Ecommerce distribution hubs, and multifamily housing Despite some significant disruptions in the context of the financial crisis, the real estate market remains one of the stable markets suitable for investments at various scales.

The real estate market moves quickly, and being even half a step ahead of the competition can be incredibly valuable in maximizing value for investors.

The US real estate market is expected to grow from $2687.5 billion in 2020 to $2774.5 billion in 2021 at a compound annual growth rate (CAGR) of 3.%.

REAL ESTATE: OUTLOOK FOR FINANCIAL INVESTMENT IN 2021

While commercial real estate, as a whole, is performing exceptionally well, considering our market conditions, not all sectors are firing on all cylinders. However, that doesn't mean their outlook is abysmal.

It merely means that investors and developers should be careful when making certain financial investments Let’s look at some of the investment opportunities for real estate market players in 2021 and beyond.

Source: https://www cbre nl/en/real-estate-outlook/midyear-update-2020

The real estate market has completed transformed over the past few years. While retail was one of the best investment options for real estate players, the demand has significantly dropped after the pandemic. Over the coming years, multifamily housing and shared office spaces are expected to rise in demand

HOSPITALITY MARKET TO WITNESS INCREMENTAL CAPACITY

While it was one of the booming real estate sectors, hospitality has taken an enormous hit during shutdowns due to the unprecedented drop in global travel. This sector includes hotels, motels, and short-term rentals designed and intended to house the travelling population. While we think that hospitality will come roaring back since there's likely to be a pentup demand for travel, prospects in the next two to three years are rough, considering many lenders aren't keen on adding this asset class to their portfolio.

However, serviced apartments appear particularly attractive within the hospitality space. Besides, government initiatives to promote tourism are generating significant demand for hotels in such cities, especially for budget hotels.

Given the sector’s outperformance and positive outlook for tourism during the coming years, it is no surprise that hospitality is attracting more and more real estate investors from around the world.

Improving property fundamentals and elevated pricing have reaped gains for investors, which should continue through year-end as the economy grows. Besides, the risks are lower than many other investment options, and the returns are strong.

BOX RETAIL DYING A SLOW DEATH

It's no surprise that big-box retail is dying a slow death for over a decade now. The pandemic forced people to adapt to online ordering to avoid inperson shopping, strengthening the grasp that online retailers, such as Amazon, have on the retail market. With the massive amount of overhead and difficulty drawing traffic, traditional big-box retailers will inevitably go by the wayside.

The financial aspect of the retail real estate market is not exactly booming, as tenants, landlords and owners take the time needed to understand the market and apply necessary adjustments The data presented herein indicates relatively moderate growth in the market, with notable declines in values, sales and cap rates of malls.

Smaller space retail such as urban storefronts and shop space appear to be handling the fluctuations of the retail environment well, thus assisting with the balance of the

Source: https://www.statista.com/forecasts/885066/real-estate-and-rental-and-leasing-revenue-in-the-us

SHARED OFFICE SPACE IN DEMAND POST COVID 3.

Shared workspace operations are witnessing a rise in demand, with companies signing new lease agreements. However, as a future strategy, most companies are expected to adopt the hybrid model comprising flexible and upgradable workspaces, while a section of employees could continue working from home. Most corporations would avoid capital expenditures and look forward to co-working facilities to accelerate its adoption rate and expansion in the coming time.

The office sector is highly sensitive to economic conditions.

According to a leading investment and real estate management firm Collier International, there is high potential for growth in the coworking industry in areas such as hospitality management, amenities, and value-added services.

For a real estate investor, shared office space means more significant profit margins, diverse revenue sources, and higher Returns on Investment.

4.

MULTIFAMILY HOUSING WILL CONTINUE TO GROW

Multifamily properties have caught many financial investors' eye as more and more of the population chooses to rent over homeownership And as baby boomers reach retirement age, they're choosing to live in more urban, walkable areas instead of out in the suburbs, which can give residents a better sense of community. Affordable housing will likely be the next wave in multifamily investing. Undoubtedly, multifamily housing is the best investment opportunity for real estate investors

Multifamily weathered the 2020 recession better than most property sectors and market deterioration was far less than in previous recessions Still, it was a tough year for multifamily as many owners lost rental income plus ancillary income from waived fees, deferred rents, and delinquencies.

CBRE forecasts a return to pre-COVID vacancy levels and a 6% increase in net effective rents next year, with a full market recovery occurring in early 2022.

FUTURE OF REAL ESTATE LIES WITH DATA

In the world of real estate, a growing number of deals rely on data analysis. From faster, more accurate appraisals to sophisticated forecasts, the use of data can lead to smarter decisions about financial investments. Considering all the data that real estate and its users generate, it seems likely that companies having access to quality data will enter the real estate services market Attributes like these necessitate companies in adopting data as a business model.

Many real estate firms have long made decisions based on a combination of intuition and traditional, retrospective data. Today, a host of new variables make it possible to paint more vivid pictures of a location’s future risks and opportunities

Being slow to identify subtle trends means leaving money on the table Conversely, being a first-mover on a compelling opportunity translates into a significant advantage. Why is it so hard to claim that spot as a first mover? How can real estate investors keep track of so much data and quickly find hidden patterns and harness them for profitable investments? And what has prevented them from doing so? Conventional data harvesting methods and data sources make it challenging to draw clear hypotheses and build robust business cases.

Traditionally, real estate players must sift through tens of millions of records or data points to discern clear patterns and place their bets with few supporting tools By the time an investor can accumulate, compile, and process the data needed to distill action, the best opportunities are gone.

Real estate data analysis for investment purposes only started to appear in real estate literature in late 1996, even though economists and financial analysts already used several analytic tools and techniques. Until then, terms such as utility functions, profitability and time value of money were nonexistent in the real estate appraisal and investment literature

With the wide adoption of computer-based systems, it is now possible to model and explore the impact of various factors on assets' value.

By accessing and incorporating web scraped real estate data into their databases and decision making, investors can leverage the huge power of this data for phenomenal effect. Given the culture of M&A within the industry and fierce competition online, accessing this data first may be a matter of survival for smaller firms, and a bulwark against disruption for larger ones Real estate is a datahungry enterprise Thankfully, web scraping is a powerful solution providing firms of every size a useful tool for monitoring supply/demand, market trends, and online public sentiment.

Source: https://www halofinancial com/properties-abroad/

HOW DATA IS BOOSTING REAL ESTATE BUSINESS

Case 1: Pricing Property Value with Real-time Trends

The real estate market progresses quickly, and being even half a step ahead of the competition can be incredibly valuable in maximizing investors' value. Thanks to the high structural nature of real estate listing data, scraping it from the Web is extremely useful and provides high-quality data, at any scale By analyzing aggregated, high-dimensional listing data, real estate market players can recommend pricing and offerings with a greater level of confidence and clarity.

Appraising a property's value is a multifaceted process, but it can be significantly improved by incorporating the Web's rich data offerings. Using web scraping, the components necessary for determining a property's valuewhich vary greatly can be aggregated and integrated directly into a real estate agent's market analysis Sellers can use these comparables to justify asking prices. It is much easier to deal with an unfortunate appraisal when you know the market's comparables in advance.

How Data can Help

During the past few years, potentially convoluted public records were scoured to pull comparable sales; with intelligent web scraping, historical and real-time data related to sales can be gathered, saving realtors and investors from potential headaches.

Time of Sale and Proximity

With intelligent web scraping, data related to sales and properties from any time period can be retrieved.

Square Footage

Square footage may seem a simple item to scrape, but it is extremely useful in determining home value when pulling comparables.

Age, Construction, and Lot Size

Variables like age, construction, and lot size can intelligently scraped, depending on the need.

Case 2: Monitoring Vacancy Rates Based on External Factors

Every property market globally is subject to a natural vacancy rate (NVR), representing the tipping point for market rental growth. By analyzing market cycles between negative and positive rental change, investors can powerfully position themselves against trends in the market - and there's no better way to fully understand and establish market vacancy rates than by incorporating Web scraped data into your analysis.

How Data can Help

While savvy economists might frequently avail of all the big tech data available to them to determine employment trends and market equilibrium, most agents don't have the time, and large firms of the recent past didn't have the resources or expertise needed to parse this complex data.

Data scraping provides the ultimate solution for scraping and creating high-dimensional data sets, purpose-built for agents across any industry sector. Collating this data with other types of essential data used in real estate, buyers, sellers, and property managers unlock massive potential in forecasting opportunities and providing their clients with the highest possible investment return.

Case

3:

Estimating Rental Yields

It's simple: property owners seek properties that generate an annual income comprising a high percentage of funds invested. While desired rental yields are in the high single digits, market fluctuations related to any odd number of variables can cause extreme yield volatility in particular markets.

By web scraping, historical yields confined to comparable properties in the vicinity of a target property, variables like the neighbourhood, property type, square footage and other metrics can provide real insight for investors and prevent blind decision making Furthermore, while gross yield is often a point of frequent discussion, net yield may be an even more crucial metric enabled by web scraping.

How Data can Help

Vacancy rates, cost of insurance, management fees, to name a few, are all contributors to costs that affect net rental yield. Web scraping allows the compilation of complex, high-dimensional data sets from numerous real estate websites

Property is among the most suitable and stable markets for investment, but investors have struggled to make informed decisions until recently. Now, web scraping tools have overcome these trials of the past, and investors are discovering unique, insightful approaches to optimizing their property portfolio.

A few ways in which web scraping empowers investors to estimate a property's potential and time their investment at the top of the market are:

Correlation of rising interest rates and rental yields

Rising interest rates that discourage some homebuyers can drive rental yield up as rental demand grows. A savvy investor will scrape data for historical interest rates and rental yields in an area and invest accordingly to target a high net yield.

Feature specific

Net rental yield is also affected by maintenance and repair expenses, helping investors see how certain features like AC/Garages/etc. factor into rental yield. Informed investors can then use the scraped data to compare the incremental benefit with the incremental cost

Historical trend

Rental yields vary year over year, but scraping historical rental details can help tell a story about a property or neighborhood. Knowing how a property's rental value tracked with the trajectory of its property value provides immense insight into the % yield one can expect

Private party leases

Web scraping is not just content specific but audience-specific. Many commercial data sets may give a rough idea of market metrics, but only fine-tuned scraping of numerable listings, agreements, etc can give insight into the private rental market that comprises a significant amount of rentals With this missing data, we are missing a significant and targeted group of investors and renters.

Size of property

With empirical data extracted from rental websites, investors can gain information about which size houses they should buy to expect a given rental yield. If an investor wants X% of yield in a certain district, then they can use web scraping to determine what property makeup and sq. footage will provide the highest payout.

Case 4: Understanding Market Direction

The US real estate market at large generates key indices that excite investors or evoke fear, but the variability market by market is one of the characteristics of the industry, which makes web scraping so valuable Web scraping has historically been used to investigate specific questions narrowly.

However, as the real estate market evolves, web scraping might prove a vital tool for a company of any size to find an edge. That edge lies in being able to determine how a market is going to perform in the future Understanding market direction is a prerequisite for being a consultative investor or realtor, and is critical for informing decisions empirically with an eye towards what's coming next.

How Data can Help

Though many will claim intuition about a market heating up or cooling off, aggregating hard, empirical data is critical for both accuracy and foresight.

Property investment

The markets in which investor activity is climbing point toward a market consensus that the area will appreciate in value Web scraping specific parameters like the net growth in investor activity, ratio of investors, ROI, etc., can offer quantitative metrics to compare various "hot" markets.

Monitoring changes in competitor pricing

Real estate is a competitive industry, with companies of all sizes fighting to stay relevant and gain market share. In the race to keep on top of market direction, one's biggest mistake would be shortsightedness. Utilizing tools like web scraping to challenge one's intuition and analyze how competitors respond to the market is vital. Knowing and understanding your competitors' strategies is half the battle, especially in this industry. The data sets enable competitor tracking and empower firms to deconstruct competitor strategy.

Tracking how long properties are on the market

Many in the industry become concerned when houses start taking over 5-6 months to sell on average. A "buyer's market" may have some benefits, but in terms of market direction, it points toward a cooling market.

As we have seen in recent recessions, there is also a breaking point for real estate bubbles that are the product of overextended lenders. Thus, web scraping to estimate average time on the market and variance from list price means it's possible to see correlations between these metrics across a large data set.

CONCLUSION

Real estate is more complicated, notably because so many uncertain factors go into determining prices

Buying or selling a property always involves a bit of gambling on pricing and transaction time. However, big data solutions are transforming the real estate sector. Big data makes purchasing property much easier, transparent and provides a lot of options for investors. Indeed the future of the real estate industry lies in the successful utilization of big data in analyzing information from multiple sources

Although 2020 has been an unprecedented year globally, it has been able to create certain unique opportunities for the real estate sector that are likely to usher in a new era of innovation and digital transformation going forward.

REFERENCES

With the democratization of newer platforms and the offering of newer investment avenues, the COVID-19 pandemic has brought about massive shifts in investment preferences that will continue to outlive the pandemic. As a result, we expect real estate demand to remain robust and the sector to emerge resilient over the nearfuture.

As the internet continues to grow, the amount of data it generates grows with it, opening new opportunities for all types of businesses to improve their processes and make more informed decisions. Incorporating such data streams into your organizational processes you can ensure your business is disruptionproofed and fully prepared for the world of tomorrow.

https://www.cbre.com/research-and-reports/apac-real-estate-marketoutlook-2021

https://www.aberdeenstandard.com/docs?editionId=3ba5dbbf-a3b1410f-957b-d71989d29205

https://www.mckinsey.com/industries/real-estate/ourinsights/understanding-real-estate-as-an-investment-class

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Clean data, quality service, managed infrastructure support, and unrivaled domain expertise makes PromptCloud the most reliable data mining and extraction partner for businesses across the globe. Our value-added services including hosted indexing, lowlatency crawls, and live crawls, deliver even the most tedious of data solutions with ease, scale, and prompt.

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