Big data is one of the most important trends around the globe today, and real estate isn’t the exception. One of the main benefits of this concept is its benefits for forecasting.
But can it predict where prices will be going for real estate after the COVID-19 crisis? That's what we'll find out today.
Before we begin, do remember that proper budgeting and forecasting is a vital skill for any company. Hiring a professional service can prove a crucial advantage during recovery.
Big data was already famous for price forecasting
Big data implementation in price forecasting isn’t new. It was already growing in popularity nearly a decade ago. This 2014 article from Medium, focused on Google trends, proves it.
Interestingly, the report talked mainly about how big data's fast information delivery. Back then, the central thesis was whether big data could be helpful for price prediction. Today, it's a common element in the said strategy.
SmartData Collective also has a great look into big data analytics and its implementation in Forex trading. Since trading is mainly dependent on price prediction, understanding its usefulness is vital for understanding why it's advantageous for real estate forecasting.
Results are quick
Big data communicates gigantic amounts of information in seconds. That means investors and analysts have real-time access to current information. Predictive analysis benefits considerably from this advantage since it lets companies instantly access this content.
It paints the full picture
Price isn’t solely defined by initial investments and even consumers’ wishes. Multiple variables make up the environment dictating price swings. The pandemic is an excellent example, and big data enables investors to understand everything that could influence price changes.
It eliminates human error
Big data also removes all emotional elements behind the information received. Market panic can stem from political turmoil, fake news, and emergencies, such as COVID-19. Big data analysis enables investors to distance their feelings from the numbers since it deals solely with statistics.
Big data’s utility in predictive analysis
Fast forward until today, and you’ll see that big data is a common aspect of decision-making in business. In that linked article, The CEO Views goes through how big data can benefit eCommerce ventures.
We already analyzed the "trading perspective," but studying different industries' uses of this concept allows us to assess possible implementations in real estate. Predictive analyses focused on sales growth are pretty similar to their use in price prediction.
Trend prediction
Market trends are a significant influence on prices. People's preferences change with time, and these interest shifts benefit specific markets over others. Big data sources can identify the onset of these developments. Investors can take advantage of trends earlier.
Analyzing specific audience reaction
Deciding on suitable investments requires assessing how a company's audience can respond to specific assets. Big data analysis lets investors assess their clientele's preferences so that they can adjust their investments according to what will perform better.
Studying customer behavior during purchase
People can make last-moment decisions while they’re buying. They might opt to invest in something else, cancel their purchase, or even end their relationship with the company. Big data analysis considers these behaviors, letting property managers find the most valuable clients.
Assessing market approach
Finally, big data provides crucial information about what a company’s competitors are doing. That includes marketing practices and investment preferences. Instant access to competitors’ prices and investments is a considerable edge when deciding the next moves.
Traditional price forecasting in real estate
Real estate predictability has been the main focus of many studies. One of the most critical observations from that study touches on the serial correlation between real estate price changes.
In other words, understanding historical price swings in different asset types enables analysts to assess how these could play into future prices. Estimating previous situations and their outcomes make it simpler to evaluate possible outcomes once the market reaches similar contexts.
Serial correlation in real estate returns
Serial price correlation refers to how historical price changes influence future swings. Real estate returns show a positive serial correlation. However, the evidence is still vague about whether said predictability is reliable enough to benefit decision-making.
Valuation ratios
Valuation ratios, including dividend-price and earning-price, have been traditional signs of possible equity returns. Naturally, determining an asset's returns—and whether they're positive or negative—helps predict if comparable prices are feasible in the future.
Economic variables
Finally, the environment around an investment opportunity plays a prominent role in said investment's potential returns. Again, the pandemic and response measures have been perfect examples of how economic variables can influence property prices.
Big data’s role during COVID-19
One of the reasons why big data became so popular during the pandemic is how vital it was for comprehending and responding to the crisis. This article from Forbes goes through how healthcare institutions relied on big data to define response strategies.
The interview goes through the concept's usefulness for epidemiological analysis. It granted experts access to extensive epidemiological data, including populations, risks, and possible developments as the virus spread and evolved.
The medical side of big data implementation
Big data enabled healthcare institutions to make informed decisions regarding which measures could yield better results.
Real-time trackers and multiple data sources were decisive factors during the pandemic. Just like with other industries, public healthcare is continuously relying more on big data.
What does this mean for real estate forecasting?
The same data used by public healthcare in response to the COVID-19 pandemic is available for real estate analysts. All these sources can prove a vital ally during recovery.
This information is vital for real estate companies when adapting their investments to market developments during 2021.
Big data’s usefulness in post-pandemic forecasting
The pandemic was a disaster for the entire world, but it might not be as disastrous as similar recessions in the past. Big data is one of the main elements responsible for that.
As we detailed, big data played a vital role in reducing the damage done by the crisis. However, it also goes beyond that. Big data will be a crucial ally for every government and company looking to develop a recovery roadmap after the pandemic subsides.
Revenue
Projecting investment revenue is the main attraction behind big data for many companies. Analysts can check their current and possible revenue streams to find the best opportunities and optimize their income depending on market changes.
Sales
Predicting what customers may prefer in the future is crucial for assessing which investments are more promising after the pandemic. Big data allows companies to gather information from millions of sources instead of individual markets.
Supply Chain
Short-term and global trade information is another advantage of big data analysis. For real estate prices, it's particularly beneficial for commercial real estate. It's easy to assess the best properties based on their supply route proximity.
Workplaces
Company employees also provide plenty of data that are useful for operational optimization. Email traffic, the mobile device uses, sick leaves, and log times provide unique insight on how companies can improve their efficiency.
Customer relationship
Finally, companies can assess their relationship with their customers and tenants. That includes assessing high-value customers, like business tenants from flourishing industries. During recovery, this information makes a huge difference when evaluating property lease opportunities.
How can you take advantage of big data in your company?
Working with big data can be complicated if your resources aren’t used to it. That’s why you should consider hiring expert project management services to aid you. It’ll help you develop more robust strategies to handle the recovery period starting this year.
However, NewGenApps has five excellent tips for using big data to optimize prices. Do remember that price optimization depends mainly on market forecasting. Let's see how their tips can teach us something about big data in price prediction.
1. Recognize data volumes
Companies and markets never run out of up-to-date data. Every transaction and development produces unique insight into how different markets are performing. Focusing on suitable data sources for specific purposes is part of the efficient analysis.
2. Focus on specific assets
Analysts can segment big data according to specific markets and property types they wish to evaluate. This approach allows them to filter irrelevant information for specific investments, like user interest and conditions from unrelated locations.
3. Segment products accordingly
Product pricing depends on multiple factors, like geography, surrounding areas, and more. Big data analytics lets users identify specific information related to particular product categories. That allows companies to divert their investments and marketing strategies to specific consumer behavior patterns.
4. Stock clearance and margin maximization
Inventory management is a primary challenge for many property managers. Big data allows companies to study how their competitors and similar offerings are performing. That enables firms to adjust their prices according to what's working in the market.
5. Cost Reduction
Finally, the quantity of data available lets companies finds the information they need to optimize operations. This benefit lets them improve profitability and allocate resources where they're more necessary. The result is better cost management and reduction.