Technology has become ubiquitous in the real estate industry, but some commercial brokers still hold reservations about embracing new CRE tech. There is an ever-present concern that people will lose their jobs if the industry freely adopts progressive technology. At its core, however, automation and technology unlock more opportunities than they take jobs.
Most professionals find that adopting cutting-edge CRE tech helps them save valuable time and make more informed decisions. Commercial transactions are based heavily on research and personal connections, both of which have room for improvement. Brokers can use new tech to expand their network, harness data in real-time for effective price negotiation, and even determine the probability of a sale.
- Automated marketing and online marketplaces provide commercial brokers ample opportunity to reach more investors
- Computer algorithms can analyze property data and pricing history for insights useful in negotiation and future investments
- Technology is remarkably accurate at determining a property’s real value and the probability of selling at a given price
Here are some examples of how automation unlocks opportunities for commercial real estate brokers, buyers and sellers, and frees them to be more productive while reducing the amount of repetitive work in their jobs:
Expanding Your Network Through Technology
Today’s commercial real estate brokers typically market a property by first evaluating the asset and then curating a list of potential buyers in their network who they believe will be right for the deal.
But marketing properties solely based on personal networks can be limiting. One broker we recently partnered with captured it perfectly when he said, “You can’t pretend to know everyone.”
In contrast, moving the market online opens it up to more investors, often yielding a higher price for the asset. Automating portions of the marketing process allows brokers to expand their reach and can also be a strong pathway to building new relationships.
Freeing Up Time For Value-Add Work
Historically, brokers were tasked with the sizable job of gathering and organizing available property data. This time-consuming work is a distraction from focusing on what really matters: sourcing new opportunities and completing deals.
The introduction of technology relegates much of the data dissemination to cloud-based software, allowing brokers to focus more attention on advising the seller, positioning a property or educating a buyer on an asset’s potential, essentially making the deal happen.
Harnessing Data For Effective Price Negotiation
Valuations used to be based in part on a broker’s instinct — they were supported by historical sales comps, but BOVs (broker’s opinion of value) were somewhat subjective.
By harnessing computing power to generate comps that include pricing data from similar properties over many years, algorithm-driven pricing is more scientific than the traditional BOV and is subject to less debate. This is quickly becoming a powerful tool for helping buyers and sellers meet on common ground.
Determining The Probability Of A Sale
Building off the ability to better determine a property’s real value, data-driven algorithms are able to predict the probability that a given asset will sell and at what price. This gives the broker and seller the power to enter the market with eyes wide open. Armed with a better understanding of whether their property will find a buyer, the informed broker or seller is able to determine which strategy will yield the best results.
Where Real Estate Is Headed
Undoubtedly, technology is continuing to transform real estate in a big way. While in the past automation was viewed as a potential threat, it’s my belief that many are beginning to embrace new tools and viewing automation as a real opportunity to create efficiencies in the industry. The tide is turning and forward-thinking professionals from all corners of real estate are realizing that automation is not the future of real estate — it’s the here and now.
View the original article at Forbes