The property sector has a great knack for changing with the times. When the internet boomed almost twenty years ago, property development companies quickly integrated it into their services. We have evolved and are thriving in this digital space.
Auctioneering, in particular, has seen vast changes online, from merely posting properties up for auction to platforms such as our new Broll Auctions Online Platform that we launched earlier this year, whereby bids can take place in real-time.
Today, we are facing different beasts, that of artificial intelligence, big data automation, virtual reality and the Internet of Things. And we would be wise to integrate these emerging technologies sooner rather than later. Just how these technologies will change property auctioneering is uncertain. But it will help a great deal to speculate so as to anticipate the changes we need to make.
With so much information out there, large data sets coupled with automation can reveal patterns, trends, and associations relating to property auctioneering. We will be able to hone in on demographics, buyers’ financial statuses and their behaviours according to a set of variables. Big data analytics does not only show us consumer behaviour patterns but can combine these with our already existing market research to provide a holistic and highly objective picture of the market.
Most businesses across all sectors are slow in taking up virtual reality as a tool to improve their services. Yet for the property market, and auctioneering in particular, it is tantalising to imaging that a potential buyer can take a tour of the store, house or shopping centre you wish to purchase before making your final decision.
It will not only present a new dimension in service, but also a marketing opportunity unlike any other. The pool of potential buyers that it can reach will be wider and deeper. This can only bode well for the industry.
Even stores within malls can use this to better their marketing and services. Soon enough, there will be technology that will allow you to feel and touch digitally. For instance, clothing stores will have software that will render a digital image of your body with all possible measurements. So now, you can superimpose a parallel type image and you can visualise how you look. And the fit is going to be using data analytics. Eventually, you are almost going to feel products, or even touch them using this visualisation software. The consumer does not need to go to a fitting room anymore. So you cannot be shy anymore.
We have moved long past the time when Deep Blue, an IBM supercomputer, beat chess grandmaster Garry Kasparov. Today, machines have self-learning algorithms that give them the ability to learn and make predictions from supplied data without them being explicitly programmed.
Problems are now being resolved by software using artificial intelligence – that is machine learning. They have the ability to support humans in decision-making and solving problems and the ability to assist humans with tasks that are too difficult.
In business, self-learning algorithms are currently used to enhance customer experience. For years, online shopping portals are able to recommend items similar to the product you have just purchased, and the tool is only getting more precise.
In the near future, self-learning machines and algorithms will be used for almost all aspects of life. Besides self-driving cars and product recommendations, these self-learning machines may evolve on their own well enough to solve some of humanity’s greatest problems, such as global warming and inequality.