Data sciences has dramatically changed the way online advertising is practiced today. It is a multi-disciplinary field that involves the use of analytical tools and algorithms to process and draw meaningful insights from structured and unstructured data; with the advanced machine learning algorithms programmed to identify the occurrence of a particular event in the future.
Most real estate advertising agencies rely on raw data (pertaining to the consumer’s age, income and purchase history) for product advertisement. The figures and statistics help these advertisers develop a deep understanding of the dynamics of changing customer preferences, providing enormous leverage for creating efficient marketing strategies.
Through the use of data sciences, companies operating e-classified portals are now able to supplement the existing information compiled over time. The phenomenon has impacted the global property sphere in more than one ways.
Online real estate platforms have seen a tremendous increase in recent years (due to technological advancements which continue to make great strides towards global connectivity). And the unprecedented role of data sciences for leveraging the success of these portals cannot be undermined.
Previously, the standard property purchase procedure happened to be a daunting and time-consuming endeavor: people spent long hours in sifting through newspaper classifieds or negotiating the service charges of (normally pilfering) real estate consultants.
Similarly, and in consideration of the opposite side of this equation, property agents were forced to rely on personal connections in their bid to turn prospects into customers. Then, the advent of e-classified portals took the property world up a notch. Online advertising became the new normal and provided the stakeholders with a flexible and congenial business setting.
Moreover, free listing services emerged as a cost-effective solution to the traditional, expensive marketing model; and, by extension eliminated the need for a middle-man (real estate agent) who once served as the trusted advisor for property every transaction.
With new and improved features, including ads customizers and search engine optimization, online real estate businesses have transformed the global real estate sector by leaps and bounds. Nowadays, sellers have easy access to multiple ad slots provided by these e-classified portals – saving these property owners both time and money.
Today, data scientists comprise a significant part of the workforce of most online advertising agencies. Consider the case of Crimtan (which provides real-time programmatic solutions for advertisers) where data scientists make up more than 50% of the company’s manpower.
Numerous other e-classified portals like Zillow, Trulia, and Prop not only create effective marketing strategies through the use of data mining practices but also provide the users with the latest stats and figures on the property market.
Zillow, one of the world’s largest online real estate websites, hosts an enormous database detailing information regarding residential properties (available for purchase, sale, or rent) in the United States. It allows users to draw comparisons of similar properties, calculate costs, as well as benefit from several other features.
Similarly, Trulia features a simple yet efficient user interface for those seeking permanent or temporary residential accommodations. It basis its listings on price trends, in addition to providing price comparisons – a feature common to most online property portals.
Perhaps, Trulia’s most unique feature is its Trulia Neighbourhoods technology which provides excellent insights (such as information on crime rates and educational and transport facilities) into localities.
In Pakistan, where the real estate remains largely undocumented, the government plans to utilize the data compiled by the local property portals as part of the executive’s efforts to regularise Pakistani property market. In a wider context, data sciences has facilitated increased completion in the cut-throat world of real estate.
More and more companies have begun to contract the services of data analysts, programmers, and mathematicians in their bid to mine complex, unstructured data – the organizations with the requisite skills and availability of latest information have emerged as industry leaders in recent years.
On the contrary, the firms who were unable to adapt to cutting-edge technologies fell out of the whole process and were replaced by technological firms with expertise in undertaking examination of large pre-existing databases for extracting new information.
As a result, this whole competitive cycle has helped create a niche market for such firms; hence, providing them with a room for growth, as well as allowing them to operate alongside established real estate businesses.
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