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Many sectors are falling behind because of the advent of big data, but housing isn’t one of them

big-dataIn terms of data acquisition, technology is advancing at a rapid rate. So fast, in fact, that many industries are getting left behind. The housing sector, however, is managing to stay ahead of the curve by incorporating big data into their business plans. Some criticise the advent of technology for pushing traditional methods aside, but the general consensus is that the positives outweigh the negatives. Big data can provide agents with the information which allows them to tailor a housing solution to each individual client’s needs.

Appraisals are the first port of call when it comes to using big data. Traditionally a complex process, the use of big data can simplify and streamline the whole affair. Analysis of the data can reveal the overall worth of the neighbourhood properties, which can be used, in conjunction with other factors, to determine the value of the property in question. This can also be used going forward. Having an accurate value in mind can also help tell the housing business whether potential projects are worth the investment or not. The acquisition of big data can also be implemented by insurance companies, to analyse the local area and make a more accurate determination about what cover people might need.

According to some studies, almost half of all houses sold for over $5 million are bought through shell companies, and there is a worry that these companies use the property for money laundering. Using big data to analyse patterns and monitor suspicious activity allows business owners to haver better control of their organisation, and fewer worries about the potentially criminal intentions of any interested parties in an expensive property.

If a property has been on the market for a long time, and there is no obvious reason why, such as a bad review, then businesses can use big data to engage in targeted marketing. By studying housing trends in certain demographics, and combining this information with data about the property in question, you can tailor your search criteria so that you only target the specific kind of person that is most likely to buy the property. This means that you end up with fewer properties lingering on the market for extended periods of time.

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