How the use of predictive analytics can help your business.

Our property website specialist and Design Director examines how the use of predictive analytics can enable estate agents and property companies make informed decisions about future marketing and customer trends.

What is Predictive Analytics?

Predictive Analytics is the practice of extracting information from existing data sets in order to determine patterns and predict future outcomes and trends. This can help estate agents and specialist property companies get smarter infomation about how homeowners are likely to behave. This would support more targeted marketing campaigns that, based on data, are more likely to yield enquiries, and therefore instructions and sales. The following are examples of data points that could be harnessed:

  • Price trends
  • Time since last sale
  • Movement in street
  • Last selling date
  • Crime
  • Price appreciation
  • Income
  • Last marketed

Why is it useful?

President Obama famously won the 2012 US election with the help of predictive analytics. By assembling a team of 100 analysts to interpret large-scale big data, his election campaigners were able to determine potential voters, especially the undecided, yet receptive voter. Through this, they were able to target their campaigns effectively, by concentrating their efforts on the voters who could potential be a ‘yes’ vote, as opposed to targeting those who would always be a ‘no’ vote.

Obviously, there is a big difference in winning elections compared to selling houses, but in marketing terms, the use of data analytics can be equally as effective. For example, for a property company, one can amalgamate data to create different targeted reports, which is combined with other open demographic data. Reports can be run to filter for properties that exhibit characteristics that tend to be associated with property likely to sell within the next year to 18 months. Similar data criteria can be used for lettings.  The size of data and complexity of data gathered by these methods  way exceeds any data provided from more commonly used property statistics.

Tweet: The size of data and complexity of data gathered by these methods way exceeds any data provided from more commonly used property statisticsThe size of data and complexity of data gathered by these methods way exceeds any data provided from more commonly used property statistics

A further extension of potential analysis would be to filter for streets where the data shows properties have sold more or where properties have sold above the averages.  It is known (through data) that high turnover streets have occupants that are also more likely to move, it is also proved that those living in streets where property is selling above market value are more open to the notion of a valuation and ultimately sale. This allows you to target your marketing be that email or direct mail, to a very specific audience – one that is more likely to be receptive to your marketing.

Prescriptive Analytics

The next step is taking this valuable information and prescribe new and engaging ways to get the attention of these already more susceptible customers.

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