Predictive Analytics in Real Estate

We talk about lead generation and conversion a lot because it’s literally the most important aspect of a successful real estate career, but today, we examine the topic from a different angle: Data.

Companies across the world, including the behemoth management consulting firm, McKinsey, have examined the effective use of predictive analysis in generating sales.

Before we get too far in the weeds and before anyone hyperventilates from all the fancy-sound business terminology, let’s define what predictive analysis is.

Simply, predictive analysis uses existing historical and transactional data to identify opportunities and risks. Credit reports are a common use of predictive analytics, for example.

In the real estate industry, predictive analytics can work in a couple of ways:

• Automate the initial lead engagement process. Analytics can actually help improve the way you engage with customers and thus the likelihood of converting to a sale. You may think you know the questions potential clients are likely to ask based on past experience, but a platform or model can process that information more efficiently, so you can be prepared not only for what questions you’ll be asked but how to improve the experience for your customers and convert them to clients.
• Improve the value of your existing leads. You already know not every lead is the same and some are easier to convert than others. Lead scoring can help you determine which ones are worth targeting so you can maximize revenue and minimize time waste.
• Develop predictive property recommendations. With the right platform, you can introduce buyers to neighborhoods or specific properties that match their lifestyle rather than a specific search criterion, in much the same way online dating apps work. Buyers may say they want three bedrooms when they intend to use one of the bedrooms as an office. By using data for property matching, you can show them a house with fewer bedrooms but another room – a converted garage space, for example – that can be used as an office.
• Home improvement. Investment in kitchen and bathroom upgrades always pays off, right? No need to make assumptions when you can analyze the ROI of home improvement. Analytics can evaluate improvements and upgrades to local homes to discern for what buyers are paying and what condition is expected at a specific price point.

None of this works if you don’t have a lead scoring model. This doesn’t have to be as difficult as it sounds, but you – or your agency – should consider creating an analytics platform that monitors conversion rates based on marketing, for instance. Google Analytics is a platform used by many marketers to identify traffic sources yield best conversions. As another example of analytics, Facebook ads use information acquired through Google AdWords to target appropriate demographics. You may choose to start with one of these existing platforms, but the point is you need a working system for tracking leads.