We get it. You’ve heard a lot about predictive analytics, but every time you try to learn more about it, you’re hit with even more terms you’ll have to google: Back-testing, machine learning, algorithmic modeling.
The truth is, you already know about all of these terms and how they work. You just don’t know how they work for agents like you. To better understand predictive analytics for real estate, let’s dive into another massive modern trend that once seemed impossible: the rise of long-term partnerships as a result of online dating.
Here are three ways our business model overlaps with today’s dating apps — from the data matching to the natural chemistry needed to build a professional or personal relationship.
1. Building up a massive repository of (imperfect) data
Each dating app is powered by staggeringly different models, but all are based on massive data sets related to their users. eHarmony has their infamous 500-question survey, while Tinder’s matches are based on your social network behavior — including your friends, location-based check-ins and even your Spotify preferences.
Of course, the data isn’t perfect. More than 50% of people are found to outright lie on their dating profiles. And in the case of Tinder’s behavior-based matching, you may get matched based on an acquaintance you have despised since high school debate team.
Source: Toon Pool
Similarly, the data used to predict likely sellers is not always complete or 100% accurate. Housing data — including sold date and price — is only as good as the transcription specialists who recently digitized millions of records from across the country. And even with that data available, there are still plenty of other holes to fill, whether it be missing data from non-disclosure counties or the infrequency of tax-assessed home values in certain states.
Other data points, like home equity numbers or the homeowner’s overall financial standing, can only be determined based on dozens of analyzed factors, some of which aren’t available in the public record.
But just as eHarmony can overcome their “fibbing” users and Tinder can scrub their data to exclude the short-lived yoga habit of a real-life couch potato, real estate data scientists can analyze the imperfect housing, financial and personal demographic data of a local market area or CRM database to determine who is likely to sell.
It all starts with building an analytics engine that is smart enough to weigh truly important variables and downplay or discard those that may not be truly indicative of future behavior.
2. Weighing that imperfect data to make predictions
When eHarmony matches up their users, they don’t just start from scratch with their 500 questions. They use the data and results of millions of past users to influence their current predictive models. As the available data grows, so does a data company’s ability to put different weight on certain variables in certain settings.
And just like match.com doesn’t always set you up with the obvious match (read: tall, dark and handsome stranger) you had in mind, we don’t always offer agents the exact list of sellers they asked for. Why? Because while you have one neighborhood in mind, our data might suggest the one down the road has even higher turnover or better supporting data, which boosts our confidence in the predictions.
And perhaps most surprisingly, we may recommend that you get in touch with someone who doesn’t seem likely to sell — sometimes, the data shows triggers that aren’t visible to the human eye.
3. Sealing the deal with chemistry and perfect timing
Just as dating requires chemistry and good timing, so too does landing a real estate client.
Our predictions and marketing can bring you to the doorstep of a likely seller, but only a genuine attempt to connect and provide a value will get you inside the living room, where they sign the contract.
At SmartZip, we don’t just hand you the predictions and leave you to fend for yourself. We have a variety of tools to help you connect with predicted sellers, including:
- inside sales agents who can vet your top prospects
- automated marketing campaigns that target them online and in real life
- a smart CRM app that helps you keep in touch naturally until you win the sale
While dating apps are notoriously quiet about getting involved in the love lives of their users, we are here to help ensure you follow up on the match and land the deal.
Need a listings matchmaker?
If you’re ready to think outside the box and see how predictive models can help you win new or repeat business, we’d love to walk you through the predictions and turnover in your local area — or to dive into your CRM to see who of your contacts is planning to sell soon.
Reach out today for a no-pressure (and no obligation) territory check.