Keller Williams Launches New App Featuring Geosocial Data
How homebuyers and agents can find the perfect home and understand any neighborhood like a local.
July 29, 2020
Back in February, Keller Williams launched their brand-new consumer app. For clients, this means a more streamlined end-to-end user experience with powerful search capabilities. For agents, the app provides greater insights into clients’ preferences and an easy way to connect with them throughout the entire buying and selling process. Many of the app’s features are driven by rich, real-time data sources, such as Geosocial data, to provide hyperlocal insights.
In this post, we dive into how Geosocial is integrated into KW’s app and what this means for the residential real estate industry in general.
What is a neighborhood like?
We’ve been analyzing the interests and personalities of neighborhoods for a while here at Spatial.ai. From the beginning, we’ve sought to uncover the true behaviors occurring in areas by categorizing billions of public geotagged posts from over 51 million social media users into 72 social segments. For example, a Geosocial analysis in 2017 revealed Northside to be the most underrated neighborhood in Cincinnati based on home affordability and social media activity. Today, we are excited to see this same data empowering KW clients and agents to answer the question, “What is this neighborhood like?”
So, what exactly does Geosocial data look like in the KW app? After selecting a particular listing, there is an option to ‘explore’ the neighborhood that property is in. This screen shows the top 12 ‘lifestyle trends’ and scores, represented by Spatial.ai’s Geosocial segments, alongside other info like commute times, nearby schools, and points of interest. Alternatively, you can view a selection of the top segments under “What Locals Say” on the listing itself.
Benefits of Geosocial
Access to this level of real-time, local understanding of the personalities of neighborhoods is useful to both agents and clients. Specifically, agents can provide personalized neighborhood specific recommendations based on clients’ preferences or previously viewed listings. Clients, similarly, can quickly understand the vibe of neighborhoods from those who know the area best - the locals. What normally would have taken hours, if not days, of research can now be accomplished in minutes.
Only a few years ago, the notion that we could quantify the personalities of neighborhoods to this degree of accuracy would have been questionable, if not unthinkable. But with the ever-growing source of public social media data available to us, and the power of machine learning, this notion is now a reality. And not a badly timed reality either, since it has become clear across industries, including the residential real estate industry, that customers desire and expect more personalized experiences. Homebuyers don’t just want to know about the types of schools and restaurants in an area, they want to find places that match their interests and personalities...
And now they can.
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