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Our data is best categorized as "alternative data", which is a burgeoning sector. Through partnerships and direct feeds, we extract key publicly available elements from rental listings on listing sites and property websites.
While some of our data is refreshed daily and other data comes in weekly, the bulk of it comes in on a biweekly basis.
Our coverage is nationwide! In our platform, we have data points for every ZIP code and neighborhood boundary in the country.
Simply put, these are different ways of creating consistent geographic boundaries. As you know, ZIP codes are postal code designations. While residential living patterns don't always collide with these boundaries, they're ubiquitous and therefore more "scientific" in a sense. Alternatively, neighborhoods are more "artsy", as they're more or less consensus driven and can adjust over time.
Not yet, but we're working on that. However, using our ZIP code and neighborhood dashboards, you can filter and zoom in/out to refine your data story as is necessary for you.
Every rental housing unit is differentiated by attributes such as its location, square footage, and amenity composition. Thanks to machine learning and natural language processing technologies we deploy, we're able to deconstructure our rental listing data points and identify key amenities for every listing. WIth this information, we're able to give signals around how certain amenities drive rental pricing value in certain areas.
Well we think so! At the highest level, our process is simple. Data is ingested, cleaned (de-duplicated. etc.), analyzed for insights, and then presented to our users. The very data that is used by renters to make rental leasing decisions is the data that flows through our dashboards.
The first thing you should do is to enter in the relevant neighborhood or ZIP code. From there, you'll want to refine what is presented to you by filtering for the unit configuration you're searching for and for the appropriate building type. To check out even more data points, adjust the data filters accordingly, however be careful for seasonality. With these data points in the dashboard, you should be able to get a sense of your market. Don't forget to examine the segmentation in the distribution charts because this can be a sanity check around a specific rent price (you can see what proportion of the market is around your rent price segment).
Start with the MSA ZIP dashboard for the city of interest. There, you'll find key area metrics like the rent/income ratio, the price/rent ratio, and areas where we are seeing the highest amenity premiums. The ZIPs that have favorable metrics in these categories are where you should start your search, because those are likely "hot" investment locales.