Find out the rental market snapshot for cities in washington

Explore in-depth rental data for every city in washington

arlington
auburn
bainbridge island
bellevue
bellingham
bonney lake
bothell
bremerton
brier
burien
camas
covington
des moines
duvall
edgewood
edmonds
ellensburg
enumclaw
everett
federal way
fife
fircrest
gig harbor
graham
issaquah
kenmore
kennewick
kent
kirkland
lacey
lake stevens
lake tapps
lakewood
liberty lake
longview
lynnwood
maple valley
marysville
mercer island
mill creek
milton
monroe
moses lake
mountlake terrace
mukilteo
newcastle
north bend
olympia
orting
pacific
pasco
port orchard
puyallup
redmond
renton
richland
ridgefield
sammamish
seatac
seattle
shoreline
silverdale
snohomish
snoqualmie
spanaway
spokane
spokane valley
steilacoom
sumner
tacoma
tukwila
tumwater
university place
vancouver
walla walla
wenatchee
woodinville
yakima
yelm

Our data is best categorized as "alternative data", which is a burgeoning sector. Through partnerships and direct feeds, we extract key factual elements that are publicly available within rental listings on internet listing sites and property websites. Once aggregated, we mine through the data to parse out relevant insights and calculate important metrics, benchmarks, and other KPIs. Each week, our system sifts through millions of listing observations and other pockets of market information to deliver the most comprehensive picture of rental housing available.

This is a metric that we try not to overthink. Simply, we take each unique listing observation within a geographic boundary and calculate a simple average. Of course, we're careful to filter for duplicates and other listings that aren't reflective of the market.

Yes, but please attribute us accordingly.

Yes. We can deliver bulk raw data in various formats. Please contact us to discuss - [email protected].

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.

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 deconstruct our rental listing data points and identify key amenities for each 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. Listings data is ingested, cleaned (de-duplicated. etc.), analyzed for insights, and then presented to our users.
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