Find out the rental market snapshot for cities in california

Explore in-depth rental data for every city in california

agoura hills
alameda
alhambra
aliso viejo
anaheim
antelope
antioch
artesia
auburn
azusa
bakersfield
banning
bay point
beaumont
bellflower
belmont
benicia
berkeley
beverly hills
brea
brentwood
burbank
burlingame
calabasas
camarillo
cambrian park
cameron park
camp pendleton south
campbell
carlsbad
carmichael
carson
castro valley
cerritos
charter oak
chico
chino
chino hills
chula vista
citrus heights
claremont
clovis
colton
compton
concord
corona
coronado
costa mesa
covina
culver city
cupertino
cypress
daly city
dana point
danville
davis
dixon
downey
duarte
dublin
el cajon
el cerrito
el dorado hills
el sobrante
elk grove
elverta
emeryville
encinitas
escalon
escondido
esparto
fair oaks
fairfield
folsom
fontana
foster city
fountain valley
fremont
fresno
fullerton
galt
garden grove
gardena
gilroy
glendale
glendora
goleta
granite bay
granite hills
hawthorne
hayward
hemet
hercules
hermosa beach
highland
hood
huntington beach
imperial beach
indio
inglewood
irvine
julian
la habra
la mesa
la mirada
la puente
la verne
ladera ranch
lafayette
laguna beach
laguna hills
laguna niguel
lake city
lake elsinore
lake forest
lakewood
lancaster
larkspur
lemoore
lincoln
linda
livermore
lodi
loma linda
lomita
long beach
los angeles
los gatos
malibu
manteca
marina del rey
martinez
marysville
menifee
menlo park
merced
mill valley
milpitas
mission hills
mission viejo
modesto
monrovia
montclair
monterey
monterey park
moreno valley
morgan hill
mountain view
murrieta
napa
national city
newark
newport beach
norco
north highlands
north shore
norwalk
novato
oak park
oakland
oakley
oceanside
olivehurst
ontario
orange
orangevale
oxnard
pacheco
pacific grove
pacifica
palm desert
palm springs
palmdale
palo alto
panorama heights
paramount
pasadena
perris
petaluma
pico rivera
pittsburg
placentia
plainview
pleasant hill
pleasanton
plumas lake
pomona
port hueneme
rancho cordova
rancho cucamonga
rancho mirage
rancho palos verdes
rancho santa margarita
redding
redlands
redondo beach
redwood city
rialto
richmond
ridgecrest
rio linda
rio vista
riverside
rocklin
rohnert park
roseville
sacramento
salinas
san bernardino
san bruno
san carlos
san clemente
san diego
san dimas
san fernando
san francisco
san jose
san leandro
san luis obispo
san marcos
san mateo
san pablo
san rafael
san ramon
santa ana
santa barbara
santa clara
santa clarita
santa cruz
santa maria
santa monica
santa rosa
santee
sheridan
signal hill
simi valley
south san francisco
spring valley
stallion springs
stanton
stevenson ranch
stockton
suisun city
sunnyvale
sunol
temecula
thousand oaks
tiburon
torrance
tracy
turlock
tustin
union city
upland
vacaville
vallecito
vallejo
vandenberg village
victorville
visalia
vista
walnut creek
west covina
west hollywood
west sacramento
westlake village
westminster
whittier
wildomar
winchester
winters
winton
woodland
yuba city
yucaipa

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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