Find out the rental market snapshot for cities in massachusetts

Explore in-depth rental data for every city in massachusetts

abington
acton
alford
andover
arlington
ashland
attleboro
bedford
belmont
beverly
billerica
boston
boxborough
braintree town
brockton
brookline
burlington
cambridge
canton
charlton
chelmsford
chelsea
chester
chicopee
concord
danvers
dedham
easton
everett
fall river
foxborough
framingham
franklin town
hanover
haverhill
hingham
hopkinton
kingston
lawrence
lexington
lowell
lynn
lynnfield
malden
mansfield
marlborough
marshfield
medford
melrose
methuen town
milford
natick
needham
new bedford
newton
north andover
north attleborough
northborough
norwood
peabody
pittsfield
plymouth
quincy
randolph
revere
rowley
salem
saugus
sharon
shrewsbury
somerville
southampton
springfield
stoneham
stoughton
sturbridge
sudbury
swampscott
tewksbury
wakefield
waltham
watertown town
wayland
wellesley
west tisbury
westborough
westfield
westford
westwood
weymouth town
whitman
wilmington
woburn
worcester

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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