FAQs - RentHub
Why is there a data dip visible between 2018 and 2020?
The dip between 2018 and 2020 resulted from a combination of internal and external factors affecting RentHub's data collection:
Early Operations (2013-2018)
RentHub initially launched their data collection operations around 2013-2014 with an early version of their platform. This initial phase ran through approximately 2018.
Business Challenges and Transition (2018-2019)
Around 2018, RentHub faced significant business challenges that nearly shut down their operations entirely. In 2019, they began slowly rebuilding and made a critical infrastructure change: transitioning from third-party data sources to their own proprietary data collection system. This transition period naturally resulted in reduced coverage as they established new infrastructure.
Pandemic Impact (2020)
The COVID-19 pandemic created additional complications, as rental listings decreased market-wide. This makes it challenging to distinguish between RentHub's coverage gaps and actual market contraction during this specific period.
Current Data Quality (2019-Present)
From 2019 onward, RentHub has significantly improved data coverage and quality by:
- Building robust proprietary data infrastructure
- Adding multiple new data sources
- Implementing multi-channel collection (note: you may see multiple listings for the same address from different channels, which could affect volume counts depending on how duplication is defined)
RentHub has expressed high confidence in their data coverage from 2019 forward and considers their current data quality to be industry-leading.
Why is rental data difficult to collect?
Unlike for-sale real estate, rental transactions are private and unrecorded at the municipal level. Rental data is fragmented across owner sites, listing platforms, and classifieds. RentHub aggregates all this data into a standardized, research-ready format.
What’s included in RentHub’s dataset?
RentHub’s dataset includes:
- Over 1 million listings weekly
- Historical coverage from 2014 to present
- Daily tracking of ~500,000 apartment complexes
- Geographic coverage across the entire U.S.
- Full dataset refreshed bi-weekly
Each listing includes rent, square footage, bedroom/bath count, amenities, geolocation, marketing description, and time stamps (posted/scraped date).
How does RentHub handle data cleanliness?
RentHub does not simply offer raw listings. It structures the data, deduplicates it, and adds identifiers:
- Unique IDs for properties and units
- Indicators for listing duration (posted-to-delisted lifecycle)
- Fields to track amenity premiums (e.g., units with granite countertops)
The platform is optimized to support clean joins and longitudinal analysis.
How has RentHub data been used in research?
Dr. Le Jiang Le presented research on how university presence affects nearby rental markets in Southern California. Her key findings using RentHub data include:
- Proximity to a university raises asking rents by $200+, plus $120/km closer
- Units near universities are more likely to be studios/1-bedrooms, furnished, dense, and amenity-rich
- These “university rental markets” are statistically distinct from surrounding areas
The research relied on RentHub’s street-level geolocation and high temporal granularity, validating results against ACS survey data.
Can RentHub data be joined with other datasets?
Yes. RentHub is integrating Placekey, a universal spatial identifier that makes it easier to join with parcel, commercial, or demographic datasets. While parcel-level joins aren't yet supported natively, they’re on the roadmap.
What legal and ethical standards guide RentHub’s scraping?
RentHub only collects public, factual listing data—never images or content behind login walls. It follows current web-scraping legal norms, ensuring compliance and ethical standards.
When merging the Rental Data with the Listing and Property Mapping by ID, some listings aren't matched, so then a listing doesn't have a UNIT_ID or PROPERTY_ID. What are possible reasons for this?
UNIT_ID or PROPERTY_ID. What are possible reasons for this?RentHub's methodology for aggregating data and assigning unit_ids and property_ids has evolved and improved over time. As a result, recent listing observations (approximately from 2019 onward) include these unit_ids and property_id fields. Unfortunately, some earlier listing observations in the dataset may not contain these fields.
If I want to know how long a unit has been on the market, is it recommended to look at the max and min of DATE_POSTED and take that difference?
DATE_POSTED and take that difference?RentHub agrees with this as a suggested approach for deriving how long a unit has been in the market. The SCRAPED_TIMESTAMP, however, refers to the date that RentHub was able to acquire the listing observation. This does not correlate to the date that the listing was posted to the channel.
For some units, the DATE_POSTED variable changes often. Does this mean the unit was reposted or something changed from the previous posting?
DATE_POSTED variable changes often. Does this mean the unit was reposted or something changed from the previous posting?The DATE_POSTED variable simply indicates the date a listing appeared on an advertising channel. If the same unit is posted with a different DATE_POSTED field, it likely means the listing was reposted. Similar to the above, RentHub can take a look to provide context with an example
Updated 4 days ago