RentEst Rent Estimate Scraper: 21 Data Fields per Record (2026)

Each record carries 21 output fields, including the estimated monthly rent, median rent, and up to 10 nearby comparable rental listings. This collector submits US street addresses or 5-digit ZIP codes to the RentEst pricing model to return valuation data without requiring a login or API key. A thousand results cost $5.00 on Apify's free plan, which provides enough monthly usage to try the tool at no cost. It is designed for practitioners who need market snapshots and comparable listing data, but it does not return historical rent trends or full building amenity lists.

Try it: open RentEst Rent Estimate Scraper on Apify, sign in on the free plan and run the prefilled example.

Can you try RentEst Rent Estimate Scraper before paying?

Yes. Apify's free plan includes $5.00 of prepaid usage every month and asks for no credit card. At $0.005 per result, that covers up to 1,000 results of RentEst Rent Estimate Scraper a month, before run-start charges and platform usage.

The example request further down caps maxItems at 20, so a first run returns at most 20 results and costs at most $0.10 in result charges. That is enough to see the real shape of the data before deciding anything.

RentEst Rent Estimate Scraper was last updated on 2026-08-06. It is one of 1,725 Actors CrawlerBros publishes on Apify, which together have 686,256 lifetime public runs and an average rating of 4.63 out of 5 across 416 reviews.

What does it cost to run RentEst Rent Estimate Scraper?

Each result costs $0.005 on Apify's free plan, which is $5.00 per 1,000 results. Starting a run is charged separately at $0.005 per GB of Actor memory. Apify also bills the platform usage each run consumes, at the rates of your Apify plan, on top of these charges.

The locations array and the maxItems cap are the primary drivers of the bill, as each successfully resolved location counts as one result. To minimize expenses during initial testing, set maxItems to 20 or fewer to verify your filters are returning the expected comparable density before running a full list of addresses.

How do you run RentEst Rent Estimate Scraper from the API?

The schema marks 1 of its 6 controls as required: locations. Every value in the payload below comes from the published schema's own prefills, which means you can paste it, swap the token, and get a real result.

Call the synchronous endpoint to start a run and receive dataset items in one request:

curl -X POST "https://api.apify.com/v2/acts/crawlerbros~rentest-rent-estimate-scraper/run-sync-get-dataset-items?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"locations":["10001","90210","60614"],"propertyType":"apartment","bedrooms":"2","bathrooms":"1","maxItems":20}'

The same run from Python, using the official client:

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")

run_input = {
  "locations": [
    "10001",
    "90210",
    "60614"
  ],
  "propertyType": "apartment",
  "bedrooms": "2",
  "bathrooms": "1",
  "maxItems": 20
}

run = client.actor("crawlerbros~rentest-rent-estimate-scraper").call(run_input=run_input)

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

And from Node.js:

import { ApifyClient } from 'apify-client'

const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' })

const input = {
  "locations": [
    "10001",
    "90210",
    "60614"
  ],
  "propertyType": "apartment",
  "bedrooms": "2",
  "bathrooms": "1",
  "maxItems": 20
}

const run = await client.actor('crawlerbros~rentest-rent-estimate-scraper').call(input)
const { items } = await client.dataset(run.defaultDatasetId).listItems()
console.log(items)

That endpoint blocks until the run completes. Fine while you are testing a handful of records, risky once a run takes minutes: a dropped connection loses the response even though the run itself finished. Switch to an asynchronous start with polling or a webhook before you schedule anything.

Which RentEst Rent Estimate Scraper inputs matter, and which can you skip?

The locations field is the only requirement, accepting either specific street addresses or broad ZIP codes. Use the propertyType and bedrooms selectors to prevent the estimate from being skewed by irrelevant property classes, such as mixing single-family homes with apartments.

• locations (array): US street addresses or 5-digit ZIP codes to get a rent estimate for. Each is geocoded and priced automatically by RentEst's free rent-estimate tool.
• propertyType (string): Restrict comparable rentals to a building type. Default: "apartment".
• bedrooms (string): Number of bedrooms to filter comparable rentals by. Default: "2".
• bathrooms (string): Number of bathrooms to filter comparable rentals by. Default: "1".
• sqft (integer): Optional interior square footage to narrow the comparable-rentals match. Leave blank to let RentEst estimate without a size filter.
• maxItems (integer): Hard cap on how many locations to process (one output record per successfully resolved location). Default: 20.

Fixed-choice controls: propertyType accepts apartment (Apartment / Condo), house (Single-Family House); bedrooms accepts 0 (Studio), 1 (1 Bedroom), 2 (2 Bedroom), 3 (3 Bedroom), 4 (4 Bedroom), 5 (5 Bedroom); bathrooms accepts 1, 1.5, 2, 2.5, 3, 3.5, 4.

What does RentEst Rent Estimate Scraper return?

The returned records are ideal for automated property valuation and market screening because they include a confidencePercent to help you filter out low-data estimates. Each result includes coordinates and distance data for up to 10 nearby properties used in the calculation.

• queryAddress - the address or ZIP you submitted
• latitude, longitude - resolved coordinates
• estimatedRent - the headline monthly rent estimate (USD)
• averageRent, medianRent - mean and 50th-percentile rent among matched comparables
• percentile25Rent, percentile75Rent - rent range bounds
• confidencePercent - RentEst's confidence score for the estimate (0-100)
• matchedPropertiesCount - how many comparable rentals were used
• searchRadiusMiles - the radius searched to find comparables
• modelUsed - the pricing model RentEst used internally
• dataSources - underlying listing sources (e.g. Zillow, Apartments.com)
• bedrooms, bathrooms, propertyType, sqft - the filters used for this estimate
• comparables[] - up to 10 nearby rentals, each with address, rent, distanceKm, bedrooms, bathrooms, sqft, similarityPercent, lastSeenDate, latitude, longitude
• currency - always USD
• sourceUrl, scrapedAt

These are the documented fields. Optional ones can be empty on a given record, so measure how often each field your deliverable depends on is populated across a real sample before automating the handoff.

How do you build the workflow end to end?

Open RentEst Rent Estimate Scraper and work through these in order. Each step ends with something to check, so a bad configuration surfaces on a small run rather than a scheduled one.

1. Set the locations array with either a 5-digit US ZIP code or a specific street address to initiate the geocoding process.
2. Configure the propertyType to apartment or house to ensure the pricing model compares your target against the correct asset class.
3. Select the bedrooms and bathrooms count to filter out mismatched inventory that could skew the medianRent.
4. Provide an optional sqft integer if the interior size of your unit is significantly different from the local average for that bedroom count.
5. Set maxItems to a value that matches your locations list to prevent the run from continuing if the geocoding engine starts producing redundant matches.
6. Execute the run and check the confidencePercent field in the dataset to verify the statistical strength of the estimate.
7. Review the comparables array to see the distanceKm and similarityPercent for each of the 10 nearby rentals used in the calculation.
8. Export the results to CSV and compare the estimatedRent against the percentile25Rent and percentile75Rent bounds.

How do you apply it? Three worked playbooks

These are RentEst Rent Estimate Scraper's own documented use cases, each worked through as an operating pattern rather than a description.

Use case 1: Landlords & property managers

Outcome: Sanity-check asking rent against comparable listings before renewing or listing a unit

Configure: Set locations to the specific street address of the unit, propertyType to the relevant building type, and bedrooms/bathrooms to match the floorplan.

Working method: Run the Actor for the target address and compare the current asking price against the estimatedRent and averageRent. Use the similarityPercent in the comparables array to identify which nearby units are the most direct competitors for your unit.

Deliverable: A valuation report for a specific address containing rent percentiles and 10 nearby comparable rental listings.

Stop condition: The confidencePercent is too low to provide a reliable basis for a price increase.

Use case 2: Real estate investors

Outcome: Screen prospective rental properties for cash-flow potential across multiple ZIP codes at once

Configure: Input a list of target ZIP codes into locations and set maxItems to match the total number of ZIPs being screened.

Working method: Perform a bulk run across multiple investment targets to identify geographic clusters where the medianRent suggests high cash-flow potential. Cross-reference the searchRadiusMiles to see which markets have the highest density of comparable data.

Deliverable: A spreadsheet comparing market rent estimates, mean rents, and median rents across several target ZIP codes.

Stop condition: The matchedPropertiesCount returns 0 for a majority of the target locations.

Use case 3: Relocation & apartment hunting

Outcome: Get a fair-market rent baseline for neighborhoods before touring

Configure: Add the specific ZIP codes for your target neighborhoods to locations and set propertyType and bedrooms to your desired living situation.

Working method: Generate rent estimates for several neighborhoods to establish a baseline for your search. Use the percentile75Rent as a ceiling to identify if specific units you are viewing are overpriced compared to the local market average.

Deliverable: A market profile showing the 25th, 50th, and 75th percentile rent ranges for a specific neighborhood and property type.

Stop condition: The geocoding fails to resolve a latitude and longitude for the requested neighborhood location.

What breaks, and how do you design around it?

When the scraper returns no results for a location, it is usually because the filters for propertyType or bedrooms are too restrictive for that specific geography. Try removing the optional sqft filter or broadening the bedroom count to allow the model to find more comparable properties in the area.

When should you not use RentEst Rent Estimate Scraper?

This Actor is not for users who need deep historical archives or building-level amenity details, as it only returns a snapshot of estimates and the top 10 comparables. If your project requires an exhaustive list of all available units in a specific building or detailed amenity data, use the Apartments.com Rental Scraper. For those specifically analyzing government subsidy compliance rather than market-rate estimates, the HUD Fair Market Rents Scraper is the better tool. If you need to find self-storage pricing rather than residential rents, use the SelfStorage.com Scraper instead.

What should you check before trusting the output?

• Verify confidencePercent is higher than 0 to ensure the RentEst pricing model had enough data to generate a score.
• Check that matchedPropertiesCount is not null, as this indicates how many real-world listings supported the estimate.
• Confirm the currency field is always USD to ensure the geocoding resolved correctly within the United States.
• Monitor searchRadiusMiles to ensure the comparable properties are within a reasonable geographic distance of your target.
• Validate that estimatedRent falls within the range defined by percentile25Rent and percentile75Rent to confirm data consistency.

None of this proves a record is correct. It gives a scheduled RentEst Rent Estimate Scraper run defined points where it should stop instead of quietly passing bad data downstream.

Frequently asked questions

How much does it cost to process 1,000 rent estimates?

On Apify's free plan, 1,000 results cost $5.00, calculated at the free-plan price of $0.005 per result. This total does not include platform usage fees, which vary based on the resources consumed during the run. You can process your first 1,000 results using the $5.00 of monthly usage included in the free plan without adding a credit card.

Is the success rate for this Actor reliable for automated workflows?

The Actor has a 100.0% success rate across 32 runs in the last 30 days. This indicates the Actor is stable for unattended scheduling. If a run fails to return a specific location, it is typically due to a lack of data on the source site for that specific property type and location combination rather than a technical failure of the scraper.

Can I get estimates for properties outside the United States?

No, this Actor is limited to US addresses and 5-digit ZIP codes because it relies on RentEst.ai, which specifically targets the American rental market. All currency values are returned in USD. For international data, you would need to find a different tool that supports regional providers in those specific countries.

Why are some comparable rental fields missing from my output?

The Actor documentation states that empty fields are omitted from every record. If a comparable listing is missing square footage or a specific similarity score, it means that data was not present for that listing. This ensures the output remains clean and only contains data points provided by the source.

How can I improve the confidence score of the rent estimates?

Confidence scores are highest when there is a high density of recent, similar listings nearby. To improve scores, ensure your propertyType and bedrooms inputs match the standard inventory for the area. If you provide a specific sqft value that is an outlier for the neighborhood, the confidence score may drop because fewer similar properties can be matched.

Where to go next

When you are ready to run it, open RentEst Rent Estimate Scraper on Apify; the free plan covers up to 1,000 results a month.

Start with the RentEst Rent Estimate Scraper Actor page for the current input schema, pricing tier, and run history.

Other Actors we maintain for related data:

• SelfStorage.com Scraper: Scrape SelfStorage.com - find self-storage facilities for rent by city, ZIP code, or address.
• Apartments.com Rental Scraper: Extract apartment rental listings from Apartments.com including property name, address, rent range, beds/baths, sqft, amenities, neighborhood, walk/transit scores, and more.
• Rent the Runway Scraper: Scrape Rent the Runway (renttherunway.com) - browse by category (dresses, tops, accessories, and more) or search by keyword, filter by designer, occasion, color, price, and size.
• HomeFinder Real Estate Scraper: Scrape HomeFinder.com real estate listings - homes for sale, homes for rent, and search by city/state or ZIP code.
• Salarship Jobs Scraper: Scrape Salarship.com - a global job board with salary estimates for 100,000+ positions.
• HUD Fair Market Rents Scraper: Scrape HUD Fair Market Rents (FMR) data for all US states, counties, and metro areas.
• PadMapper Scraper: Scrape PadMapper.com apartment and rental listings.
• ChildcareCenter.us Daycare & Childcare Directory Scraper: Scrape ChildcareCenter.us, the largest US directory of licensed childcare centers and home daycares.

Related guides:

• SelfStorage.com Scraper: 3 Practical Use Cases
• Apartments.com Rental Scraper: Practical Use Cases and Guide
• HomeFinder Real Estate Scraper: 3 Practical Use Cases
• HUD Fair Market Rents Scraper: 15 Data Fields per Record (2026)

Resources

• Actor documentation, input schema, and pricing: verified against the published Actor on 2026-09-27.

• Actor last updated by its maintainers on 2026-08-06.

• Run outcome figures cover the 30 day public window ending 2026-09-27.

• RentEst Rent Estimate Scraper on Apify