RENTestimate

Discover the rental value of any residential property

What is RENTestimate?
RENTestimate is a tool that helps you determine the rental investment potential of a residential property using machine learning. RENTestimate is powered by big data on more than 113 million homes, institutional-quality research and on-the-ground experts with deep insight on local real estate market conditions. RENTestimate covers approximately 85% of all residential properties in the US.

How Do We Determine a Property's Rental Investment Value?

Three factors determine a property’s rental investment value: Its rent, price, and operating expenses. To that end, we created Rent, Price and Expense Estimate automated valuation models (AVMs) to predict these values. Our AVMs provide you with an accurate assessment of the earning potential of a property as an investment. RENTestimate determines a property’s gross yield using the Rent and Price Estimates, while the net yield is calculated using our Expense Estimate. RENTestimate is a starting point for residential property valuations, and should not be considered an appraisal.

RENTestimate
/in•vest•tuh•meyt/
noun
  1. By estimating the rent and price on the property
  2. By estimating expenses that may be incurred in managing the property as an investment
  3. By estimating the rent and price growth of the property
RENTestimate/rent•est•tuh•meyt/noun

3 Key Metrics Determine the RENTestimate

Rent Estimate

Market-rate rents on more than 113 million properties are used to create Rent Estimate. Rent plays an integral role in real estate investing. A healthy yield is dependent on establishing an accurate rent for an investment property. The Rent Estimate uses the following features to predict rent:

  • Property characteristics
  • Geographic features like a property’s location and distance from points of interest
  • Market conditions and trends, such as unemployment, income, crime, and school rankings
  • Neighborhood quality
  • Historical rent trends

We determine rents for more than 113 million properties nationwide using over 7,000 geographically-varying models.

Measure of Accuracy

RENT ESTIMATE

We compare all the recent leased rents (within the past year) and determine the number of predictions that are off within ±10%, ±20% from the actual rents. For an overall performance of the model at state, county, city, and zip code levels, we measure Median Absolute Percentage Error (MAPE). To understand over-prediction or under-prediction of rent in a location, we measure Median Percentage Error (MPE).

Nation wide Rent estimate Accuracy

4.26%
-0.94%
MAPE
MPE
% of Properties with Rent Estimate
57%
Within ±5%
80%
Within ±10%
93%
Within ±20%
(Updated January 2019)

* Nationally, we over-predict property rents by 0.94 percent.

Rent Estimate Star Rating

Best
Great
Good
Fair
Insufficient Data
MARKET
STAR RATINGSTARS
NUMBER OF PROPERTIESNO. PROP
RENT AVM MAPERENT MAPE
±5%
±10%
±20%
National (includes all HomeUnion® markets)
113,931,565
4%
56%
80%
93%
Abilene, TX
57,644
9%
34%
53%
71%
Akron, OH
252,019
4%
59%
77%
90%
Atlanta-Sandy Springs-Roswell, GA
2,233,238
5%
53%
77%
92%
Austin-Round Rock, TX
684,092
5%
53%
74%
87%
Charlotte-Concord-Gastonia, NC-SC
918,949
4%
60%
84%
95%
Cleveland-Elyria, OH
732,547
4%
58%
80%
94%
Dallas-Fort Worth-Arlington, TX
2,089,931
4%
57%
81%
93%
Deltona-Daytona Beach-Ormond Beach, FL
270,214
4%
58%
83%
97%
Durham-Chapel Hill, NC
173,114
5%
52%
75%
88%
Gainesville, GA
70,533
4%
59%
80%
88%
Greenville-Anderson-Mauldin, SC
334,904
4%
58%
86%
94%

We use over 15,000 geographically-varying models to predict prices for more than 113 million properties nationwide.

Price Estimate

Price Estimate determines the market value of any home in the United States. The following features are used to analyze and calculate Price Estimate:

  • Property characteristics
  • Current sales comps
  • Market conditions and trends such as unemployment, income, crime, and school rankings
  • Tax assessments and other tax records
  • Previous valuations and historical home price data
  • Neighborhood quality

Measure of Accuracy

Price Estimate

To assess how well the price estimate models perform, we compare all recent sales (within the past year) and determine the number of predicted estimates that are off within ±10%, ±20% from the actual sale price. For an overall performance of the model at state, county, city, and zip code levels, we measure Median Absolute Percentage Error (MAPE). To account for over-prediction or under-prediction in a location, we measure Median Percentage Error (MPE).

Nation wide Price estimate Accuracy

2.12%
0.0265%
MAPE
MPE
% of Properties with Price estimate
59%
Within ±5%
84.68%
Within ±10%
94.00%
Within ±20%
(Updated January 2019)

* Nationally, we under-predict property values by 0.0265%.

Price Estimate Star Rating

We determine a property’s price based on big data for more than 113 million properties nationwide.

Best
Great
Good
Fair
Insufficient Data
STATE/US
STAR RATINGSTARS
NUMBER OF PROPERTIESNO. PROP
TOTAL SOLD SAMPLESSOLD SAMPLES
±5%
±10%
±20%
US
113,931,583
2,802,842
70.88%
84.68%
94.00%
AK
255,836
5,430
31.05%
53.10%
83.32%
AL
2,102,109
32,117
73.97%
87.13%
93.95%
AR
1,264,604
22,611
79.30%
89.36%
95.66%
AZ
2,333,702
76,168
88.58%
94.57%
97.67%
CA
10,139,403
298,994
73.91%
88.38%
95.52%
CO
1,996,669
77,554
88.52%
94.63%
97.71%
CT
1,140,353
26,246
79.70%
90.27%
96.12%
DC
156,101
5,304
82.11%
92.77%
96.86%
DE
376,893
8,264
79.39%
89.08%
94.97%
FL
7,846,387
334,255
66.82%
83.69%
94.20%
GA
4,190,804
116,118
73.92%
87.05%
94.58%

We have more than 170,000 models that predict investment property taxes across various geographies nationally.

Expense Estimate

The expense estimate of an investment is driven by the property’s location and condition. For example, the repair estimates are dependent on how old the property is, when specific items in the property were replaced or how well the previous owner or tenant had maintained the property. Property tax levied on an investment property will be higher than the owner-occupied tax. Insurance companies charge a high premium on investment properties. We derive expense estimates based on:

  • Tax expense models for investment properties
  • Insurance expenses modeled on property replacement values
  • Property management expenses based on industry standards
  • Property maintenance expenses based on age and condition of home
  • Vacancy estimates based on national and local trends

An important note on estimates:

RENTestimate should be used to determine the rental investment potential of a property, and should not be used to determine the actual investment performance of the rental asset.

Listed below are some of the reasons why the accuracy may be low in price and rent estimates:

Not enough data: The estimate calculation requires the surrounding recent rental or sale records to be similar to the property being estimated. If there are not enough comparables, the model falls short at a granular level and has no choice but to revert to a larger geography. This can lead to more comparables, however, they may be more dissimilar to a property, and so the estimate becomes inaccurate.

Incorrect data: Much of the information received is from public records, so the data may have been entered incorrectly at the source.

Missing data: Some of the important facts about house (e.g. bedrooms, bathrooms, square footage, year built) may not be available from the source.

The property RENTestimate is derived from our estimated market rent (Rent estimate), price (Price estimate) and expenses (Expense estimate). RENTestimate is calculated for more than 113 million homes nationwide. It can be a preliminary reference in determining the rental investment potential of a home and is not an official appraisal or investment commitment. The RENTestimate is auto computed based on millions of data points focusing on special parameters, location, market growth, employment, rentability and so on.

We also produce the RENTestimate forecast, which is a 1-year prediction of a property’s rent and price on historical data. In some areas, we may not be able to produce an RENTestimate at all. The RENTestimate’s accuracy varies by the availability of data in a neighborhood and market.

* It is important to note that the Price Estimate is the starting point for residential property valuations, and should not be considered an appraisal. It is difficult to assess a property’s valuation without conducting a physical inspection or methodical appraisal of the asset.

* It is important to note that the Rent Estimate is starting point for assessing market-rate SFR rents, and should not be used to determine lease values.