You can use Mashvisor API to access all endpoints needed by developers to build their applications on top of Mashvisor Inc, a rich real estate API, which can get real estate information, deep analysis, solid and up to date calculations on various cities, zip codes, and neighborhoods in our database across the United States. You’ll be able to see investment valuation analysis for listings, rental rates and incomes for both short term or long term strategies, mortgage calculator, Airbnb listings and areas performance, top reviewed Airbnb listing in any location. Also, general information about trending cities across the U.S. Moreover, you’ll be able to use the power of Mashvisor AI and machine learning on real estate valuation.
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Welcome to the Mashvisor API reference! A real estate API you can use to access Mashvisor API endpoints needed by developers to build their applications on top of Mashvisor Inc, which can get real estate information, deep analysis, solid and up to date calculations on various cities, zip codes, and neighborhoods in our database across the United States.
You can view code examples in the dark area to the right, and you can switch the programming language of the examples with the tabs in the top right.
In order to get a key to use the APIs, you need to subscribe to Mashvisor, navigate to the developers’ section in the profile page and generate a key.
The endpoints will let you access solid and concrete data calculated via our services, real estate information like:
The investment properties tab will give you a list of the properties that are available for purchase, as well as their projected returns. When hovering over a property on the map or selecting it from the list of properties, Mashvisor will provide data related to the potential cash on cash return and a cap rate of the property if it was rented out traditionally or through Airbnb, allowing investors to determine the strategy that is more suitable for their investment.
This option allows the investor to see all existing traditional and rental properties and Airbnb listings in the area, which can then be used in order to understand how the different properties are performing by comparing them to one another. Just like any other rental website, the monthly rent for traditional rental properties will be displayed. Airbnb properties will also display their nightly rates, estimated monthly rental income, as well as their Airbnb occupancy rate.
Get deep insights and predictive analytics related to Airbnb rentals in a specific city, neighborhood, zip code, or even a street address, with the power of [Mashvisor](https://www.mashvisor.com developed algorithms and machine learning models to obtain predictions of Airbnb rental income, deep estimates of Airbnb occupancy rate, cash on cash return, cap rate, ratings, number of Airbnb reviews, historical performance, property types, number of bedrooms, and all other information and characteristics you’re looking for.
Mashvisor provides data and analysis for different short term rentals services presenting them for the investment listings, including Airbnb, HomeAway, and VRBO.
For each Airbnb listing, we calculate its occupancy rate, month per month, and an annual rate, and we offer our clients a 12-month historical performance for the occupancy rates. We store each listing’s bookings and calendar since the day the listing became active over AirBnB.
We have access to a day per day performance, nightly price, and if the property was available for booking or not. So for each month, we check day over a day if it was booked or not, and how much the host made off that booking, whether it was a one-night booking or a booking for a few nights in a row.
Sometimes, a host makes the listing calendar look like it’s occupied and not available for booking, even though a guest does not book it. Generally speaking, this might cause inaccurate calculations for the occupancy rates and the listing rental rate. At Mashvisor, we have identified this issue and solved it by the continuous hard working cycle over cycle over the past 4 years to enhance how we calculate the occupancy and to verify if a night was really booked or only blocked by the host from booking.
We also calculate the nightly price rate based on the nights that were actually booked. We calculate the nightly price as the average of all booked nights in a month.
Also, when Mashvisor sees a month is almost fully booked, we review the month’s reviews and compare it to the number of bookings. This guarantees the bookings are real and the data and calculation we made are right. If the validation fails, we don’t consider the month’s bookings.
Finally, the listing’s occupancy rate is calculated as the average (mean) occupancy rate of the previous 12 months’ occupancies to make sure that seasonality is considered in the analysis.
Get solid, reliable comparable rental income for long-term rentals in your location or any housing market in the US for any property type and number of bedrooms via Mashvisor AI algorithms in addition to the predicted cap rate and cash on cash return as well as the vacancy rate for the area, the available traditional term rentals, and their rental rates.
Mashvisor has agreements with multiple MLS’ providers and we’re currently finalizing agreements with multiple others.
We currently have 1,5M+ rental listings in total in our databases (active and inactive). 450K+ Active rental listings from them nationwide.
Integration and agreements are the same included in the MLS Listings section above.
Mashvisor has agreements with multiple MLS’ providers and we’re currently finalizing agreements with multiple others. We currently have 6M+ MLS listings in total in our databases (active and inactive). ~850K Active MLS listings from them nationwide. Covering 600+ MLSs out of 820.
Get real estate data on comparable long-term rental listings with an average monthly rental rate as well as comparable Airbnb rental listings including Airbnb occupancy rate, daily rate, rental income, and Airbnb reviews and rating. Obtain data on recent sales of similar properties in the area and neighborhood-level data, moreover, have access to property details, characteristics, taxing info and history, sales history, owner info, the breakdown for the expenses, and much more.
Mashvisor API lets you find out an estimated rental rate for a specific location either for long term rentals (traditional way), or for short term rentals (Airbnb, VRBO, or Homeaway). These estimates categorized by the number of bedrooms of property you’re trying to get the estimates for. The estimates are based on 12 months’ historical performance for the target area, and they are calculated over several similar listings that were rented in the area, or currently available for rent.
Study a housing market through Mashvisor big data with access to the number of active listings, median listing price, price changes, comparable long-term rental listings, comparable short-term rental listings, comparable rental estimates, their investment performance, and optimal insights.
Mashvisor predictive analytics provide you with a way to analyze rental properties and real estate markets to get the whole picture of the US housing market trends to predict whether a specific market is worth investing in by the use of Mashvisor big data powered by our AI algorithms developed by an experienced real estate data team with a feel of human experience through our market experts:
A unique Mashvisor designed score showing an overall evaluation of the neighborhood investment opportunity as a percentage.
The Mashmeter is a function build over machine learning algorithms and a developed mathematical formula by our data engineers, which only Mashvisor offers to real estate investors. This simply shows you if a real estate investment in a certain neighborhood is a good or bad real estate investment decision.
The goal of this model is to evaluate a neighborhood by predicting how much it is good for investment. The resulting score is what so-called Mashmeter.
A Mashvisor developed a tool comparing unique historical investment property sales to give you optimal investment property opportunities in multiple locations in real-time.
In the last year we were trying to go over the traditional technique for searching an area per area for the best investment home to buy or rent over like other listings site, so went over this with our new product the “Property Finder”, the model built over a machine learning model Investment Likelihood telling the score of each MLS listing if it’s suitable for investment or not, and the customer could easily search within a shortlisted of listings that are suitable for investment in multiple areas (up to 5 different areas concurrently).
The model had 3 development iterations yet, and we achieved more than 86% accuracy with it in our last iteration with our data scientist and real estate experience with help of multiple real estate brokers and agents who were using the product for the past recent months. The model designed to get used to all sold listings for investment use them in the next training cycle to guarantee model evolving upon time automatically as well as our data scientists keep working on the best machine learning algorithm to introduce very high-quality investment listings for our customers.
The model has shown very good impressions from our customers and recently it’s our most performing product with a thank for our developed machine learning algorithms. Currently, our data team is working on having a new feature over the Property Finder and this investment likelihood model for predicting the most likely investment listings characters that the lead would be interested to buy through defining and implementing new machine learning models having in respect the advantage of the investment likelihood model itself as a basement, with mode dependency over the persons financials situations, demographics, and lifestyle intestates.
With only the email, name, and phone number of the user, this Mashvisor tool predicts the most preferred property specifications for this specific user in terms of property type, number of bedrooms and bathrooms, and home value and applies them to the search filter of the Property Finder to pull out a list of the properties which meet the user’s preferences and are most likely to be purchased by him/her.
The API is to return a JSON object holding data representing specifications for recommended properties based on the person demographics and financials. The specifications including property type, number of rooms, number of bathrooms, and the home value.
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