<p>You name the states, metros, counties, ZIP codes or property types and the fields you need. Movoto's state-to-city-to-address URL structure makes that scoping exact: a run can be one county's condos, every open house in a metro, or the full rental set behind a single ZIP code.</p><p>Much of the detail worth having - price history, tax history, assigned schools, nearby sold comparables - is rendered dynamically rather than sitting in the search result, and the site limits heavy crawling, so we collect from public pages at a measured pace and normalize prices, square footage, lot size in sqft or acres and the status labels into one schema. Delivery is CSV, JSON, XLSX, straight into your database or through an API, on a daily, weekly or custom schedule. When Movoto changes its markup, we fix it - no work on your side.</p>
<p>We collect the fields a Movoto property page and search result actually expose:</p><ul><li><strong>Listing URL, Movoto listing ID and MLS number</strong> with listing brokerage and listing agent name</li><li><strong>Status</strong>: For Sale, Pending, Contingent, Sold, Off Market, Coming Soon, For Rent</li><li><strong>List price in USD</strong>, sold price, price cut amount and date, price per square foot</li><li><strong>Full street address</strong>, unit, city, state, ZIP code, county, latitude and longitude</li><li><strong>Beds, full and half baths, square footage, lot size</strong> in sqft or acres, year built, stories, garage and parking spaces</li><li><strong>Property type</strong>: single family, condo, townhouse, multi-family, land, mobile or manufactured</li><li><strong>Days on market</strong>, list date, last status change, open house dates and times</li><li><strong>HOA fee and frequency</strong>, annual property tax, tax assessment and parcel or APN when shown</li><li><strong>Assigned schools</strong> with name, level, rating and distance</li><li><strong>Description text, feature and amenity lists, photo URLs and photo count, virtual tour link</strong></li><li><strong>Estimated monthly payment and Movoto value estimate</strong> where published</li></ul>
<p>Beyond the visible listing card, we can extract and derive:</p><ul><li><strong>Price history rows</strong>: each event with date, event type (Listed, Price Changed, Pending, Sold, Relisted), price and source, so you can see how many times a home came back to market</li><li><strong>Tax history by year</strong> with assessed land and improvement values where published</li><li><strong>Nearby sold comparables</strong> listed on the property page, with address, sold price and sold date</li><li><strong>Neighborhood and city market pages</strong>: median list price, inventory context and cost-of-living blocks</li><li><strong>School attendance detail</strong>: district name, grade span, rating and distance per assigned school</li><li><strong>Derived signals</strong>: implied cap rate from paired rental and sale listings, list-to-sold spread, stale-inventory flags, new-listing and delisted deltas between runs, duplicate detection across MLS numbers, and normalized address plus geocode keys so Movoto records join cleanly to Zillow, Redfin or your own CRM.</li></ul>
<p>Movoto is a United States residential real estate portal covering the country state by state and metro by metro. It is licensed as a real estate brokerage, so its inventory is fed by MLS data rather than by seller-posted classifieds, and each listing carries an MLS number, a listing brokerage and a listing agent. Listings are in English with prices in USD.</p><p>The portal splits inventory into homes for sale, recently sold homes, new construction, open houses, foreclosures and rentals, and it also builds out pages for land, mobile homes, condos, townhouses and multi-family properties. Around each listing Movoto layers local context that many portals keep in separate products: assigned elementary, middle and high schools with ratings and distances, neighborhood and market pages, cost-of-living and commute context, and nearby sold comparables. URLs are geographic and predictable, running from state to city to street address to a numeric listing identifier.</p>
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<p>Movoto is useful precisely because it carries for-sale, sold and rental inventory on the same address grain. Sold prices next to original list prices give you real discount-to-list and days-on-market curves per ZIP code, and a rental listing at the same address lets you build gross-yield models that a for-sale-only portal cannot support.</p><p>Because the inventory is MLS-fed, every listing names a brokerage and an agent, so a brokerage can rank who actually wins listings in a given county instead of guessing. Investors screen on price per square foot, year built, lot size and the price cut amount and date to find sellers who have already moved once. PropTech teams take the assigned-school block, the HOA fee with its payment frequency and the tax history off the same property page, so an affordability or total-cost-of-ownership model needs no second data source. Appraisers take the nearby sold comparables Movoto already prints on the page, with address, sold price and sold date. Home services and moving companies use the recently-sold, new-construction and open-house feeds as dated events rather than as a static address list.</p>
Monitoring of real estate listings on funda.nl, pararius.com, rentberry.com, rentola.com, and zimmo.be to support the growth of a European property portal.
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Daily detection of new private property listings in Switzerland on Homegate.ch and ImmoScout24.ch, giving the agency first access to high-value leads.
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Scraping residential listings from Immobilienscout24.de in Germany and Mallorca, including complete data and resized images.
Learn MoreLearn how to use web scraping to solve data problems for your organization
Real estate teams work in a fragmented data landscape. The sites that drive demand in Boston look nothing like the ones that matter in Berlin, São Paulo, Dubai, or Mumbai.
Real estate teams are operating in a data environment that is bigger, faster, and more fragmented than ever. Listings go live and disappear in hours, price cuts happen quietly, and the portals that matter most in each country are rarely the same global “top 5.”
Real estate web scraping: a powerful tool for data collection and analysis. Learn how to choose the right data collection method and benefit from real estate web scraping
<p>ScrapeIt is a fully managed web scraping service. You tell us the target sites and the fields you need; we build the crawlers, run them, maintain them when the site changes, and deliver structured data on your schedule. No infrastructure, no code, no scraping team.</p><p>Plans start from EUR 199. We collect only publicly available data, work within a GDPR and CCPA posture, sign confidentiality agreements, and do not bypass logins, paywalls or CAPTCHAs.</p>
Yes. We pull sold price, sold date and each price history event - Listed, Price Changed, Pending, Sold, Relisted - where Movoto publishes them publicly.
Yes. For-sale, sold, new construction, foreclosure and rental listings come through one schema, so you can pair sale and rent data by address.
Yes. Scope by state, metro, city, county, ZIP code, property type or price band. Movoto URLs are geographic, so targeting is precise.
Yes. Assigned schools with level, rating and distance, plus HOA fee and frequency, property tax and parcel data when the listing shows them.
CSV, JSON, XLSX, direct database load or API, on a daily, weekly or custom schedule. Plans start from EUR 199.
Step 1 - Make a Request
You share your needs, expectations, and desired timeframe. We’ll suggest the best solution based on your request and budget.
Step 2 - Configuring Custom Web Crawlers
Our specialists configure the crawlers and extract a sample dataset for your review before proceeding with the full-scale extraction.
Step 3 - Collect and Deliver
Once you approve the sample, we launch the project and start full data collection. We gather, filter, and structure the data for easy use, delivering it on time in your preferred format.
Step 4 - Maintain and Support
Our team manages ongoing processes, monitors website changes, and supports all data extraction cycles. We can also help integrate data into your systems or create dashboards to simplify analysis.
Scrapeit Sp. z o.o.
10/208 Legionowa str., 15-099, Bialystok, Poland
NIP: 5423457175
REGON: 523384582
