How Real Estate and Web Scraping are Made for Each Other?
Real estate has changed completely with the development of the
internet and a lot of other businesses are initially needed heaps of the
organization. Technology helps realty dominations like CBRE in scraping and
managing their listings internationally.
Automation has dribbled in fields like customer support and email
marketing therefore, why not optimize the online property listings to draw a
bigger group of buyers?
Most of the realtors are
not trained to become technologically intelligent, therefore, manual market
research has become more difficult. Web scraping
services offers boundless possibilities, which eliminates
confusion among the all-encompassing amount of disorganized data.
Web Scraping has Become a Savior
Web scraping makes sure that you have an enormous amount of
accurate and reliable real estate information.
Consequently, you can utilize this insight for boosting your
company as well as earn considerable rewards.
Extracting real estate data using the Internet with a web
scraping service provider gives you the position to provide high-quality real
estate solutions and services for the betterment of the customers.
Extracting the web produces metrics, which a realtor can search
further to measure sales as well as future customers. These are the parameters,
which could be obtained with data scraping:
- Property’s Type
- Sale Prices
- Size
- Location
- Parking Space
- Amenities
- Property Agent
- Monthly Rental Pricing
Use Cases
Accurate Deduction of the Property Values
Want to sell your babyhood home? Don’t mess around with the
pricing through shooting in dark as there is ample space for profit after
making research as well as observing similar properties as well as their
values. Now, the market research can be fast and efficient therefore, you will
get the finest deals.
Maximize Rental Yields & Long-Term Sustainability
Before making an
investment in the real estate, the most vital thing to keep in mind is rental
yields. You would find which properties in the neighborhood are having the
finest rental yields by extracting data from the real estate sites. Scraping real
estate data shows which real estate types are most general in
the given region as well as have the best ROI.
Gathering as well as reviewing data might allow a company to take
the best decisions depending on high-quality data. This is also an ideal way of
maintaining a strategic lead in the competition.
Tracking Vacancy Rates
Investments in the restricted building could be risky. It is
important to look at the property details as well as suburbs having new rental
listings to discover what could be the source of better vacancy rates for any
particular property.
Having sufficient extracted data, companies could find the
difference between diamonds.
Investing Like an Expert
If you wish to constantly invest in the current year, might be you
don’t require to listen your elders’ advice from the ’80s. No space is left for
imprecise information, which has not got updated ever since the foundation of
Google!
Web harvesting permits you to get the latest real estate data,
which provides the way to do investment analysis of the listing websites.
Let’s See How to Do it?
Let’s accept that we wish to extract Realtors to get properties
with minimum two bedrooms and two baths in Miami as well as compare them to
observe which option is better. Just follow these steps in the process.
We’ll begin by using a web scraping tool. You can also do it by
creating your individual web scraper, however, it would be time-consuming as
well as won’t get a lot of features like a pre-built tool.
We will use our Web Scraping API as it comes with great features
including avoiding the IP blocks, geo-targeting, rotating proxies, synchronized
requests etc. Also, we will utilize JSDOM and NodeJS.
1. Creating a Web Scraping API Account
This is an easy step. Just register as well as validate your
account through email and we’ll go to the following step.
2. API key
You’ll require an API Key to validate your API that you can have
from the dashboard.
Just reset the private key anytime with pressing “Reset API Key”
option if there is any change of getting it stolen.
3. Application Integration
3.1 Necessary Tools
To make the HTTP request, just install a package as well as jsdom
for parsing the HTML resumed from the requests.
npm install got jsdom
3.2 Setting the API Requests Parameters
const params = {
api_key: “XXXXXXXXXXXX”,
url:
“https://www.realtor.com/realestateandhomes-search/Miami_FL"
}
3.3 Making the Request
const response = await got(‘https://api.webscrapingapi.com/v1',
{searchParams: params})
console.log(response.body)
After making a request, we see that a page is resumed in the HTML
format.
3.3 Inspecting the Source Codes
We can search the page as well as elements that we’re involved in
using different Developer Tools. To inspect the elements, just right-click on
an element and choose ‘Inspect’ option.
We have found that property elements have the class of
component_property-card. A few fundamental information about the listings are
positioned within this element in the wrapper named property-wrap.
3.5 Parse the HTML
We require to parse request results to manipulate that as the
results are returned in the HTML format. JSDOM would complete the job!
const {document} = new JSDOM(response.body).window
3.6 Result Processing
We are looking for the elements having class
component_property-card as well as reiterate over them. With each listing, we
search corresponding elements with property address, size, price, baths and
beds; if these properties are available, we save them in the object. After
finishing with current listings, we push that into the array.
Iterating with all listings in an array, we show ones
corresponding to the conditions (minimum two beds and two baths).
We wrap this code with the sync function and it needs to look like
that:
const {JSDOM} = require(“jsdom”);
const got = require(“got”);
(async () => {
const params = {
api_key: “XXXXXXXXXX”,
url:
“https://www.realtor.com/realestateandhomes-search/Miami_FL"
}
const response = await
got(‘https://api.webscrapingapi.com/v1', {searchParams: params})
const {document} = new
JSDOM(response.body).window
const listings =
document.querySelectorAll(‘.component_property-card’)
const properties = []
listings.forEach(el =>
{
if (el) {
const price =
el.querySelector(‘span[data-label=”pc-price”]’)
const beds =
el.querySelector(‘li[data-label=”pc-meta-beds”]’)
const baths =
el.querySelector(‘li[data-label=”pc-meta-baths”]’)
const size = el.querySelector(‘li[data-label=”pc-meta-sqft”]’)
const address =
el.querySelector(‘div[data-label=”pc-address”]’)
let listing = {}
if (price) {
listing.price =
price.innerHTML
}
if (beds &&
beds.querySelector(‘.meta-value’)) {
listing.beds =
beds.querySelector(‘.meta-value’).innerHTML
}
if (baths &&
baths.querySelector(‘.meta-value’)) {
listing.baths =
baths.querySelector(‘.meta-value’).innerHTML
}
if (size &&
size.querySelector(‘.meta-value’)) {
listing.size =
size.querySelector(‘.meta-value’).innerHTML
}
if (address &&
address.textContent)
listing.address =
address.textContent
properties.push(listing)
}
})
properties.forEach((property) => {
if (property.beds >= 2
&& property.baths >= 2) {
console.log(“Address: “ +
property.address)
console.log(“Price: “ +
property.price)
console.log(“Beds: “ +
property.beds)
console.log(“Baths: “ +
property.baths)
console.log(“Size: “ +
property.size + “ sqft \n”)
}
})
})();
4. There you are!
Within seconds, you will get all the data on your fingertips! The
important thing is how you do it!
Congratulations! You have extracted this web page well.
Use of a Web Scraping Tool is Very Easy
We believe that you’ve understood how website scraping is changing
the real estate market.
Those that can adapt to the always-changing technology trends as
well as use data will get the best chance of setting an industry pace.
Web scrapers are available in different sizes and shapes. The
finest option is try our API before buying anything. Contact X-Byte Enterprise
Crawling for real estate data scraping services or ask for a free quote!
For more visit: https://www.xbyte.io/how-real-estate-and-web-scraping-are-made-for-each-other.php
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