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Zillow Scraping: Extracting Real Estate Data for Market Analysis

Few fields are as dynamic as real estate. The figures are telling. The global real estate market was measured at $3,704 billion in 2022 and is going to hit $6,219 billion by 2032. Every sway in the market echoes through the entire sector, making the desks of CEOs and the boards of property companies have their finger on the pulse of the vibrant business landscape.

If you’re in the continuous search for insights, you probably monitor Zillow. With over 200 million visitors per month, this platform is more than just a directory of homes. It’s a place where you can pull information about the market, consumers, and properties. But if you want to approach collecting Zillow data efficiently, you should definitely consider web scraping. How will it help you uncover the depth of real estate data? Keep reading to learn this and more.

Extract real estate data from Zillow

Can you download data from Zillow?

Yes, you can download information from Zillow. But before you proceed with that, you’ve got to understand its legal and ethical land. Because every website, including Zillow, has its own rules that define whether you can scrape data and what information you can access.

First, you’ve got to understand the line between public and private information. As you scrape data accessible to anyone navigating the platform, that’s totally legal. However, trying to get access to sensitive data can be considered outside the law.

But it’s not only about what information you fetch. How you do that is equally important. For example, you may consider using a Zillow API. This will allow you to collect the platform’s data in a streamlined, ethical, and policy-compliant way. The downside to this is that you may be limited in what data points you can access. And if that doesn’t comply with your scraping objectives, Zillow web scraping is your choice to go.

During this activity, you’ve got to ensure that your actions don’t disrupt the website’s functionality as you pull an extensive range of data. And, believe us, there’s a lot you can scrape. The lists of houses for sale in a particular city with the number of bedrooms, bathrooms, price tags, geolocations, and other important information. Once extracted, you can export that data in any format—.csv, .txt, .xlsx, or even directly into your own database.

How scraped data from Zillow can benefit you?

Automated data collection

Gartner found that process automation saves 25,000 hours of avoidable work annually. Also, 78% of business leaders believe that automating tasks in the organization boosts productivity.

Web scraping allows your company to automate one of the processes—data collection. This method involves using bots, also known as scrapers, to navigate through web pages, identify, and collect specified data. Unlike manual data collection, scraping Zillow allows you to fetch large volumes of information swiftly. And, most importantly, without errors.

Would you like to extend your real estate data scraping effort beyond Zillow? No problem! Stretch your data mining activities across multiple platforms. With this approach, you’ll amplify the volume of data and get a more holistic view of the market.

Discover new opportunities

Are you sure you do your best to make your business succeed? And what if we tell you that scraping data from Zillow will broaden the horizons and open new opportunities? See for yourself.

If you’re an agent, you may want to expand your portfolio in a rapidly developing neighborhood. For this purpose, you want to have as much information as you can. So, you use web scraping to extract a list of properties for sale, along with their prices, features, and days on the market. After analysis, you’ll be able to reveal what properties are likely to sell quickly or those that are priced below market value. And that’s how you’ll add prime listings to your portfolio.

As an investor, you’ll be able to discover lucrative investment opportunities on Zillow. For example, you’ll keep an eye on the multifamily housing market in a particular city. As you may have guessed, you’ll get a comprehensive list of properties that meet your criteria. But that’s not all. You can also take a glimpse into historical data on property values and rental yields. As you side this data with other economic indicators or neighborhood development plans, you can discover undervalued assets or just the ones worth your investment.

Big data in the tourism industry also finds a way. Through Zillow, agents will be able to identify quaint towns or lesser-known cities that are beginning to garner attention. But how exactly? The thing is that real estate popularity is frequently connected with emerging tourist destinations. If let’s say, there is a sudden uptick in property values or a surge in new listings in a particular area, a travel agent may trace the signs of a growing interest in that location through Zillow demographic data.

Discover new market opportunities with Zillow data

Competitive benchmarking

The competitive business environment of the real estate business probably doesn’t let you rest. To win the race, you’ve got to address clients’ needs in innovative ways. So, to create something new, you must do things you’ve never done before. This may mean studying Zillow market data through web scraping.

Indeed suggests that you do the following things to outpace your competitors (listed in the chart below). And here’s how web crawling will help you with that.

Step How web scraping helps perform it
Make a competitive analysis Fetch competitor pricing, listings, and market positioning
Profile your ideal customer Collect Zillow data to analyze consumer behaviors, preferences, and interactions
Define what makes your brand different Export data from Zillow to understand the competitive market and client needs to craft your USP
Focus on customer experience Analyze reviews and metrics on Zillow to have a better idea of what will resonate with your prospects
Innovate Use alternative data to get a new perspective on your real estate business and your target audience to create new experiences

How to extract relevant real estate data from Zillow?

To fetch Zillow real estate data, we use C# along with the .NET platform. We like these tools because they ensure high speed of execution. Also, .NET has an automated error-handling system, which is a good thing for an uninterrupted scraping flow. It’s also integrated with AWS (the cloud provider we use) for scalability and reliability.

Let us illustrate how you can scrape different types of data from this real estate platform.

How to pull Zillow property value data

  1. Let’s set up the environment first. For this, make sure you have .NET framework on your machine. Also, install Visual Studio or another C# Integrated Development Environment (IDE).

  2. Then, you’ve got to create a new project. Select a “Console App” as the project type and name it. Let’s call it “ZillowScraper.”

  3. After that, install the library. For example, HtmlAgilityPack. Install it via NuGet Package Manager with the following command:

Install-Package HtmlAgilityPack
  1. And here’s the code for Zillow housing data on values:
using System;
using HtmlAgilityPack;

namespace ZillowScraper
    class Program
        static void Main(string[] args)
            var url = "https://www.zillow.com/homedetails/some-property-id";
            var web = new HtmlWeb();
            var doc = web.Load(url);

            var node = doc.DocumentNode.SelectSingleNode("//span[@class='zestimate-value']");
            var propertyValue = node?.InnerText ?? "Data not found";
            Console.WriteLine($"Property Value: {propertyValue}");

To further use the fetched data, you’ll need to download it. Let’s say you want to have it in a CSV file.

How to scrape Zillow?

Even though Zillow scraping is a technical process, you should make sure it’s rooted in business acumen as well. So, to maximize your ROI from this activity, you’ve got to take a well-thought-out approach.

Define your goals

Before you write a single line of code, make sure you know what specific data you’re after. Make a thorough analysis of your business needs. What challenges are you facing? What information could provide the solutions? For instance, to expand your property portfolio, you may want to collect data to identify emerging markets or undervalued properties.

💡 Establish specific, measurable, achievable, relevant, and time-bound (SMART) goals for your scraping project.

Quality always comes first

Undoubtedly, Zillow is abundant with data. But it doesn’t mean that you’ve got to collect every single data point that comes your way.

  • First, the information you gather should be relevant to your objectives. Irrelevant data, no matter the volume, won’t do any good for you.
  • Second, prioritize data accuracy. With poor data, you’ll create misguided strategies or even face losses.
  • Relevant data at the perfect time—that’s the approach to stick with. The thing is that the real estate market is dynamic. And what was relevant yesterday might not be to the point today.
  • You can collect any data you want—structured or unstructured. But if you collect the latter, invest time in structuring the data post-scraping to ease the analysis process.

Integrate data with existing systems

Do you rely on different systems in your work? For example, you have a CRM, real estate management system, or BI platform for daily tasks. So, you may want Zillow rental data to flow into those systems for ever deeper insights.

So, determine where and how the Zillow data will complement or enhance your current data sets. For instance, if you have a CRM system where you keep track of client interactions and property listings, you may think of merging scraped property value data with your listings. In other words, each listing in your CRM will automatically reflect the latest market values.

Keep in mind the format compatibility of scraped data with your system. After scraping, you may reveal that data fields are formatted differently, or numerical values have commas instead of periods. So, you’ll need to tweak this data to align with the format your systems recognize.

Train your team

There’s a belief that one of the core things that separates great teams from good teams is their ability to strategically use data. If your company has never invested in data literacy, it’s high time to do that. A study by McKinsey shows that those organizations that rely on consumer data see an 85% increase in sales growth margins. So, as a leader, you should communicate the value that lies behind the use of Zillow research and data to the teams that will benefit from it.

If the integration of new data will change the flows and systems, arrange technical training for the team. For example, if you want to handle data cleaning in-house, organize a workshop on how to do that.

Common challenges of Zillow data scraping

Nothing good ever comes easy. So, there might be some hurdles along your way to getting Zillow data.

Challenge Effect on business Solution
Rate-limiting IP blocking Disrupted data collection Use proxy servers, rotate IP addresses/td>
Data quality Misinformed decision-making Implement data validation and cleaning
Data standardization Inconsistent data formats that lead to ineffective analysis and lead outreach Employ data parsers
Legal compliance Legal repercussions, bad reputation Adhere to Zillow’s Terms
Missing data Incomplete analysis Check for updates
Captcha and other anti-bot measures Slowed or halted data scraping Employ captcha-solving services
Frequent website structure changes Broken scrapers, inconsistent data Regularly update and maintain scraping scripts
Data integration Siloed data, inefficient analysis Utilize robust integration tools
Lack of expertise Ineffective data scraping Train team, consider hiring experts


As the real estate market is highly saturated, it’s worth considering various methods to gain a competitive edge and discover new market opportunities for revenue growth.

Web scraping from Zillow is one of those solutions. As you collect data from this platform, you’ll understand how you compare to your competitors, what your leads want, and how you can deliver that.

If you’re uncertain whether web scraping is the right fit for your business, connect with us, and we’ll schedule a quick discovery call.

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