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  • Writer's pictureBhagyeshwari Chauhan

13 Ways our Customers are Using Real Estate Market Data

Historically, real estate has been a big player in the investment market and it will remain so.

The reason is simple: we all need real estate to build homes and run businesses.

Getting the best value out of real estate investment is difficult but not impossible. Sensing the market dynamics and finding opportunities is the key. There are many people who made it big in real estate: Shark Tank star Barbara Corcoran and US President Donald Trump are good examples.

Real estate is a gold mine if you invest in the right property at the right time at the right price. However, finding that big RIGHT is the problem that is troubling real estate investors. Investors are turning to real estate market data or housing market data to help make purchasing decisions.

Simply saying Real estate market data or housing market data is the data obtained from real estate portals through web scraping.

Datahut has scraped real estate data for numerous companies in the real estate industry. Here are the 13 ways in which they use the real estate market data to beat their competition.

1. Helps companies monitor their competitors' inventory

Real estate portals are essentially a two-sided marketplace that connects buyers and sellers. One of the biggest factors which attract buyers is the amount of inventory the real estate portal has. The more inventory you have, the better the prospects you attract.

The volume of inventory with decent Search engine optimization can boost your search appearance. This will translate into a spike total number of visits and thereby sales. Monitoring the inventory details of the competitors and analyzing them can reveal interesting insights.

We’ve worked with a real estate portal from the US. Our customer needed data from 7 of their competitors’ websites in 12 cities. We built data extractors using our cloud-based platform and fed them into the analytics tool of our customers. The customer was able to discover how their competitors are performing in inventory development across different real estate segments. This data was used as a benchmark for planning strategic initiatives to improve their own inventory development efforts.

2. Track inventory distribution across states/cities/Zip codes

For data-driven companies, just knowing the size of the inventory is not enough. They need information on how it is distributed among states and cities, sometimes even at a zip code level if possible.

There are companies competing on a national level across all 50 states in the US. However, the distribution of inventory among them fluctuates a lot. Knowing these dynamics can be very useful for companies trying to get to reach the industry apex in that market.

Even if a particular real estate portal holds the number one position in the total number of listings, it might be lagging in crucial markets where there is a lot of market activity. That is a gap worth filling.

One of our customers wanted zip code-level property listing information from competitor sites and to understand how it is distributed among them. We extracted this data for her and she used Tableau to plot the data on the maps of states in the US. A clear pattern and a lot of interesting insights were visible on the Tableau dashboard.

Our customer experimented by strategically identifying and placing billboards to see if it changes the dynamics. Within a month there was a significant change in inventory growth and it was in direct proportion to the billboards. They decided to identify more strategically important positions and it was a clear path to success.

Note: They used a few other private data sets along with our market data to identify the location.

3. Real estate data helps companies track the prices of properties

In the real estate industry, the price is a deal maker or breaker for buyers and sellers. It is important for real estate investors and sellers to get the right price for their property.

How do you know what is the fair market price in a region? To find this, you can get the pricing information from real estate portals. If you monitor these prices long enough, you can get time-series data of the prices and this can be used to benchmark the base price. Furthermore, you can build a predictive analytics model to forecast future prices.

Datahut worked with a large real estate brokerage firm that wanted to keep its sales reps informed about the inventory movement, price changes, and other details. We monitored price changes across 12 different real estate portals. The data we scraped was pushed to their custom analytics engine. The output was exposed through an API and an APP on the tabs and phones of the sales rep was able to see visualizations of pricing data and other important information. This helped sales reps better engage prospects and sell more.

4. Real estate data helps understand the shelf velocity of the competitors' inventory

Just before the housing crisis of 2008 – real estate was sold and bought like popcorn.

One of the investors who worked with us said the shelf velocity was on weed In Dubai. By the time you see a property and finish the due diligence, it would have sold at least 3 times in a month. His firm got scared and sold all the properties just before the crisis hit.

Shelf velocity or how fast the inventory is being sold is a KPI real estate investors must track. A slow shelf velocity and a high self velocity are signs of trouble.

A large real estate company with HQ in Singapore wanted our help to track the shelf velocity. They wanted to know how dynamic it is across different cities across different Asia and Pacific countries. We set up web scrapers on our cloud-based web scraping platform and delivered the data on a weekly basis for three months. This data revealed some very interesting insights.

One of the markets he was interested in moving into had a very slow shelf velocity. Liquidation of assets would be very difficult and slow in such markets. Investors always need an exit route and the data was giving clear indications of where not to go.

5. Real estate data analytics reveals what type of properties are coming to the market and how they are performing

From small houses to big buildings, a real estate portal has all kinds of data. If you take the top 10 real estate portals in a city, you will cover 90+ % of the inventory.

An investor needs to know a lot of things before entering a market

  1. What types of inventory is coming to the market ( Villa, Whole building etc.).

  2. What is the shelf velocity in each segment.

  3. Which portals are dominating in each segment.

  4. Which parts of the city /state/neighborhood are contributing the most to the inventory.

Real estate market data can answer many of these questions. We’re working with a hedge fund that needs the market data to answer the questions above.

Web scraping is the best choice to get data from real estate websites. We set up data scrapers on our cloud-based data extraction platform. We extracted data from 20 websites from different countries to understand market dynamics.

6. Determine the type of properties in the inventories across the state.

Real estate data is a powerful tool for real estate companies looking to gain insight into the types of properties in their inventories. With an understanding of the type and condition of their inventory, companies can make better decisions about how to spend their marketing dollars, as well as how to manage their current properties. Real estate companies can also use data to identify which areas or demographics are performing particularly well and should be focused on in the future.

7. Help real estate brokers better negotiate with customers.

Real estate companies can use real estate market data to gain insights into the market, which can help real estate brokers better negotiate with customers.

Real estate is a competitive industry, and real estate companies need to know what their competitors are doing in order to stay ahead of the curve. Real estate market data helps companies do this by giving them access to information about the competition's pricing strategies, marketing campaigns, and more.

Real estate brokers have access to this same information, which allows them to better assess how they should approach any given deal. Brokers can use this information to help their customers prepare for negotiations by providing them with an accurate assessment of what they can expect from the other party.

8. Optimally use scarce resources and prioritize marketing spend to help real estate investors in making a confident purchase decision.

When you're an investor in the real estate market, it can be hard to know when to start marketing your properties and which properties are best to market first. You don't want to waste your time and money marketing a property that's not going to sell, but you also don't want to miss out on the opportunity to make some cash by selling your property at a higher price.

Luckily, there's a solution! Real estate data can help you pinpoint exactly when you should start marketing your property and what kind of price range you should be aiming for. It will also tell you how many people are looking for properties like yours and how much competition there is. This way, when it comes time for you to make a decision about whether or not to sell, you'll know exactly what kind of market conditions are affecting your decisions—and if they're optimal for making the sale.

9. Correlate crime rate data with demographics of the inventory to make safe investment decisions.

Real estate investors are always looking for ways to make their investments more profitable.

One way to do that is by balancing two key factors: the risk of crime, and the demographics of the inventory.

Crime rate data can be used to pinpoint areas where there is a high risk of crime and therefore less profit potential. This can help investors avoid making investments in those areas, which can be a huge time saver when you're trying to find the best deals.

Demographics, on the other hand, can help an investor predict demand for their properties based on the type of people who live in the area and their income levels (or lack thereof). If you're considering investing in an area where many people are low-income or unemployed, then you may want to reconsider your investment because this could lead to trouble with tenants paying rent on time or maintaining your property.

10. To correlate data from different sources to understand what type of amenities and emergency services are available nearby.

Real estate investors have an obligation to their clients to ensure that they are investing in properties that are safe, sound, and profitable. They can do this by leveraging real estate market data to correlate data from different sources to understand what type of amenities and emergency services are available nearby. In doing so, they can make sure they're investing in the right areas.

This kind of information can help investors make decisions about which properties will be most profitable for them. For example, if you know that there's a hospital on the other side of your property line, you'll know that tenants will be able to get medical care if they need it, which means they'll stay longer in your units and pay rent more reliably.

Or if you're looking for an investment property with a high likelihood of being occupied by tenants who have children, you might want to consider purchasing a home in an area where there is good public transportation and access to daycares.

11. Correlate property data with foot traffic data to validate the commercial viability of ideas.

Real estate investors can leverage real estate market data to correlate property data with foot traffic data and validate the commercial viability of ideas.

This is a very popular strategy for real estate investors because it helps them identify properties that are undervalued in relation to their potential.

By correlating property data with foot traffic data, real estate investors get an idea of how many people are looking for a particular type of property at any given time in a particular area. This will help you determine which properties have the most commercial viability and thus will be most likely to appreciate in value over time as demand increases.

12. Public records, such as plans for new infrastructure development can give insights into the direction in which the real estate market is moving.

The real estate market is constantly changing, and in order to stay ahead of the curve, you need to be able to understand and anticipate what's happening.

Real estate investors can find key insights into the direction of the real estate market.

One way to do this is by looking at public records, such as plans for new infrastructure development. These plans will give you an idea of where the government is investing money and resources: if you see a lot of construction happening near your home or business, it's likely that more people will be moving there soon.

13. Train predictive algorithms for residential and commercial markets.

Real estate investors can use the power of predictive analytics to train algorithms to predict the future of their markets. By using historical data on housing prices, rent and occupancy rates, and other metrics like crime rates, they can create mathematical models that can predict future trends and behaviors.

These tools are especially helpful for investors who are looking at a new market or need help deciding where to invest their money. By using predictive analytics, investors can see which areas have the best chance of returning investment or being profitable for them over time.

Wrapping up

Real estate is a highly dynamic industry and filled with a lot of unknowns. However, prior conducted data insights using the right kind of data not only arm you with a strategical mindset for new investments but can also help you transform the real estate investment process completely. Real estate market data is a powerful tool as you explore new investment opportunities and grow your investment portfolio.

Are you a real estate firm looking to leverage data to grow your business? Get in touch with Datahut, your web scraping experts.


Do you want to offload the dull, complex, and labour-intensive web scraping task to an expert?

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