The Importance of Perfect Real Estate Data Aggregation in the Development of Powerful Marketplaces

The Importance of Perfect Real Estate Data Aggregation in the Development of Powerful Marketplaces

Rashmi Soni

Property listing sites are kept on their toes by the dynamic nature of the property market, the quick onslaught of technology, and cutting-edge competition. Property data is the backbone of marketplaces, and real estate data aggregators' ability to leverage on it dictates their market position and success.

A real estate marketplace connects customers with realtors, brokers, and property managers. Its main goal is to make it simple for consumers to look through property listings, compare them, and buy or sell them. Data aggregation companies gather, clean, and manage property data in order to supply mortgage, construction project leads, residential real estate, foreclosed properties, expired listings, and For Sale by Owner listings to markets.

The availability and accessibility of reliable data is critical to user decisions made throughout the property lifecycle, from buying, financing, and building through leasing and occupying. The effectiveness with which real estate marketplaces use this information influences their distinct market positions and success. A marketplace's user experience, as well as its development and earnings, are defined by the depth, breadth, and quality of the property data it hosts.

Accurate real estate data aggregation allows marketplaces to add value in terms of analytic features, fast and rapid searches, local information, 360-degree views of properties, and visual appeal to gain a competitive advantage.

Real Estate Marketplaces Face 4 Data Challenges

For a variety of reasons, real estate marketplaces continue to collect data most of which is lost, forgotten, or gets destroyed over a period, or its formats become incompatible with new reporting needs or datasets. All too frequently, data is not shared and is kept in silos. The situation is made worse by the lack of process documentation. The inability to identify the mechanism utilized to generate the data renders it untrustworthy and useless.

All of these characteristics have an impact on how helpful collected data is to a marketplace and its users. If data is unreliable, strategies will be skewed, targets will be impossible to create, and reporting, benchmarking, and analysis comparison would be impossible.

1.    Keeping up with the latest technical advancements.

Data aggregators are unable to use AI and machine learning techniques to collect data in real time at the scale and depth required in this hyper-competitive industry due to legacy infrastructure. This causes data aggregation to be prone to errors and thus dangerous.

Consider the dangers of manually gathering, inputting, authenticating, and verifying property data from 3,100 counties and 230,000 cities, schools, and other jurisdictions.

With so many technological advancements coming at once, it's critical for real estate data aggregators to reconsider their tool adoption and usage. According to HBR, almost 52 percent of Fortune 500 organizations have become obsolete as a result of failing to keep up with the digital transformation.

2.    The skills shortage

The pressure on real estate data suppliers to keep their databases comprehensive, accurate, and up to date is great. Aggregators with foresight are attempting to manage decades of data such as property value, asset management, client listing, and so on. However, they are unable to incorporate machine learning into their data aggregation operations due to a shortage of competent resources.

Only 5% of real estate aggregators have data management experts on staff. That's why 80 percent of businesses don't base their judgments on data "most or all of the time."

Companies are emerging in the data provider arena, allowing real estate marketplaces to get relevant data fast and at scale. They also assist them in determining what the client desires and improving the user experience.

3.    Keeping up with customer expectations

Before finalizing the purchase a few years ago, real estate customers had broad expectations about the amount of money they would spend or receive, as well as property details. They would warn friends and neighbors not to employ a certain realtor if things didn't go their way. The ability of customers to provide comments and influence a realtor's brand image was restricted.

Consumers today expect realtors to provide accurate information on the neighborhood, pricing trends, and other factors that can help them make important buying/selling/rental/investment decisions.

Even with a small $5 eCommerce transaction, customers want complete transparency. Imagine their expectations from a real estate purchase involving their life savings. While mistakes or incorrect listings might easily send people to competitors, their online feedback can help them stand out.

4.   Dealing with various data sources

One of the oldest and most difficult difficulties that real estate database aggregators face is combining data from numerous sources. Most third-party data sources now have their own taxonomies and schemas.

There is no uniform definition of a bedroom or the difference between a full and a half bath. The definition of a property's usable square footage varies depending on the data source. Property address features, such as the number of bedrooms and square footage, are not uniform.

Real estate marketplaces must compile data on residences, commercial properties, and other types of properties for sale and rent. They should also maintain track of properties that aren't on the market right now. And all of these records must be gathered from a variety of sources.

The quality of data available determines the robustness of real estate marketplaces

The real estate business is about to be thrown into disarray. It includes numerous options for reducing buyer-seller friction while also enhancing efficiency. However, the information offered by real estate databases about the property, the owner, the area, and so on must be clean, accurate, and comprehensive.

Real estate inventory volume

Real estate platforms bring buyers and sellers together. A large inventory that is well-optimized for search engines has the potential to enhance total visits and sales. Inventory aggregators' capacity to attract buyers is determined by the quantity and quality of inventory they keep.

The real estate site may provide customers with home and apartment listings, mortgage shopping, and information on residences thanks to accurate real estate data aggregation. It also allows them to evaluate how their competitors are doing.

In the inventory, there are several types of properties and related attributes.

A real estate portal should have information on everything from modest dwellings to large buildings.

1.    Property types in inventory across the state
2.    Data about crime rates and demographics of the inventory
3.    Information on surrounding amenities and emergency services
4.    Data on real estate and foot traffic to verify business viability
5.    Plans for new infrastructure development, for example, are public information.
6.    Data about the commercial real estate market

Distribution of inventory across states, cities, and ZIP codes

The size of the inventory can be estimated using data that has been accurately aggregated at scale. MLS sites, on the other hand, require data on how properties are dispersed throughout states and localities at the ZIP code level.

On a nationwide basis, real estate marketplaces compete. They require knowledge of inventory dynamics in order to achieve top rank in the real estate industry. When it comes to the total quantity of listings, a real estate portal may be at the top. However, in active markets with a high volume of real estate transactions, it may be placed far lower. For the aggregator and the site to which they are sending data, only complete, accurate, and up-to-date data can fill that gap.

Keep an eye on real estate pricing.

In the real estate industry, as in any other, price makes or breaks a deal. But how do buyers, sellers, and investors figure out what a region's fair market price is?

Customers keep a close eye on real estate listing sites for time-series data that may be used to benchmark the base price in a given area. As a result, listing sites' performance is significantly reliant on accurate real estate data collection. Because the portals are fed with the same info. As a result, real estate data aggregators must:

To aggregate and augment property databases with data from customer evaluations and social media buzz, use NLP approaches supplemented by machine learning. Add in-depth neighbourhood, crime, school, community, and other information to real-time or property-focused tax, deed, foreclosure, and mortgage data.

All of this would help a real estate marketplace assist buyers, sellers, and investors in better understanding property characteristics and acquiring an early grasp of important property trends. It will also assist businesses in predicting real estate price swings so that they may make more informed business decisions. Brokers, investors, and other stakeholders in the real estate business can then use the portals to gain access to comprehensive property data, convert customers, and close deals.

Property velocity on the shelf

The rate at which inventory is sold, or shelf velocity, is a vital performance measure that real estate investors must keep an eye on.

Buyers are purchasing more properties than real estate agents are putting on the market, resulting in lower inventory levels. It's a good sign that the real estate market is alive and well, and that home prices will rise as demand outstrips supply. Property investors should look for markets with inventory levels of one quarter (3 months) or less. Such markets' growth indicators usually trend upwards.

Fewer properties are selling against what real estate agents placed on the market due to higher inventory levels. It reflects a less competitive real estate market, with homes staying on the market for extended periods of time.

Data aggregators that can scrape near-real-time data from many time zones can assist a real estate marketplace in highlighting intriguing findings. They could include things like which markets are experiencing slow shelf velocity or why asset liquidation is difficult and slow in a given market. This would allow real estate platforms to issue appropriate warnings to buyers and investors.

Stunning photographs of real estate

For a better online buyer experience and marketplace growth, appealing property photographs are essential. Attractive property images are critical in converting potential buyers into purchases. The following are examples of visual representations of property:

1.    Still property photos that have been edited and retouched
2.    Floor plans in 3D
3.    Interior and exterior walkthroughs rendered in 3D.
4.    Walkthroughs of 3D plans

Property information, upgraded property photos, videos, and walkthroughs can be combined in a real estate marketplace to provide a comprehensive perspective of all properties on the market, including current and prior listings.

Property Marketplaces in the Future: Analytics-Driven Features

Speculation, educated estimates, and gut feeling have powered the real estate industry for years. Legacy systems were unable to unlock the value of decades of transaction records, valuations, asset management details, listing, and other datasets due to their use. They were unable to extract meaningful information in order to compete confidently and withstand market dynamics.

It's past time for real estate data aggregators to start utilising scripts and schedule macros to automate tasks such as obtaining property listings, demographic and socioeconomic data, spatial data, and even data from recently completed real estate transactions. Real estate websites can deliver granular and accurate insights to their clients while seeking and comparing homes by analysing accurately obtained data.

Customers can use data analysis to construct valuation and property suggestion models to help them find houses that best fit their budget, as well as mortgages with a high risk of overvaluation.


Advanced technology has successfully established an ecosystem for quick advancements, disruptions, and the abolition of legacy real estate marketplace processes and models. Technology has disrupted numerous businesses and industries, and the pace with which these disruptions occur is substantial. Data aggregators who keep up with technology advancements and include risk mitigation into their business models will be able to take advantage of this opportunity.

About Author

Rashmi Soni

Rashmi Soni is the head of business process management division within Triyock BPO, an integrated data and digital solutions firm. Over the past 10 years, She developed and successfully managed an extensive portfolio of more than 30+ different solutions in the fields of  Data Collection, Automation Services, Data Annotation, research and analysis, and image intelligence. Her primary areas of focus are operational efficiency, operational excellence and AI & automation.

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