The Pressure Is On To Advocate For Better Data Quality

The demand for data

In a 2018 KPMG Global PropTech survey, 49% of participants thought that AI, big data and data analysis were the technologies likely to have the biggest impact on real estate in the long term. 

But fast forward a few years later and real estate professionals are still facing challenges figuring out how to actually utilize data. Another survey confirmed that 80% of real estate firms still do not have “most or all” of their decision making led by data, with a mere 5% of firms saying their transformation efforts have been led by someone with sufficient knowledge of data analytics. 

Real estate needs to prioritize Data Quality, not data quantity

A McKinsey report found that for many real estate developers and investors, there is a real frustration with the disconnect between the sheer availability of data and the difficulty of harnessing it for quick, actionable insights.  For them, there is a constant tug-of-war between understanding, for example, when to acquire property and knowing when to trigger development. How do portfolio holders assess conditions sufficiently (and accurately enough) to know when to divest or capture value when it comes to optimizing property value? 

While there is an abundance of data in the sector for interested parties to work with, manually curating and verifying the relevance and timeliness of data is still incredibly time-consuming and prone to error. It explains why there is an emergence of AI-powered data quality technologies that property stakeholders can utilize in order to automate much of that work for them and still retrieve valuable insight. 

The difference that good data quality makes

Residential property professionals face the same challenge. 

A Deloitte survey of over 750 CRE respondents identified “lack of availability of quality data to make timely decisions” as one of the biggest challenges the industry faces today. 

More brokerages and agents are tapping into tech solutions that offer in-depth analytics and comparisons, helping sellers to set more competitive prices and helping buyers with better recommendations at their price points and preferences.

Good quality data helps agents make an evidential case that identifies best-case scenarios and alternative options, with data-backed recommendations that can set them apart from the competition in simple but highly effective ways. 

As for poor data quality…

Deloitte studies found that data quality is a huge challenge for commercial real estate respondents when it comes to using AI/ML technologies. Poor data quality could stem from something as simple as an extra bathroom being mistakenly inputted as a guest bedroom, instantly making the agent’s portfolio inaccurate and pricing points misleading. 

Compounding the issue is the sheer amount of data sources:

• Mortgage applications
• Appraisals
• Demographics
• Lifecycle stage
• MLS listings
• Neighbourhood
• Deeds & registration 
• FSBO listings etc etc

And the list could go on. Data decay also occurs when data points become increasingly outdated, adding to the level of data inaccuracy and irrelevancy, ultimately preventing agents from serving their clients to the best of their ability. 

After all, the endgame of data really should be to help agents foster flourishing client relationships with integrity, transparency and flexibility.  

Enter the rise of Zero-Party Data 

Recent years have shown many consumers feeling like they’re losing control over how their data is being collected and used by companies. But despite these lingering concerns, consumers nevertheless are demanding more personalized experiences from brands, and the world of real estate is no different. 

Most marketers are familiar with:

• Third-party data (data collected by external parties, aggregated and sold in data exchanges)
• Second-party data (another company’s first party data, acquired through partnerships)
• First-party data (data collected directly from customers via a website) 

Zero-party data is the new kid on the block but ultimately the one that matters most. It refers to data that customers provide to brands voluntarily and intentionally. Although first-party data is still valuable to companies for sharing consumer data willingly and tracking a person’s online behavior, it’s really still about collecting more data, as opposed to having the consumer really volunteer it. 

Zero-party data works within a privacy-focused arena and benefits both sides. Consumers are offering up their data intentionally, actively volunteering specific information, and agents get a much more accurate idea of who the consumer is and their preferences. 

First-party data is like an agent asking a couple if they’re interested in looking at the market and they say yes. Zero-party data is more like the couple telling an agent they’re expecting, and they’d like to be looking at three-bedroom homes in a year’s time. The quality of that data is unmatched. 

Realforce helps brokerages streamline, scale and analyze their operations with precision and ease. 

Profitable real estate agents thrive on strong relationships. Realforce’s powerful platform is not only industry-specific, but empowers agents to unify their customer data and unlock deep customer insights, personalization and increased engagement. 

This superior customer experience fuels referrals, repeat business, increased profitability and ultimately, lasting relationships.