The real estate market, traditionally slow to embrace new technologies, is currently experiencing a wave of innovation. Increasing numbers of ‘proptech’ companies are developing applications and platforms to facilitate buyers, sellers, and professionals. This progress requires a constant integration of real estate data, prompting many companies to ask themselves: should we collect and manage this data ourselve (build) or purchase it from a specialized data provider (buy)? This article explores why the ‘build or buy’ dilemma often poses a challenge and why purchasing data generally proves to be the better strategy, with a focus on costs, time, and quality.
Common mistakes with real estate platforms
Many proptech companies, as well as real estate investors and lenders, contemplate whether collecting and managing real estate data should be part of their core business. As a specialized data provider, we have extensive experience with such clients and recognize that further digitalization and access to high-quality real estate data are crucial for their core processes. Many of our clients initially decide to develop their data needs in-house (build). While this seems like a logical choice given the necessity of real estate data, in practice, collecting and managing this data is often much more complex than expected. Additionally, collecting real estate data is rarely a distinguishing success factor for end clients. The core activities of these companies typically lie in software development, building networks with clients and suppliers, and developing in-depth knowledge of real estate processes.
Below, we explain the top three reasons why purchasing real estate data is a better choice than building it in-house.
The Top 3 Reasons Why Purchasing Real Estate Data is a Better Choice Than Building It In-House
- Costs: Attracting the Right Personnel and Setting Up IT Infrastructure is Expensive
Setting up and maintaining a data team and infrastructure entails significant costs. This includes salaries for highly qualified data engineers, data scientists, and developers, as well as costs for hardware, storage, cloud services, software licenses, security, and ongoing maintenance. Many parties we speak to report that the actual costs are much higher than initial estimates, leading to substantial budget overruns and an unrealized business case. A specialized real estate data company can always organize this more efficiently and with higher quality at lower costs because they can serve multiple clients on a scalable basis. - Focus: Real Estate Data is Often Not a Distinctive Proposition, But It is a Distraction
Let’s be honest, owning self-collected real estate data does not offer a distinctive value proposition for many software providers, real estate investors, and mortgage lenders. Why would you spend all your time and energy on this when you could focus on activities that truly set you apart? Many of our clients focus on developing software that supports real estate processes or professionals. Distinctive features often lie in the network of clients and suppliers and/or the digitalization of real estate processes, such as buying, selling, or financing real estate.
Collecting, understanding, and manipulating real estate data, as well as setting up a data organization, requires significant time and attention. Depending on the data needs, it can take 1 to 3 years to attract a team and set up the necessary infrastructure. Particularly if parties decide to develop an automated real estate valuation model themselves, a lot of time and focus is required.
Additionally, companies need to consider peripheral issues such as privacy regulations, keeping systems up to date, ensuring data quality, complying with regulations, securing data, and maintaining data infrastructure. All of this leads to considerable distraction from core activities and delays the introduction of new features and products that are truly distinctive in the market. You should therefore seriously ask yourself: do I want to spend my time and energy on this? - Data Quality: Specialists Do It Better
The data quality of specialized data providers is often superior to that of organizations where data is not the core product. Specialized real estate data providers have years of experience, advanced technologies, and access to extensive datasets that are difficult to replicate internally. Furthermore, self-built systems and real estate valuation models usually lack the quality and reliability that specialized providers can offer. This can lead to lower product quality and many questions from end users, which places additional pressure on the support department.
Conclusion
For many real estate companies, the ‘build or buy’ dilemma for real estate data is a crucial decision. While it may seem attractive to have an in-house data team, the complexity and investment are often underestimated. The costs, time investments, and quality differences strongly point towards purchasing data. By collaborating with specialized data providers, companies can focus on their core activities, innovate faster, and better serve their customers.
