Big data is reshaping real estate development, helping developers shift from error-prone, gut decision-making to data-backed insights. A data-driven approach to real estate development has been transforming the industry for years, allowing investors and developers to boost efficiency and mitigate risk across a project’s lifecycle. Real estate data analytics can facilitate better site selection, market analysis, budgeting, project management, and decision making during every phase of the development process.
When leveraging data analytics for real estate, it’s important to understand the difference between structured and unstructured data. Structured data has a strict, predefined data model while unstructured data does not have a predefined format. Both can be used in AI models but structured data is leveraged for machine learning and machine learning algorithms while unstructured data is often used in natural language processing and is primarily useful for generative AI. Leaders in the real estate industry can rely on both to inform the
development process, enhancing efficiency and allowing for more reliable outcomes.
How Big Data Is Changing Real Estate
The real estate development landscape has been dramatically transformed by the advent of big data, and will continue to reshape the industry in 2025 and beyond. Even though developers have traditionally been resistant to modern workflows and leaving behind traditional but error-prone methods, the advent of AI is leading to an unprecedented level of technology adoption. CBRE reports that the global demand for AI in real estate is growing, and the property technology market is projected to grow by 70% to $32.2 billion by 2030. Looking toward the future, real estate leaders will increasingly look to AI and big data to tackle the contemporary challenges of the market, from slow capital deployment to construction supply shortages.
1. Site Selection
Investment and development strategies outline characteristics, from big picture items, like geographic market and asset class, to more nuanced details, including proximity to job centers, average area income and education and access to transit and amenities. Identifying opportunities that align with investment criteria can often feel like finding a needle in a haystack, but it’s also time-consuming.
Big data technology manages complex and large data sets by leveraging automation, allowing investors and developers to filter through potential investment opportunities that meet a set of predetermined criteria. When used in conjunction with internal data, investors can curate a comprehensive picture of an asset and make smarter investment decisions. Historical data, like zoning or former uses, can also eliminate assets that don’t support your firm’s investment strategy.
2. Underwriting and Valuations
Automated valuation models (AVM) have been around for a while, but they historically haven’t met the diverse and specific needs of most commercial real estate investors. New startups are beginning to change that by leveraging big data benchmarks to provide more accurate valuations.
According to research from JLL, these benchmarks include local amenities, ESG accreditations and occupant reviews, all of which can have an impact on valuation. With this data, AVMs can deliver updated property or even portfolio valuations throughout ownership.
During the acquisition process, valuation data will drive efficiency in internal underwriting and provide accurate projections. It can differentiate investment strategy and give investors the ability to look at assets differently than competitors by including non-traditional data sets in the underwriting process.
Big data reveals appreciation trends on a specific asset, forecasts pro forma rents on new developments and renovation projects and provides critical insight into demand. It can also look deeper into financial records and cash-flow models that can provide better net operating income (NOI) projections.
3. Hyperlocal Forecasting
Thorough underwriting and site selection are already a solid hedge against downside risk on an investment asset. But, by harnessing big data, we can do more.
While there is no way to predict a global pandemic that shuts down the supply-side of the economy (sorry!) or any other unimaginable event, big data can evaluate economic and capital trends that can help predict risk factors that lead to earning higher returns.
Using proactive intelligence data, investors can better forecast future trends that can impact the success of an investment. This is especially valuable for developers and value-add players that are delivering and exiting from a project in three to five years. Everything from interest rate trends and yield curves to presidential elections, trade and economic growth can affect returns on delivery. According to Deloitte research, data is one of the best ways that investors can manage and mitigate rising risk factors to actually relieve outside pressure on profit margins.
4. Predicting Returns and Assessing Risk
Big data platforms offer more unique, accurate valuations than traditional AVMS, boosting developer confidence. The platforms help do this by harnessing large data sets to assist with forecast property values and identify emerging markets. Deeper analysis powered by big data means the insights can be more granular, such as micro-level insights like zoning codes or population growth trends, allowing for more accurate valuation.
Predictive analytics can also play a role in underwriting for this reason, helping reduce costs and uncover undervalued properties. Investors who have access to precise property valuations and the ability to identify promising or up and coming areas for projects will get a competitive edge in the acquisitions process.
5. Construction Cost & Timing
Technology integration into construction is one of the biggest trends in CRE to come out of the pandemic. Building information modeling software, drones, and site sensors are a fewways construction sites use big data to drive efficiency.
Developers can’t overlook the impact of data analytics on project development. In construction, big data analyzes cost information and site details, labor productivity, supply chain trends and even the weather and traffic patterns that can impact construction schedules.
This data can provide real-time insights during construction to mitigate risk and allow for swift reaction to issues, and can also help forecast pricing to keep budgets and development timelines in check.
While the financial incentives are always the most weighted, big data can use sensor data to create safer and healthier job sites and reduce waste.
6. Tracking Urban Governance
In the transition to smart cityscapes, local governments are using big data to drive flexibility and support hybrid property uses. The data includes everything from mobile phone records that track people’s movements throughout the city and energy grid activity to geospatial land registry data.
Cities are making this data more transparent and accessible to the real estate community in an effort to democratize the planning process, according to research from JLL. This is already happening in other global cities. Barcelona and Sydney have launched pilot programs for open data portals, encouraging residents to both utilize and share data.
This data is also driving efficiencies in urban management by connecting infrastructure. Using IoT sensors, cities better understand noise and light pollution, energy inefficiencies, and structural defects.
This information is a goldmine for CRE investors. While many of these programs are early in their inception, investors should take early note of which governments have digital strategies and how they are evolving. These could become key investment markets in the future, and the data could inform future developments.
7. Data-Driven Capital Planning and Budget Control
Historical project data is essential for data-driven capital planning and budget control, empowering accurate cost estimates by compiling vendor insights from past projects. Looking at past vendor performance and project timelines also allows for better predictions, ensuring your budgets aren’t further derailed by timeline delays. Predictive spend forecasting means your team will be able to anticipate risks and identify opportunities to lower costs. Data-driven workflows will also uplevel your scenario planning and capital allocation, flagging potential issues before they escalate and require change orders. Modern real estate development software like Northspyre lets your team create different budget scenarios, evaluate bidding opportunities while avoiding any future disruptions that will slow you down and derail your project financials.
Turn Big Data Into Big Returns
At Northspyre, we understand the tremendous benefits that AI-powered data and analytics can bring to a project, and we have seen it firsthand. With the help of Northspyre’s AI technology, our clients have managed more than $30 billion in projects over the last three years, saving up to 6% in construction costs and driving more efficient development timelines.
Book a demo and see how Northspyre’s end-to-end development platform can help your team leverage data to drive higher returns.
