Data-Driven Real Estate: How a Strong Data Strategy Enables Informed Decisions and Drives Transactions


The real estate industry has always relied on data. Historical market trends and active inventory remain key metrics for real estate professionals. However, emerging technologies give decision-makers more tools than ever before. 

In today’s digital world, real estate firms implementing an effective data strategy will have a significant advantage in making decisions and signing deals. Analytics tools can condense the decision process, transform pricing strategy, and give real estate firms an advantage over their competitors. 

How Data Analytics Drives Informed Decisions

Real estate firm handing home owner their keys

Real estate leaders regularly make investment decisions, pricing strategies, and property development decisions. Accurate data is a strong predictive tool for informing this decision-making. Understanding your data and what measurements are important to your firm is critical to building a comprehensive data strategy.  Data analytics allow decision-makers to assess risk profiles, analyze trends, and perform due diligence in less time.

Condensing the Time Invested In Data to Decision Time

The more time real estate firms spend collecting data, the slower they implement decisions based on that data. In the competitive landscape that is commercial real estate, condensing the time required to collect and analyze data means decision-makers can evaluate results and execute transactions faster.

A data strategy that incorporates strong analytics tools improves the process. These platforms make it easier to identify trends, organize big data sets, and act quickly. As a result, firms with a strong data strategy have a competitive advantage. 

Industry Need To Standardize Data Sets For More Thorough Information

In order to draw reliable information from data sets, real estate leaders and developers need reliable data. Standardizing data sets across the industry would allow firms to make informed decisions quickly. For example, standardizing the terminology in data feeds for a property’s square footage or listing number would eliminate errors and save time, but this broad challenge would require industry wide buy-in, so it is imperative for individual businesses to focus on what data is important to standardize for routine reporting and dynamic modeling. 

Key Metrics: Geographic Information Systems, Predictive Analysis, Model Building

What are the key metrics in a real estate data strategy? For one, geographic information systems (GIS) offer a powerful tool for assessing locations, calculating risk, and determining ROI. Similarly, predictive analytics provide insights into market data, future appreciation, and investment strategy.

Model building represents another key metric. Investors can seamlessly review occupancy data, energy consumption, and commercial investment trends when making decisions, enabling developers to boost efficiency and lower costs.

Data Analytics Is Leading In Transactions

Analytics tools are already transforming the real estate industry. Investors can improve their marketing performance at lower costs with analytics. Tools like automated value modeling help buyers and sellers agree on prices. Big data puts more information in the hands of decision-makers in every step of the  real estate transaction––making it more important than ever for real estate firms to build an actionable data strategy. 

Data analytics help real estate investors target their marketing efforts. Analyzing target audiences and evaluating the effectiveness of past campaigns can mean lower costs, higher conversion rate, and increased ROI. In addition, a data-driven marketing strategy can help brokerages optimize their prices and tailor advertisements for niche markets. These strategies translate into more listings without increasing the marketing budget.

Automated Value Modeling For Competitive Pricing

Assessing property values and setting competitive prices is both an art and a science. Data analytics tools like automated value modeling take the guesswork out of pricing strategies. What is automated value modeling? It’s a tool that takes into account multiple data sources and pricing models to determine values. 

By drawing on machine learning algorithms, automated value modeling gives real estate firms an edge when determining prices.  

Connect Your Real Estate Initiatives To Your Data-Driven Analytics With Hartman

Person holding the concept of a house through a screen

How can data analytics transform your firm’s current real estate initiatives? The experts at Hartman Executive Advisors help real estate firms implement customized data strategies to reach their business goals. Contact Hartman today to learn how data-driven analytics can streamline the decision-making process and drive transactions.


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