The world of commercial real estate (CRE) is rapidly changing, as consumers evolve how and where they live, work, travel, shop, dine and more. The key to unlocking success in real estate in this changing world is using data analytics. Previously, real estate professionals relied on conventional metrics such as trade area rules of thumb like 1-3-5 mile radius, or on customer surveys that are hard to scale and get stale quickly. But today, the power of consumer behavior data enables much more granular insights into both prospective customers as well the location of the site itself. With these granular insights, real estate professionals can mitigate risk, enhance their services and make better decisions to propel their businesses to new heights.
What is Real Estate Data Analytics?
Real estate data analytics refers to insights from data that empower professionals in the real estate industry to make smarter decisions to increase sales, ROI and offer better services. The process involves gathering and studying consumer behavior data and places intelligence to make informed decisions on marketing or operational decisions, site selection or disposition, or finding the right tenants for a property.
Insights from real-estate data analytics can help streamline both marketing and operational decisions, mitigating risk and enabling businesses to offer more customized services. We will look at the transformative potential of real estate data analytics, how to use these insights, and how they have been used successfully by brands.
Benefits of Real Estate Data Analytics
1. Uncovering Market Trends: Understanding evolving market trends is the foundation for success in the real estate industry. Fluctuations in the economy impact the real-estate industry almost immediately and industry professionals need to constantly track new developments to mitigate risks and make informed decisions when investing. With real-time data insights, comprehensive analysis of pricing trends, demographic data, and changes in consumer behavior and preferences can help real estate professionals stay ahead of ever-shifting market dynamics and trends. Insights from real estate data analytics can also help experienced professionals accurately forecast market shifts.
2. Informing Smarter Investment Decisions: Data analytics can enable real-estate companies to make informed decisions when it comes to investments, reduce risk and ensure optimal returns. They can accurately assess potential acquisitions or investments, and conduct in-depth analysis of property values, rental income, market growth rates, and other crucial factors that indicate a high growth area. Armed with these insights, businesses can minimize risk and maximize returns on their investments, and optimize their portfolio.
3. Enabling Property Development: Taking a strategic approach to property development requires precise and granular insights into the neighborhood, people seen in the neighborhood, and more. This level of precision enables property developers to make informed decisions regarding the type of property, pricing, amenities, and retail and tenant mix resulting in increased occupancy and customer satisfaction. For example, developers can use Near’s platform to look at proxy locations of similar properties or neighborhoods and analyze tenants’ foot traffic patterns, and consumer behavior for increased understanding of a target site with regard to brand and location affinities, demographics, and more.
4. Optimizing Merchant-Consumer Fit: Use consumer behavior data to match the right properties to the best tenants based on their preferences leading to better customer experience and more sales. With Near’s data intelligence platform, get precise insights, even down to which floor or area of a shopping mall would be the best spot for a retailer. With insights into foot traffic and visitation patterns, find the best retail tenant mix for any shopping center.
5. Performing Trade Area Analysis: With exhaustive data on consumer profiles and movement patterns, survey any place or site instant to know the demographics, preferences and footfall trends, and movement patterns of residents and visitors. For example, a luxury brand retailer can choose the right location with trade area analysis that reveals the right neighborhood which matches their ideal customer profile.
6. Improving Operational Efficiency: Operational efficiency is the cornerstone of success in the commercial real estate industry. Through data analytics, CRE companies can optimize most aspects of their operations including property maintenance, energy consumption, and occupancy rates. These insights can be used to streamline operations and uncover cost-saving opportunities resulting in reduced operating costs, heightened tenant satisfaction, and increased profitability.
7. Mitigating Risks: The real estate landscape is not without risks and data analytics can help businesses with tools to mitigate most of them. Through analysis of historical data, market volatility, real-time trends, and more, businesses can identify and mitigate risks. CRE companies can use data to make informed decisions when it comes to portfolio diversification, property acquisitions, site selection, and more to stay ahead of the curve and anticipate market trends and shifts.
There is a wealth of information available to real estate organizations if they learn how to efficiently use the data on their consumer available to them. Interested in experiencing the transformative power of data analytics? Embrace real estate data analytics and tap into the boundless potential of data.