It's a process that leverages data to gain insights and make informed decisions in various aspects of the real estate industry, including property valuation, market trends, investment opportunities, risk assessment, and more. This approach helps professionals in the real estate sector to better understand market dynamics and make strategic choices.
How To Make Real-Estate Data-Driven Decisions?
In the past, work in the real estate sector was based on traditional channels of information, and decisions were made based on the value of the property, location and target group of buyers. But today at the disposal of analytical agencies there are an incredibly many useful tools and opportunities for working with real estate analytics, which allows you to get a complete picture when working with real estate - both private and commercial.
For example, when choosing commercial real estate - shops or restaurants, - you need to have an idea about the activity of the local population, the preferences and habits of people living in close proximity to your future business. Where do they go, what do they buy and what preferences do they have? Using heat maps of foot traffic and activity, you can understand exactly where there are more people more often, and where there are significantly fewer people.
Professional real estate analysts in 2023 use various tools for their assessments, for example:
- Data on prices for the purchase and rental of housing
- Crime statistics, development plans, traffic flows
- Analytics on foot traffic, habits and preferences of local residents, as well as their behavior and other related data
- Migration and Population Da
- Social climate and popularity of nearby malls or office centers
- General demographic background
Key Uses for Real Estate Data Analytics
Data analytics allows you to make the most profitable decisions when choosing a place to purchase commercial real estate. With modern tools and capabilities, analysts can help you make good decisions and start a successful business.
Consider the use of modern real estate analytics technologies using the example of a grocery store chain. The owner dreams of opening another branch, and chooses a place to rent the premises. Even 10-15 years ago, he would have had to trust his intuition, having previously specified the prices for renting one square foot and the size of utility payments, but today such an entrepreneur has ample business intelligence opportunities in his hands.
Here are some examples of data analytics we used for day-to-day work with real estate data at GetPlace:
- Center-wide visitation trends analysis. As for term, in real estate analytics center-wide visitation typically refers to the analysis of visitor or foot traffic patterns within a specific area or location, often referred to as a "center." This could be a shopping mall, a commercial complex, a business district, a tourist area, or any other centralized location that attracts people for various reasons. Understanding center-wide visitation trends can provide valuable insights into the popularity and attractiveness of a particular area. Real estate professionals, owners of property, retailers, and urban planners use this data to make informed decisions about property development, marketing strategies, lease negotiations, and more.
- Foot traffic analytics for specific venues. This data tools in real estate data analytics involve the collection, analysis, and interpretation of data related to the movement and behavior of people within specific locations, such as retail stores, malls, event venues, and commercial complexes. This type of analysis provides insights into visitor patterns, preferences, and behaviors, which can be instrumental in making informed decisions about property management, marketing strategies, tenant placement, and more.
- Demographic insights. In real estate analytics this data involves the analysis of demographic data to understand the characteristics and preferences of populations within specific geographic areas. These insights are essential for real estate professionals, developers, investors, and urban planners to make informed decisions regarding property development, investment strategies, marketing efforts, and more.
- Cross-shopping data. In real estate analytics, this data is relevant to analyzing consumer behavior of visiting or considering multiple properties or locations before making a purchase decision. This data helps real estate professionals, developers and marketers understand how potential buyers or renters consider different options and make informed real estate decisions.
- An in-depth analysis of potential competition in real estate data analytics involves thoroughly examining the properties that could compete with a target property for buyers' attention. This analysis helps real estate professionals, developers, and sellers understand the competitive landscape, make informed decisions, and devise effective strategies to position their property favorably.
How to Find Real Estate Acquisition Opportunities with Analytics
Finding and assessing real estate acquisition opportunities using data analytics involves leveraging data-driven approaches to identify and evaluate properties that have the potential to provide favorable returns on investment
- Venue Health. Checking the health of a venue using real estate data analytics involves evaluating its performance, popularity, and potential for attracting visitors or tenants. This analysis helps property owners, managers, and investors assess the viability of a venue and make informed decisions to optimize its performance.
- Trade area size and characteristics. Checking the trade area size and characteristics using real estate data analytics involves assessing the geographical area from which a business or property draws its customers or tenants. Trade area analysis helps businesses and real estate professionals understand the potential customer base, demographics, and market trends within a specific region.
- Checking local factors using real estate data analytics involves evaluating the various aspects of a specific geographic area that can impact the value, desirability, and potential of a property. These local factors could include neighborhood characteristics, infrastructure, amenities, schools, crime rates, transportation, and more.
- Finding broader migration and demographic patterns using real estate data analytics involves analyzing large-scale trends in population movement, migration, and demographic changes. These insights are valuable for understanding shifts in real estate demand, investment opportunities, and urban development
What Makes a Good Real Estate Analytics Tool?
A good real estate analytics tool combines comprehensive data integration, powerful visualization, and sophisticated analytical capabilities to provide actionable insights. It integrates seamlessly diverse data sources, including property listings, market trends, demographic information, and economic indicators.
The tool's user interface is intuitive, enabling users to create interactive dashboards and visualizations that unveil complex trends with simplicity. Advanced analytics, such as predictive modeling and spatial analysis, should allow users to forecast market shifts and understand location-based dynamics. Furthermore, the tool should support customization, enabling users to tailor analyses to their specific needs.
Data accuracy and real-time updates are crucial for informed decision-making. Effective real estate analytics tools empower professionals to identify investment opportunities, assess property values, understand buyer preferences, and gauge market trends, contributing to strategic decisions that optimize returns and minimize risks in the dynamic real estate landscape.
Real Estate Data Analytics with GetPlace platform
GetPlace's advanced real estate data analytics service offers you data from millions of different sources, processed into easy-to-read heat maps, foot traffic, and analytic samples that allow you to draw conclusions about the situation in your area. Through the use of advanced AI, machine learning algorithms and data filtering, we provide the most accurate data available today.
The Importance of Data Analysis in Real Estate
Data analysis plays a pivotal role in the real estate industry, offering crucial insights that inform decision-making, enhance property values, and optimize operational efficiency. By leveraging data, professionals can accurately gauge market trends, buyer preferences, and property performance. This information enables them to strategically invest, develop, market, and manage properties. Using a simple and accessible platform like GetPlace, you can access the latest data for your geographical location and choose the best options for buying or renting real estate.