In the high-stakes realm of retail site selection, millions of dollars are at stake. Retailers, brokers, and commercial executives meticulously analyze thousands of data points—from census information and demographic insights to traffic patterns—to ensure precise site selection.
The adage “retail follows rooftops” holds true as each rooftop represents a household of potential customers. With the rise of big data analytics, real estate executives are incorporating more accurate, real-time data into their decision-making processes.
Enter housing data, a game-changer in the retail site selection process. This invaluable resource is reshaping how retailers identify and evaluate potential sites. Nolan Christian, senior vice president of data licensing at Zonda, highlights the power of housing data, heralding a new era of data utilization in the retail sector.
How do retailers find the perfect retail site?
The first question our clients typically ask is, “Which market should we look into?” This question aims to find the next boom market, but, more importantly, it seeks to uncover specific areas within each market that are already booming or soon will be.
Identifying suburban sprawl and population growth requires comprehensive, accurate, and frequent data. Each company’s strategy on timing, market entry, site location, traffic flow, and proximity to amenities depends on this data. Ultimately, decisions are driven by data and people interpreting it.
What are retailers looking at right now?
Retailers use a wide array of data sources to inform their decisions. As data becomes more commoditized, companies search for unique data sets that offer more robust and straightforward solutions. This has led to an approach that combines foundational market and economic data with more targeted content, such as traffic pattern flows, rooftop tracking, occupancy observations at a unit level, and future development patterns.
What challenges do they face?
One of the significant challenges in the site selection process is calculating accurate sales projections, both in the short and long term. This plays a major part in determining the value and expected return on a specific site, as well as its relative value compared to alternative locations. Determining the rate at which new households are forming is vital for this calculation, and, historically, obtaining timely and location-based data has been difficult.
Is this where housing data comes in?
[BUILDER parent company] Zonda’s primary focus is to track the change in new rooftops, allowing us to measure both the current and future growth of the community. It’s the who, what, where, when, and “how much” of housing. We collect our data utilizing AI technology, updated satellite imagery, and a research team comprising hundreds of individuals.
This coordinated approach allows us to consistently monitor changes in both future housing developments and household occupancy on a unit level. In turn, our clients can better determine household and population counts, improving the accuracy of sales projections.
How can retailers effectively use housing data for site selection?
A large part of our work involves sitting down with each client to define objectives both at the onset of our partnership and as their strategy evolves over time. From high-level market comparisons to the comparison of multiple in-market locations, our data guides clients through every step of the decision-making process to ensure the best location choices.
For managing and displaying the data, companies use BI tools like Power BI or Tableau for trend analysis and high-level monitoring, while a map-based approach aids in site hunting and trade area reviews. To meet these needs, we provide our data in various formats: raw data exports for operations teams (for plugging directly into those BI tools), as well as map-based solutions with customizable and automated reports (accessible on both desktop and mobile) for real estate teams.
What are the key advantages and disadvantages of using housing data in retail site selection?
Avoiding the decision that leads to acquiring the wrong site is just as important as picking the best site. Once that asset is developed, efforts to improve its performance or the potential of relocation can become major opportunity costs and real-dollar costs. Having data that accurately reflects observable rooftop changes and tracks future housing developments helps mitigate risk and enhances decision-making.
