The Tech Helping Retail Landlords Find the Right Tenant Mix

In retail real estate, when the retailer makes money, the landlord makes money. Landlords pay close attention to the size and demographics of the people who visit their properties. They also try their best to find tenants that have synergy. Now, there is an entire economy of technology tools that have been built to help landlords better understand their customer base and what mix of tenants will lead to high sales. Given the major shifts the retail industry has experienced over the last few years, as more shopping has shifted to e-commerce and aging malls have fallen out of favor, data and tech tools have become a key part of both retailers’ and landlords’ business strategies.

Choosing the right tenants for a shopping center may seem simple to those outside the real estate industry, but curating the right mix requires a ton of data, careful consideration, and, perhaps, a little luck. Both retailers and retail landlords know that bringing together categories and brands that complement one another is the key to a successful shopping center. “We believe cross-shopping relationships will become an even more important consideration when planning retailer locations,” researchers from Deloitte wrote in a recent report on the future of retail. “Having a shared customer base, rather than a more traditional, one-size-fits-all shopping center layout, can boost overall consumer traffic and spending.” In many Class B and Class C malls across the country, retail owners are facing anchor tenant vacancies. This is leading to new concepts around what an anchor tenant looks like. Simon Property Group opened a hotel in one of its malls in Florida in 2021, while other malls added anchor tenants that centered around entertainment, like bowling alleys or sports-related venues.

With shopping centers evolving, the need for more data to measure demand and traffic is clear. The kinds of measurements that have been commonly used in recent years often center around movement. Footfall analytics, which is compiled through cameras, sensors, cell phones, wi-fi traffic, and even manual counting, track how many people enter and move through a shopping center. The data collected then helps landlords understand traffic patterns and identify areas with high or low foot traffic, the number of people who visited stores over a set period of time, the busiest days and times for business, and the average duration of each customer’s stay. It can also give insight into how many people walk past a store without entering, how effective marketing and sales campaigns have been, and which parts of a store are most frequently visited. This detailed insight allows landlords to not only choose tenants more strategically but also to adapt their properties to better meet the evolving preferences and needs of their customers. Predictive analytics can forecast trends, helping landlords proactively adjust their strategies to maintain competitiveness and profitability.

Platforms have emerged in recent years that aim to help better match retail landlords with the right brands for their properties. By using thousands of data points, brokers, investors, and landlords can determine if a retail brand planning to open in a particular community is a good match with a property’s data profile. These kinds of platforms often use custom algorithms and AI in helping to match vacant spaces with tenants expanding in that area. They can help close the gap for leasing brokers, who may be unaware of potential retailers that are expanding locally or nationwide. “Retailers are becoming a lot more competitive and a lot more data-driven,” said Alan McKeon, CEO of the data analytics company Alexander Babbage. “And as retailers become more data-driven, we see increased collaboration between the retailer and the landlord.”

Utilizing the extensive data collected on foot traffic and customer demographics, landlords and retailers are increasingly fine-tuning their marketing strategies to maximize consumer engagement and sales. Sophisticated data analysis tools allow for the detailed tracking of how marketing initiatives perform in real-time, enabling quick adjustments to be made based on actual customer responses. For example, analyzing traffic patterns during promotional events can reveal not just peak times but also which offers draw the most interest and which areas of a shopping center are most effective for displays. This level of insight helps in crafting highly targeted marketing campaigns that resonate with the desired demographic, ultimately enhancing the shopping experience and boosting revenue.

Owners are also looking to create more synergies in their tenant mix. Federal Realty Investment Trust, a company that operates and develops retail properties across the country, is highly focused on synergies when it curates tenants and looks to strike a balance between strong local, regional, and national tenants. “It’s not just about filling shops; our aim is to create thriving retail ecosystems,” said Jeff Kreshek, Federal’s West Coast President. “This involves a deliberate mix of large and small retailers. It’s about driving meaningful footfall, which in turn enhances the financial performance of each property.” 

But there are new technologies that go even further. Facial recognition software, a controversial technology that has been used in places like large entertainment venues to screen attendees, has been popping up in retail stores in recent years. In New York City, major retailers like Macy’s have used the face scanning tech, as…