7 Location Analytics Firms for Malls and Shopping Centers
This post is the latest in our “Disrupting Retail” series. It’s our editorial focus for the month of July, including topics like in-store innovation and Amazon’s moves. See the rest of the series here.
If you want to see what retail innovation looks like first-hand, walk into a shopping mall. Faced with the option to transform or die, shopping mall operators across the country are choosing to fight back against the shifting tides in retail.
Companies like Simon Property Group, Westfield Group, and Brookfield Properties are digging in and finding innovative ways to use prescriptive and predictive analytics to increase profitability at some of the biggest shopping centers in the world. Location analytics firms working in the retail space are providing mall owners with unprecedented information about consumer movements and behaviors to drive decisions and build marketing strategies.
Whereas the retailers located inside shopping malls are most interested in using advanced analytics to drive conversions, mall operators are focused on mining foot traffic data to influence tenant decisions and traffic planning, and to determine the best mix of stores inside their buildings. According to research from McKinsey & Co., mall operators that use advanced analytics to select tenants, optimize mall layouts, and determine rents see revenues rise by 20%.
Here are seven tech firms that malls, and other retail giants, are relying on to collect and study location data gleaned from shoppers’ mobile devices.
GroundTruth’s location-based marketing platform was developed to allow marketers in a number of verticals, including malls and shopping centers, to understand, influence, and predict consumer intent. The company’s geofencing advertising platform uses a combination of automation and human touch to apply virtual boundaries around locations, so malls can reach consumers with targeted offers as they enter the parking lot or leave specific stores. GroundTruth also serves up visitation data, audience data, and trade area data that mall managers can use to better target audiences both online and offline.
Placer.ai offers its own dashboard that provides insights into audience and competition with the goal of helping its clients discover new business opportunities. Shopping center operators use Placer.ai’s tools to attract high-value shoppers, engage their ideal retail tenants, and identify acquisition opportunities. For example, shopping centers can use the data gathered by Placer.ai to find untapped audiences, understand current tenant health vs. local competition, and identify new competitors and emerging trends in the retail industry.
The retail analytics firm ShopperTrak works with shopping centers to measure foot traffic and benchmark performance. ShopperTrak’s real-time analytics generate insights into how many shoppers are walking in a mall and when they’re coming. The company says its platform can accurately count shopping center traffic, compare traffic performance to prior periods, and predict future traffic trends. From a marketing perspective, ShopperTrak also provides mall owners with quantitative insight on the impact of their latest campaigns.
RetailNext analyzes more than 800 million shoppers a month across dozens of retail chains. The company’s in-store analytics platform integrates with both physical and digital data sources inside and around shopping malls, using existing infrastructure like analog and IP cameras. Using the data that RetailNext generates, shopping center operators can calculate the return-on-investment from their marketing initiatives, and they can identify daily, weekly, or yearly traffic cycles. Shopping centers can also leverage foot traffic data to drive their retail leasing strategies.
A retail analytics provider that has been operating for more than a decade, CountBOX uses video-based technology to track store traffic and identify peak shopping periods. Mall operators have the ability to analyze return visitors, view foot traffic data in real-time, and compare how traffic patterns differ from floor to floor. (For example, why are stores on the third floor seeing more foot traffic than those on the second or fourth floors?) With this data in hand, mall operators can identify new opportunities and work to boost individual store sales. CountBOX says its data is up to 98% accurate.
Mall operators can use RetailFlux’s analytical tools to understand how shoppers are behaving inside their walls and push foot traffic toward less populated areas. Using video analytics collected from in-store CCTV systems, coupled with retail people counting, heat maps, and footfall solutions, RetailFlux is able to identify key hot zones and cold zones. Based on in-store shopper journey parameters, mall managers can design events to get shoppers into under-utilized areas of their malls. This keeps tenants satisfied, and helps to increase the rents that mall operators can charge.
Dor uses thermal people counters that can be stuck over doors to collect accurate foot traffic data. That data can be accessed by retailers and mall operators, and integrated into any point-of-sale system using Dor’s API for custom applications. Because Dor doesn’t rely on any in-store networks, it’s a particularly effective solution for mall operators. With foot traffic data in hand, operators are able to make future predictions and track how operational decisions create change for their shopping centers. They can also compare store-by-store performance.
Stephanie Miles is a senior editor at Street Fight.