How Spatial Intelligence Technologies Will Help Drive Results For Retailers And Other Businesses In 2022

By George Shaw 

With growing online sales and the climbing number of digital buyers, it is more important than ever that brick-and-mortar companies actively study their buyer behavior to remain competitive, prevent fraud, and understand how their customers interact in physical spaces. Many companies already monitor their locations for security and safety reasons using camera infrastructure but are unable to leverage this data for anything else. 

Real-time human behavior analytics for physical locations is paramount for the future of retail. Online vendors are able to understand the entire customer journey on their site. Brick-and-mortar companies are not able to easily track their customer’s journey in their store. One area that is expected to take off is that of Spatial Intelligence. Spatial Intelligence helps businesses and operators better understand the way people and objects move throughout their physical space and connect these insights to business optimization decisions that drive growth and reduce cost. These solutions will have a massive impact on more than retail. Other market segments such as commercial real estate, grocery, manufacturing, industrial, and critical infrastructure will see the benefits of observing human behavior in any physical space in real-time. 

For commercial real estate, that means companies can analyze tenant engagement with concierge services to reduce wait times and maximize tenant satisfaction or reduce “tailgating” (the use of one security guard swipe to enable multiple people to enter) at controlled entrances. Within grocery stores, grocers can measure the effectiveness of CPG displays by analyzing traffic and dwell patterns along aisles and end caps. Manufacturers can use real-time analytics to prevent accidents by addressing safety issues before they become a problem or optimizing worker paths taken in manufacturing/industrial environments to ensure maximum efficiency. 

Real-time human behavior analytics for physical locations will start to shape where items are sold in stores of the future. This technology can help uncover critical consumer behavior, helping to answer questions such as: Does milk belong in the back of the store? Do fish sell more when placed next to cheese? Do end caps really work? Where should a cereal box be placed to ensure maximum sales? Real-time human behavior analytics will make determining the answers to these questions simple. Stores can rearrange their goods as a result to ensure maximum sales. 

Spatial Intelligence can also change how stores conduct employee training. Real-time human behavior analytics in physical locations allows companies to address if staff is interacting effectively with customers. This could include anything from ensuring customers are being helped in a timely manner to making sure the proper number of cash registers are open and employees are focusing their efforts on high-margin items. 

Another key area where real-time human behavior analytics can be used is to help companies address fraud and theft in an unbiased way. By using anonymous location data, stores can predict suspicious customer behavior, like shoplifting, in physical stores in an unbiased way and address it in real-time. This also has applications in addressing organized retail crimes and detecting other types of shrinkage and fraud, such as customer returns with no customer present. By offering an unbiased and anonymous way to monitor potential fraud, Spatial Intelligence can help retailers mitigate product loss from various types of theft.

Shifting consumer trends have led shopping malls to evolve from traditional retail locations to repurposed centers, adding amenity spaces, such as co-working and gyms, becoming logistics and fulfillment hubs, and transforming into marketing vehicles. Spatial Intelligence can measure how effective these spaces and hubs are performing by analyzing foot traffic and impressions for each location, leading mall operators to optimize lease rates and attract related tenants through a data-driven approach. Additionally, impression analytics can be used to measure the effectiveness of shopping mall marketing and set in-mall advertising rates according to how many shoppers looked at a particular piece of digital content.

Spatial Intelligence is about understanding the movement and behavior of people in physical spaces and tying those insights to business outcomes. The benefits of Spatial Intelligence technology are limitless. The data provides information that owners and operators can use to make stronger business decisions. Anonymously observing people’s movement inside a store and utilizing these insights to drive critical business goals will have a lasting beneficial impact on a company’s bottom line. 

About The Author

George Shaw

George Shaw is the Founder and CEO of Pathr.ai™. An accomplished industry veteran working at the intersection of data and engineering, Shaw is a true innovator in the fields of spatial intelligence, machine learning, artificial intelligence, and related technology solutions.

Prior to founding Pathr.ai™, Shaw served as Senior Director of Technical R&D at AltSchool. He additionally held senior technical positions at Intel and Target, working respectively as a Principal Engineer and Principal Data Strategist in Consumer IoT.

Preceding Intel and Target, Shaw was a Technical Fellow & Scientific Advisor and Vice President of R&D at RetailNext, revolutionizing the way retailers generate and utilize data about how customers move through their stores. He also served as a consultant at Second Spectrum, implementing spatiotemporal pattern recognition and machine learning technology to provide real-time insights based on NBA player movements.

He has served as an advisor to multiple startups and emerging technology entities and holds multiple U.S. patents for his inventive work in the areas of retail analytics methodology, customer movement and path analysis.

Shaw earned his B.A. from Boston University and M.S. from MIT.

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