Brick-and-mortar retail leaders regularly evaluate store layouts, fixtures, planograms, staffing, and product offerings to optimize customer convenience and basket size. But how do they best determine and understand how shoppers move around their stores ― where they go, in what order, how long they stay, when they arrive ― and how these behaviors map to actual sales?
The cloud-based RetailNext store analytics platform from RetailNext, a real-time in-store monitoring and Applied Big Data solutions provider, utilizes video analytics, on-shelf sensors, and data from POS systems and other sources to enable merchants to monitor, collect, analyze and visualize in-store data.
The newest platform upgrade ― RetailNext v4.0, yet to be announced formally ― delivers traffic heat mapping, demographic detection and other innovations that help retailers better understand and leverage shopper behaviors. Among the new enhancements, RetailNext v4.0 offers:
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- Multi-Camera Heat Maps that combine data from multiple camera views into a single, storewide traffic heat map;
- Male/Female Demographic Detection, based on sophisticated gender recognition software;
- Advanced Wi-Fi-Based Analytics that measure the behavior of Wi-Fi-enabled smartphones and tablets in and around the store’s environs; and
- Employee Traffic Exclusion, which eliminates associates from video traffic counts, based on assigned Wi-Fi tracking tags.
Gander Mountain, Cache, Gordmans and The Art of Shaving are among the latest merchants to adopt RetailNext, bringing the total number of stores committed to using the technology in 2013 to 5,000.
RetailNext is a “mission-critical tool” that provides Gander Mountain with insights that are “helping us detect and execute on opportunities to make changes that can lead to increased sales and bottom line improvement,” said Chris Schindler, Director of Operations of Gander Mountain, in a press release. “We use the platform for a variety of applications like staffing optimization by store, measurement of marketing programs, and even evaluating the impact of remodeled store departments on the key metrics that we know lead to sales.”
RetailNext v3.5, announced October 2012, delivered increased support for more video camera models; more scalable and efficient video processing and storage; and fully redundant data storage.
The RetailNext tool collects approximately 10,000 data points per store visitor to help store operations executives measure successes, execute changes and identify opportunities for growth. Across the full customer set of more than 60 retail chains, RetailNext collects more than 75 petabytes (75,000,000 GB) of raw data across more than 400 million shopping trips per year. The information is delivered from more than 30,000 sensors across thousands of stores in 20 countries.
