Showrooming to Show-Stopping: Shopper Analytics Help Brick & Mortar Retail Fight Back

Posted in: Sector and Company Insights, instore analytics, prism skylabs, retailnext, shopper analytics, showrooming

In Store Analytics

While the threat of online shopping appears existential in nature, physical retail is attempting to fight back by utilizing technology that has previously been the exclusive purview of online retailers: shopper analytics.

As online shopping has captured greater consumer mind- and dollar- share, brick and mortar retail has struggled to maintain relevancy and continues to face declining consumer visits as well as sales. The term “showrooming”, popularly defined as when a consumer tries a product in a physical store before purchasing it from an online competitor, often at a lower price, occurs with such frequency that it has become part of the everyday vernacular.

Even though online retailers have been deconstructing the shopping funnel for years and have comprehensively tested nearly every aspect of the shopping experience, analytics for shoppers in physical stores is a relatively novel concept that B&M retail is quickly embracing. This post will explore the basic technologies currently utilized as well as several companies in the space.

BLE & Beacons

Bluetooth Low Energy is a Bluetooth standard that transmits signals via radio waves while using very little power, and in the case of iOS 7 devices, transmits information even when the relevant apps are not running. The ability to transmit highly relevant and geographically sensitive messages to consumers in physical stores is one critical component to measuring how those consumers convert. For example, say that after ten consumers receive an offer for a pair of jeans while they are in store but only two convert, how would one understand what the base conversion rate is to determine improvement?

Cameras, Door Counters & Heat Maps

To answer this question, shopper analytics providers are also utilizing store security cameras, door counters, and guest WiFi systems to ascertain control levels of foot traffic that correlate to certain sales benchmarks. A security camera that views the menswear section of a retail store may report how many consumers typically visit that section, while Bluetooth beacons at the entrance, cash register, and exit of the store might measure how many of those individuals purchase something from that section or another, resulting in a “conversion” for that consumer.

Although each startup’s measurement methodology may differ, they all attempt to answer similar questions: where are customers, how long are checkout lines and what are abandonment rates, how long do customers linger, how often do the same customers return, how are employees performing, how long does it take for a customer to convert, and finally, what are the demographics of in-store customers?

Using the DataFox platform, we can quickly and easily determine which companies are focused on providing answers to those questions and who the leaders are in the space. Be sure to login to see the full DataFox watchlist.

Prism Skylabs is perhaps the most visual platform, allowing store owners to graphically select areas of interest to measure customer activity, product popularity, and store interaction.

RetailNext uses both WiFi and Bluetooth devices in concert with video cameras, PoS systems, and sales promotions to determine a store’s base statistics. Each customer of the platform can also elect to receive a composite report of retailers across the RetailNext platform to ascertain how different aspects of their store’s performance compare to nationwide benchmarks and millions of retail performance data points.

Swarm Mobile produces their own Beacon devices that store owners can simply stick on the wall or counter anywhere in their stores to begin tracking a myriad number of performance measurements.

Swarm Mobile

 Explore our curated DataFox watchlist to gain exclusive insights into the leading players in the shopper analytics space:

Shopper Analytics - Funding Leaderboard