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Why Augmented Reality-Based In-Store Navigation Is A Smart Investment For Retailers

Andrew Makarov, MobiDev

By Andrew Makarov, MobiDev

Augmented reality (AR) technology has been a mainstay in the retail industry for a number of years, generally used to allow customers to virtually try a product before purchasing. Some of the biggest players in tech, such as Google, Microsoft and Apple, are pushing forward new developments in the field of AR, and navigating indoor spaces via AR is becoming more and more attractive and possible.

A recent A.T. Kearney survey said that more than 60% of those responding indicated that their top desire would be to leverage technology to decrease the time needed to navigate store space.

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Giving customers improved ability to navigate within a store increases loyalty to the brand. And when adding AR-based navigation to customized, data-driven offers made in real time and a digital catalog, the benefits of AR-based navigation go far beyond simply helping customers get from point A to point B.

Already, we have been seeing various implementations of in-store navigation systems. Major shopping centers like Target, Mall of America, Harrod’s, Ginza Six and Carrefour have used beacon technology to create in-store navigation solutions. The beacon-based systems originally were tasked with locating a device of a possible customer in close proximity and passing along a special offer or a coupon code.

These first-generation systems had limitations when trying to deal with the exact locations of customers, however. On average, beacons can provide an accuracy of five to six meters, which is acceptable when walking between gates at the airport, but might be frustrating when searching for certain products in a store.

In a larger store, a beacon-based solution becomes expensive, stemming from a combination of installation costs, maintenance and the number of beacons required. As a result, a number of retailers have looked into WiFi Positioning System, an alternate solution tied to the already existing WiFi access points, with accuracy ranging from five to 15 meters.

In 2014, Apple started a mapping program for indoor spaces based on WiFi positioning, and the system has been implemented in a number of shopping malls worldwide. Users can pinpoint their location within the space, although floor location must be manually input.

Google has implemented mapping within IKEA, Macy’s, Mall of America, Bloomingdale’s, The Home Depot and other retail locations, with the similar requirement that users choose their floor manually.

Project Tango is a technology used by Lowe’s and Walgreens to provide digital navigation features through their aisles, with a range of virtual shopping options to enhance customers’ shopping trips.

This solution, however, had a limitation — it was compatible with just two devices. In 2018, the project was closed, with Google ARCore filling the void ever since.

AR-based indoor space navigation is presently able to mitigate some of the drawbacks and weaknesses of existing solutions, offering positional accuracy to within a few centimeters, and is capable of displaying a virtual path complete with signs and arrows to assist in navigating a store space.

This solution uses visual markers that are located on the floor or walls and have the appearance of a poster. Once scanned by a shopper, a marker triggers an algorithm to determine the shopper’s location within the building, automatically determining the exact floor, and generates a route to whichever product or department the shopper has indicated, delivering an impressive AR experience to the customer.

This technology isn’t limited only to B2C applications. It also can be used internally to guide workers and staff through office buildings and inventory warehouses.

There were 1.05 billion devices enabled for AR as of May 2019. This widespread adoption allows retailers to use AR technologies with confidence that they will be compatible with a majority of their customers. When paired with machine learning and data science, AR has the ability to use past patterns of customer traffic to improve the efficiency of placing products and predicting future sales volumes and trends.

Andrew Makarov is the Head of Mobile Development and Augmented Reality Lead Solution Architect at MobiDev. Makarov has been involved in integration of innovative technologies like augmented reality, Internet of Things and machine learning with custom retail software solutions for clients from the U.S. and Europe. He is an active speaker at tech conferences including MobileTechCon, DevFest, SmallBusinessExpo and Webinale.

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