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AR isn’t one technology but a convergence of several that came before it. They include everything from computer vision to AI to 3D modeling. And just as it borrows from other tech, it also gives back. In AR’s current era, it’s being applied to everything from gaming to productivity.
One of those areas that continues to develop is brick & mortar commerce. This extends from the benefits that AR has demonstrated in eCommerce, such as virtual try-ons. In physical retail, AR materializes in related but different ways – both customer-facing and business-facing.
Customer-facing applications include in-store wayfinding and informational overlays on products and store shelves. Business-facing applications – the focus of this series – include digital twins of store interiors that help retailers optimize spaces foot foot traffic, and product placement.
We examined such possibilities in Part 1 (Augmodo), Part 2 (Auki Labs), and Part 3 (Starbucks). These involve a combination of computer vision and AI to scan store shelves. Among other things, this unlocks spatial maps or digital twins to optimize things like inventory management.
Shelf Intelligence
Building on those narratives, the latest example to cross our desks is BrainCorp’s ShelfOptix. Working towards what it calls shelf intelligence, it achieves similar ends as the above efforts by digitizing the analog information that sits on store shelves. Once digitized, insights can flow.
For example, the company estimates that out-of-stock products, “phantom inventory,” and other related issues cost the retail industry $1.7 trillion each year. It also reports that 70 percent of consumers switch retailers or brands when they encounter out-of-stock items.
So the name of the game, according to BrainCorp, is to collect ‘ground truth shelf visibility.’ That data can uncover sales blockers or other issues that are otherwise overlooked. Acting on that data can mean tangible bottom-line results, and mitigate the lost revenue quantified above.
But one thing that differentiates ShelfOptix from the other players we’ve examined is the degree to which it automates. Put another way, it cuts humans out of the loop. Rather than equipping store personnel to actively or passively scan shelves, ShelfOptix is all about robotics.
Its technology takes shape in wheeled robots that autonomously roam store aisles like a Roomba. They accomplish all the standard obstacle avoidance while scanning shelves in a systematic way. One outcome is comprehensive live maps of store aisles and shelves for retailers to act on.
Trust Issues
Further differentiating ShelfOptix is its business model. Rather than sell robots to retailers – a tough proposition given AI’s early trust issues – it offers a managed service. Retailers get a turnkey system including hardware, software, and SaaS pricing. Call it robot as a service (RaaS).
The key term above is trust. AI isn’t strong in the trust department, given hallucinations and fears of job displacement. And that’s just in digital form… embody the technology, then set it loose, and the fears start to stack up. This is evident in what many call the robot investment bubble.
That all boils down to sales resistance from retailers – a vertical known for its tech-challenged state. Beyond their own misgivings about the robot uprising, they’ll likely extrapolate what really matters: reactions of in-aisle customers (assuming robots roam during opening hours).
This all makes the RaaS approach smart in reducing friction and giving the technology the chance to prove itself. A recent sales win with Winn-Dixie and Harveys Supermarkets will do just that, answering questions like the ROI case and how well robots assimilate in a store aisle near you.
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