When Shelves Go Digital: The Next Frontier of Retail Intelligence

Tom Gehani, VP of Product and Growth at Simbe, explains how real-time shelf intelligence helps retailers uncover hidden inefficiencies, recover lost sales, and create more connected, customer-centric shopping experiences.

In modern retail, every misplaced label or empty shelf represents more than a lost sale. It’s a lost moment of trust. 

As shoppers blend online convenience with in-store immediacy, retailers are under pressure to make every aisle as intelligent as their ecommerce platforms. The challenge isn’t just stocking products; it’s seeing what’s really happening on the shelf, in real-time.

That’s where shelf digitisation is rewriting the economics of retail. 

By turning every product-facing unit into a data point, real-time shelf visibility helps retailers bridge the divide between physical and digital, uncover inefficiencies that quietly drain profits, and deliver on the promise of omnichannel consistency.

“Omnichannel execution often stumbles when online promises don’t match in-store reality… Bridging that gap starts with digitising the physical shelf so it’s as transparent as the digital store. Real-time shelf intelligence acts as the critical source of truth between the two,” says Tom Gehani, VP of Product and Growth at Simbe.

Tom talks about how real-time shelf visibility is helping retailers close the gap between data and execution, turning aisles into intelligent ecosystems that drive profitability, precision, and customer trust.

Excerpts from the interview:

How can real-time shelf visibility reshape the economics of inventory management?

Real-time shelf visibility removes one of retail’s biggest blind spots: a gap between “what we think is in the store” and “what is actually on shelf”. Without this visibility, retailers face phantom inventory, lost sales, overstocks that quietly drain margin, and disappointed customers who can’t find the products they expect on the shelf. 

Digitising the shelf gives retailers a trusted, constantly updated picture of product availability, pricing and promotional execution, and placement. That insight fuels smarter replenishment, reduces shrink, and improves forecasting. 

In fact, Coresight data shows that 5.5% of sales and 5% of margin are lost to store inefficiencies that shelf digitisation can address.

One finance leader at SpartanNash told us that often what they thought was an in-stock issue turned out to be driven by misplaced or inventory stranded in the backroom. With that clarity, they recovered sales and lifted margins. 

In an industry where even a 1% improvement can translate into millions, real-time intelligence reshapes inventory economics from reactive guesswork to proactive precision.

What’s the untapped value in analysing “walk-by” data when customers see but don’t buy?

Historically, retail operated with very limited data sets. The adage of the industry used to be “stack it high, and watch it fly” – the assumption being the existence of product on the shelf was all that was needed for successful merchandising strategies. 

Modern consumers have more choices than ever, and as a result, retailers must change their execution approach. Most retailers measure success at the register, but this often misses much-needed context. 

The reason for poor sales can vary; in addition to customers viewing but choosing not to buy a product (“walk-bys”), poor placement, out-of-stock items, missing promotions, or pricing mismatches often lead to items that would have been bought losing the sale. 

For example, one in five desired items are unavailable in-store, with 24% of shoppers switching to competitors when shelves are empty, and 50% of Instacart items ordered online are substituted or not found, eroding omnichannel trust.

By increasing their knowledge of shelf intelligence along with other signals like point of sale and shopper preferences, retailers can diagnose the true opportunities in their assortments. 

For example, if shoppers repeatedly bypass an item that’s fully stocked but incorrectly priced, that insight can immediately inform both merchandising and vendor strategy. Or if an item is consistently and frequently out on the shelf, planogram optimisations that would allow a higher shelf holding capacity by removing less productive item facings could lead to better results. 

This data transforms missed sales into learnings, helping retailers fine-tune assortments, layouts, and promotions to better meet demand.

Can store intelligence predict demand shifts before they hit the POS system?

Yes, it can. Store intelligence offers the most reliable data infrastructure available to power retailers’ AI strategies.

POS data only shows demand after a sale, but shelf intelligence spots signals like fast-depleting items, unexpected spikes, or substitutions much earlier. At Schnuck Markets, leaders discovered they were missing up to ten times more out-of-stocks than expected once shelves were digitised. 

As they described it, the data revealed a demand they hadn’t realised was there until it was too late. That visibility allowed them to respond faster and adjust replenishment before sales were lost.

By surfacing demand shifts earlier, retailers not only protect revenue but also give their supply chains the lead time needed to respond proactively.

How can retailers use shelf-level data to drive dynamic, in-store pricing?

Complex supply chains, varying geopolitical conditions, changing customer preferences, and increased competition mean retailers need to be more responsive and capable of pricing changes than ever. 

A recent study by Simbe found that prices are changing much more dramatically than ever, with categories like pasta seeing a 300% increase from 15 items per store changing prices a month, to approximately 60 items by February 2025. 

Dynamic pricing can be tricky to execute correctly, however, due to the need to manage customer concerns around “surge” pricing, as well as ensuring a store associate’s ability to execute and a retailer’s confidence in pricing accuracy and compliance, even with solutions like electronic shelf labels. 

Historically, retailers relied on manual audits, which frequently led to gaps in compliance and often significant fines when shelf prices didn’t match the price at the register. Simbe’s solutions help retailers monitor both on-shelf availability and price and promotional compliance through automation and at scale, consistently, frequently, and accurately. 

That foundation makes it possible to flex prices responsibly – whether lowering perishables approaching expiration, matching local competition, or adjusting to real-time demand. Several retailers have seen dramatic improvements here; one farm and home chain reported pricing accuracy improved by nearly 90% in test stores. 

With that level of confidence, they could explore pricing strategies that protect margin without sacrificing trust.

In a world of omnichannel retail, how do you bridge the intelligence gap between physical shelf and digital shelf?

It’s clear that customers prefer retailers with strong omnichannel solutions. Buy-online-pick-up-in-store, curbside pickup, and even same-day delivery are becoming table stakes, and all rely on retailers being able to leverage their forward-deployed inventory inside their physical stores to compete profitably. 

Omnichannel execution often stumbles when online promises don’t match in-store reality, leading to substitutions and disappointed shoppers. Bridging that gap starts with digitising the physical shelf so it’s as transparent as the digital store. 

Real-time shelf intelligence acts as the critical source of truth between the two, powering ecommerce systems with accurate availability, pricing, and location data. A grocery CIO described this as “finally operating with ground truth – and the math works.” 

Once shelves are digitised, retailers can dramatically improve fulfilment accuracy, reduce substitutions, and give store teams the tools to pick faster and more confidently.

Is it time for retailers to think of shelf-edge space the way brands think of Google search real estate?

Absolutely. The shelf edge is prime real estate – just as valuable as the top slot in a Google search – because it determines what products shoppers see and buy. 

Brands big and small often spend significant parts of their marketing budgets on “slotting fees” and vendor income agreements to get preferred placements and shelf space in stores.  

But execution has historically been opaque, leaving brands uncertain if their investments are paying off. With daily SKU-level shelf intelligence, that changes. 

Retailers like Schnuck Markets now use this visibility to bring vendors hard data on placement and performance, and Simbe Brand Insights gives brands access to data and insights they previously needed to rely on costly third-party audits, increasing costs for both retailers and customers.

As one merchandising leader put it, they can finally prove if products are truly positioned and priced as intended. That transforms shelf-edge from guesswork into measurable, monetisable real estate that benefits both retailers and brands.

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