Shelf intelligence is AI-powered technology that turns shelf images into actionable insights—like out-of-stocks, price errors, and planogram issues—so retailers can fix problems faster and boost store performance.
It helps reduce operating costs, improve productivity, and increase sales by automating manual shelf checks and optimizing shelf execution at scale.
Retailers can start small using existing mobile devices, and then scale with a hybrid data capture approach that combines smartphones, fixed cameras, and robots for maximum flexibility and ROI.
Misplaced or missing items are, unfortunately, a common sight in stores.
And it’s a big problem for retailers. Despite advances in supply chain management and inventory tracking, the last few feet between the storeroom and the shelf remain a costly blind spot.
Coresight research reveals that failing to manage out-of-stocks and ensure pricing and planogram compliance costs retailers over 5% of their operating margin.
But the landscape is shifting. AI-driven shelf intelligence technology is transforming the way retailers manage stock and optimize their operations.
What is retail shelf intelligence?
Shelf intelligence is an AI-powered retail technology that turns shelf images into prioritized and actionable insights, flagging out-of-stocks, planogram gaps, and pricing errors so store teams can quickly address problems, optimize store performance, and keep products available.
While traditional methods, such as barcode scanning and manual shelf checks, do capture data, they are slow, labor-intensive, and prone to human error. Data alone isn’t intelligence, true shelf intelligence comes from the ability to analyze that data and turn it into meaningful insights that drive action, guide decision-making, and improve store operations.
The role of AI in retail shelf intelligence
AI hype is huge. New use cases, businesses, and technology spring up daily.
But in the world of shelf management, AI is a necessity for managing shelf execution at scale.
AI-powered shelf intelligence sits at the cutting edge of store technology.
It uses advanced machine learning and computer vision to transform shelf images, captured by smartphones, fixed cameras, or autonomous robots, into prioritized and actionable insights. These insights help retailers monitor store conditions and respond quickly to fix operational issues, such as:
On-shelf availability: Identifying which products are not on the shelf and those with low stock levels based on a customizable threshold, enabling timely replenishment and improved inventory accuracy.
Planogram compliance: Verifying that products are positioned according to store-specific planogram guidelines and highlighting misplaced or missing items.
Price accuracy: Checking discrepancies where the displayed price does not match the correct system price.
Machine learning models trained on vast data sets recognize packaging, logos, and different SKUs. They generate a realogram (a digital twin of the shelf) and compare it to the ideal layout to assess shelf performance.
The benefits of shelf intelligence technology
The impact of shelf intelligence technology extends far beyond automation. When implemented correctly, retailers can achieve lower operating expenses (OPEX), optimized capital expenditures (CAPEX), and increased revenue. Let’s explore some of the upsides:
Increased sales
By minimizing out-of-stock scenarios and restocking shelves faster, retailers have increased store revenue by up to 2.5%. This higher product availability also improves customer satisfaction.
The IHL Group, a specialist retail advisory firm, suggests that inventory mismanagement costs retailers $1.7 trillion annually.
AI-driven shelf intelligence ensures up-to-date stock visibility, helping to eliminate stockouts, phantom inventory, and reliance on manual stock counts. This enhanced visibility improves forecasting and replenishment accuracy, reducing both over- and under-ordering and minimizing food waste, ultimately maximizing profitability.
Labor optimization
With labor shortages and rising wages, optimizing retail workforce efficiency is crucial. Shelf intelligence automates tedious tasks like shelf audits, improving inventory accuracy, and streamlining shelf management. This reduces time spent on audits and shelf issues, freeing workers to focus on value-adding activities.
Maximizing existing infrastructure
Most retailers already equip store associates with mobile devices that can be used to capture shelves. Leveraging these existing devices minimizes the need for new hardware, enabling a phased rollout and delivering rapid ROI with minimal upfront investment.
Why now? The growing urgency for retailers
From discussions with our retail customers, it’s clear that they are becoming aware of the power of shelf intelligence solutions.
With rising competition and increasingly informed buyers, retailers are actively testing and piloting solutions to stay ahead of the curve.
And with customer loyalty on a knife's edge, product availability is more critical than ever.
Almost a third of consumers question their loyalty if out-of-stocks are a regular occurrence.
New tariffs, recent high inflation, rising labor costs, and consumers seeking more value from shopping have squeezed profitability across the board. According to McKinsey’s survey, managing cost and margin pressure now is a top-three priority for 70 percent of grocery CEOs.
This has led retailers to seek new revenue opportunities or ways to unlock the revenue potential of their existing operations, allowing them to continue growing.
Improving on-shelf availability and tightening the execution of planograms and pricing can directly boost revenue and strengthen competitive positioning.
Shelf intelligence solutions also offer a new revenue stream. Insights on product availability and merchandising can be monetized by selling shelf data to suppliers and consumer packaged goods (CPG) brands.
Finally, rapid advances in AI and computer vision have made these solutions more powerful and accessible, playing a crucial role in the ‘why now’ argument.
Today’s technology delivers higher accuracy, greater scalability, and stronger ROI, unlocking a level of performance that simply wasn't achievable just a few years ago.
AI-powered shelf intelligence
Maximize on-shelf availability and ensure price and planogram compliance with Scandit ShelfView
New technology inevitably requires investment, and shelf intelligence solutions are no exception. Retailers are understandably cautious about investing in the hardware, software, and infrastructure needed to capture and analyze shelf data.
It’s wise to start small and leverage existing mobile devices to minimize up-front costs. This will allow you to evaluate performance and assess anticipated results before increasing automation and committing to additional capital expenditure.
Once you see positive outcomes, scaling becomes more strategic and ROI driven.
Implementing a hybrid data capture model that combines mobile solutions, robots, and fixed cameras offers a flexible, scalable, and efficient approach to shelf monitoring.
This model enables retailers to tailor their automation strategy to their store size and operational needs, maximizing ROI. For example:
Mobile solutions are cost-effective and ideal for smaller stores or those with limited deliveries (1-2 times a week).
Robots excel in large stores
Fixed cameras are suitable for stores of all sizes and types and are particularly effective in environments or shelves that require high-frequency data updates.
Additionally, combining different data capture methods within the same store ensures that automation efforts target the areas with the highest potential return.
From tool to transformation
It’s essential to recognize that shelf intelligence isn’t just a new tool, but a fundamental shift in the way processes work.
The successful rollout of such a solution requires time and effort to train associates, monitor performance, and optimize the user experience.
Part of that shift involves delivering clear, actionable, and accurate insights that associates can trust and act on confidently.
Accuracy is critical. The shelf insights provided to associates must be at least 95% accurate.
Anything below that threshold risks undermining efficiency, missing revenue-generating opportunities, and failing to prevent out-of-stocks.
By focusing on process, people, and precision, retailers can ensure shelf intelligence drives substantial operational improvements.
For many retailers, the message is clear: shelf intelligence is a strategic necessity. The technology is here, the ROI is evident, and the retailers that embrace it will lead the future of physical retail.
Now is the time to stop guessing what’s happening on your shelves and start knowing.
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