Scandit ShelfView

A shelf-intelligence product combining image recognition and barcode scanning to grasp in real time whether products are on-shelf, priced right, and displayed correctly

4.1 Switzerland

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What is it

Scandit ShelfView is a shelf-intelligence product from Switzerland's Scandit, combining the company's specialty barcode-scanning technology with visual-AI image recognition. After store or audit staff photograph a shelf, the system can recognize products on the shelf, compare barcodes and price tags, and produce analysis of on-shelf availability and whether prices and the planogram comply.

What problem it solves

The most common yet most expensive problems in retail are out-of-stocks and display inconsistency: customers come to the store but can't buy, prices are labeled wrong, and displays don't match HQ's planogram — all directly lose revenue. ShelfView turns shelf status into measurable data, quickly finding gaps, mispriced items, and display deviations, shortening the manpower time of store visits and audits. It suits chain-retail operations and display-audit teams, and brand sales needing to confirm product distribution. Scandit itself is known for high-accuracy scanning-recognition technology, relatively confident in scenarios with large numbers of products and complex shelves. Adoption usually pairs with mobile devices and existing store-visit processes, and actual recognition results still depend on photo quality and product-database completeness.

Key Features

Dual image-recognition and barcode-scanning engines
Detects on-shelf availability and out-of-stock gaps
Compares whether price tags are correct
Checks whether displays match the planogram
Real-time analysis by photographing with a mobile device
Supports large numbers of items and complex shelf scenarios

Pros

Combines mature barcode-scanning tech with a solid recognition base
Turns store-visit audits from subjective observation into quantifiable data
Covers out-of-stock, price, and display dimensions at once

Cons

Recognition quality depends on shooting angle and clarity
Needs maintaining product and planogram databases to be effective

Use Cases

Chain stores using mobile devices to do store visits and quickly mark out-of-stock shelves
Audit teams checking whether each branch's display matches HQ's planogram
Brand sales confirming their products' distribution and prices at channels

Editor's Note

Scandit, a scanning veteran, steps into shelf intelligence — a practical solution for out-of-stock and display audits.

FAQ

How does ShelfView differ from ordinary barcode scanning?

Beyond barcode scanning, it adds image recognition, able to analyze a whole shelf's products, gaps, and prices at once, not just scan single items one by one.

Does it need dedicated hardware?

It leads with photo analysis via a mobile device, pairable with existing store-visit processes; in practice you still need to confirm device-camera and network conditions.

Is recognition 100% accurate?

No image recognition can guarantee full accuracy; results depend on photo quality and product-data completeness, so pairing with human review is advised.