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Computer Vision in Retail — Is It Worth the Investment?


Jun 8, 2022 - 6 minute read

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Melania Sulak Content Marketing Manager

She specialises in writing and overseeing a broad range of content tailored to meet the needs and interests of IT B2B sector readers.

See all Melania's posts

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Computer vision solutions have the power to optimise your omnichannel selling strategy. In doing so, they not only serve as convenient applications customers can be delighted by, but they also provide a wealth of actionable analytics your business could leverage. Equipped with a range of in-depth data insights, you could increase profitable sales, enhance your operations, reduce losses, amplify security, and manage your store in real time.

With an unwavering shift towards omnichannel, now might be the most opportune time to invest in powerful new retail portfolios that will meet customers’ existing and evolving demands.

However, is the time and development cost of computer vision applications really worth it?

Should Your Retail Business Invest in Computer Vision?

If you’re looking to ensure that your customers have a consistently great shopping experience when they turn to your brand, employing computer vision solutions could be one way to achieve this.

As buyer journeys begin comprising more and more digital touchpoints, the key will be to make sure all your physical and virtual channels are seamlessly connected and in sync. Computer vision applications can serve as an effective bridge between the online and offline shopping experience. In serving as the key connector, the vast amount of advanced analytics they generate can transform your operations at their very core.

A digitally-led transformation of your processes can become one of your biggest differentiators. When cutting-edge technology is applied effectively, it can help you establish seamless omnichannel connectivity — a feat that not many retailers today have yet accomplished.

The rapid expansion into digital channels propelled by the pandemic has been catalytic in terms of convincing on-the-fence retailers to make greater investments into e-commerce avenues.

However, the pace of change has many retailers struggling to truly keep up with customer expectations. As such, in deciding to expand your retail solutions portfolio by adopting computer vision technologies, your business would be amongst a select few industry leaders.

Top 5 Computer Vision Use Cases in Retail

McKinsey predicts that by 2030, artificial intelligence (AI) could equip retailers with the tools they need to automate their decision-making processes, allowing them to make informed decisions in real time. With the ability to make business-savvy decisions quickly, various processes from inventory management to store visitor analytics could be leveraged like never before.

The vast volumes of data insights supplied by computer vision technologies can help retailers adjust to an increasingly dynamic market environment and introduce automation in a range of different areas.

Below are a few examples of where and how computer vision can be applied in retail for the greatest added value.

Online & Offline Stock Availability

Brick-and-mortar stock availability can be impactful in terms of whether consumers choose to shop with you in the future. However, today, it’s equally important to ensure that you provide precise and up-to-date information about the availability of the products you list online.

The statistics from our comprehensive “Top 5 Retail Tech Trends for 2022” industry report indicate that product availability is one of consumers’ most significant expectations:

  • 76% of consumers claim convenience is their top priority when buying online,
  • 81% of customers expect brands to offer a seamless purchasing process across all devices,
  • Only 11% of consumers are willing to wait until the product becomes available at their chosen retailer, while 33% would rather buy it in a different store.

Considering this, it’s no surprise that according to RIS’s 30th Annual Retail Technology Study, by 2023, 64% of retailers will be aiming to optimise their inventory management by implementing cutting-edge analytics solutions, such as computer vision.

By automating inventory processes with computer vision technology, you’ll be able to update your stock information in real time — ensuring your stock is in the right place at the right time.

In-Store Inventory Management

If you’re looking to ensure that your customers have a truly seamless omnichannel retail experience, automating inventory processes can be a crucial step towards achieving this aim.

Digitally enabled tools, such as computer vision, allow retailers to better control their stock levels and in-store inventory. SIM applications can be integrated with other in-store digital solutions to provide the best possible view of the inventory levels and replenishment needs.

By leveraging imaging technology, computer vision solutions can provide you with real-time information about your store environment. Cameras can automatically detect empty shelf space, and the corresponding software solution can send your staff a notification to replenish the missing stock.

With stock always there when your customers need it, their overall Customer Lifetime Value will likely significantly increase. As such, adopting computer vision applications to assist with inventory management processes can give you the upper hand in staying ahead of your competition.


Real-Life Retail Success Story

US retailer, Walmart, utilises the capabilities of AI to monitor their inventories and secure the best substitutes for out-of-stock items. Their solution analyses hundreds of variables (e.g., size, type, brand, price, customer preferences, and store inventory) to optimise stock levels and drive sales.


Self-Checkout Solutions

Recent research has found that 61% of British consumers claim that they have increased the use of self-checkouts in stores. This number is surely, at least in part, influenced by pandemic-era physical distancing requirements and increased hygienic recommendations. However, since then, the increased use of self-checkouts has evolved into a matter of consumer convenience.

Customers’ need for convenience and touchless interactions can be addressed by adopting smart checkout solutions — e.g., self-checkout kiosks, RFID-enabled smart solutions (e.g., Decathlon), or entirely checkout-less stores. The latter, pioneered by Amazon a few years ago, follows the convenience trend and helps to optimise workforce-related costs, customer throughput, and shrink. Amazon Go, and other stores that followed suit, combine computer vision, AI, machine learning, and sensor fusion technologies to recognise selected products, calculate the total basket cost, and manage the payment.

However, the majority of self-checkouts still require customers to manually scan barcodes of individual items, which — when it comes to convenience — isn’t ideal. This is where computer vision technologies can help. The applications’ imaging technology can automatically recognise products and add them to the basket without having to scan their barcodes. Such a smart checkout not only improves customer experience but also increases security and accelerates the entire payment process.

Targeted Advertising

Advanced, real-time data analytics made available via computer vision solutions can also be used to advertise to customers in a more targeted and relevant manner. Such applications provide insights on customers’ purchasing patterns, which makes it much easier to send them product recommendations or discounts that best reflect their individual buying preferences.

Analytics also enable retailers to keep their customers up to date about the availability of the products they showed interest in by sending them automatic notifications. All this serves to delight customers while helping you run your operations more effectively.

Store Visitor Analytics

By tracking and analysing in-store behavioural patterns with computer vision, retailers can make the type of optimisations to their operations that will drive a greater number of sales. This technology can be applied to accurately assess the effectiveness of store layout, consumer traffic as well as how each store’s performance differs.</span

In the long term, having access to this data can lead to significant cost savings. For instance, if the data repeatedly shows that one of your stores isn’t generating as much revenue as the rest of your brick-and-mortar locations, you can make the informed decision to close that particular store. This is merely one example of how computer vision can be leveraged for greater business success. In addition to this use case, there are various other applications of this technology that can help you take advantage of store visitor analytics.


Computer vision has already begun influencing various aspects of the retail industry — from serving to better address consumer expectations through optimising business ecosystems to full-scale digital transformation.

The new retail reality is one where out of the efforts made to try to survive, a select few retailers have been able to truly thrive. Often what sets them apart is the smart use of technology which has helped them to stay ahead of the pace of change in a rapidly evolving market. The ones who have been successful would likely argue that their decision to invest in computer vision has indeed been worthwhile.

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Melania Sulak Content Marketing Manager

She specialises in writing and overseeing a broad range of content tailored to meet the needs and interests of IT B2B sector readers.

See all Melania's posts

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