3 Ways Computer Vision is Reimagining the Future of Retail
Today’s retail environment is faced with a heightened demand to employ new techniques and technologies to drive efficiencies, increase product sales and improve the customer experience. New technologies with the power to drive digital transformation are gaining attention from retailers of all sizes — presenting not only the opportunity to meetcustomer expectations, but to redefine them.
Oftentimes, new technologies can be intimidating and may seem overly complex for retail scenarios. But new technologies such as computer vision are being embraced by retailers to simplify everyday tasks, from managing inventory to optimizing staffing.
According to a recent Insight-sponsored IDG Market Pulse Survey on computer vision, a majority (58%) of retail, wholesale and distribution organizations have definite plans to implement computer vision going forward. As the cost of adopting these new technologies decreases and the expected return on investment (ROI) increases, this trend is only poised to accelerate more rapidly.
How does computer vision work? Images and video captured through new or existing cameras are uploaded to the cloud or the edge, where they are processed by an AI model. This specially trained algorithm evaluates the image data for known patterns that can be used to provide actionable business insights and enable real-time management of store conditions.
While there are many potential use cases for computer vision, here are three of the most common applications that are helping retailers to improve their operations and deliver a high-quality customer experience:
1. Improving Inventory Management
What if when a customer was faced with an empty shelf when searching for a particular product, they were redirected to an alternative brand? What if in making that new suggestion, digital signage also pointed the shopper to items that go well with that product, for example, upselling a pasta buyer on a sauce and wine that match? What if inventory management could function preemptively rather than in a reactionary mode, alerting staff to products that need restocking before a customer complains or, worse, simply leaves the store emptyhanded in search of the product elsewhere?
With computer vision, in-place cameras can monitor when display shelves get low on inventory to adjust digital signage to redirect customers to similar products to ensure inventory management efforts are always one step ahead. Similarly, digital displays connected with computer vision can be used for “just-in-time” pricing as store traffic peaks or ebbs, operating similarly to price surges and discounts on ride-sharing apps: discounts can automatically be applied during busy hours or for products that need to be moved to make room for others.
2. Reducing Product Shrinkage
According to the National Retail Federation,70% of retailers report a shrink rate greater than 1%. This results in industry losses of more than $61 billion from stolen products, unauthorized discounts or customers swapping in barcodes from cheaper products onto more expensive items at self-checkout stations.
Computer vision offers retailers a simple way to combat this and allows for implementation of more advanced loss-prevention efforts. By using existing security cameras in combination with point-of-sale system data, computer vision can monitor self-checkouts and alert management in real-time if the cameras detect any anomalies.
Grocery retailers also can leverage computer vision to combat food waste, another common source of shrinkage, by monitoring environmental conditions and correlating data with other temperature sensors to identify when a freezer is malfunctioning — or whether a door has simply been left open.
3. Enhancing the Customer Experience
Computer vision also enables retailers to improve the overall shopping experience. For example, cameras can monitor checkout lines and issue an automatic alert to the store manager when another checkout counter may need to be opened. This not only reduces the wait time but improves employee efficiency because employees don’t need to wait for a teammate to signal for support. Allowing employees to work more efficiently drastically improves the shopping experience for customers while freeing up staff to focus on more pressing customer needs.
With the Insight-IDG Market Pulse Survey on Computer Vision reporting that most respondents (72%) expect to see a return on computer vision investments within 2-3 years, adoption is only expected to grow as enterprise-wide implementations become more affordable and the ROI more widely recognized. By working with a technology partner to install the necessary edge computing devices and provide training and support, retailers of all sizes can adopt and scale this technology across multiple use-cases to help drive efficiencies as they grow their business with an eye toward the future of retail.
Matt Jackson is vice president and national general manager, digital innovation at Insight, a Fortune 400 IT service provider.
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