Retail operations is a field where computer vision applications are growing. This technology can help many companies tackle their retail pain points. In doing so, companies can transform their customer experiences.
First, what is computer vision?
Computer vision is an interdisciplinary field that explores how computers can gain high-level understanding from digital images or videos. By perceiving physical objects in an image, the algorithms at the heart of computer vision technologies seek to understand aspects like shape, size, and color. Computer vision is closely related to artificial intelligence, computer graphics, and computational geometry.
How can retailers utilize computer vision?
Computer vision has various applications in retail settings, which can include many functions of retail operations. If you’ve been to an Amazon store, you might have seen a lot of this technology in practice. In those store environments, you can scan your Amazon Prime account when you walk in, shop, and then walk out. You never have to encounter a checkout clerk or other human. This is because computer vision technologies:
- Sort the items that are being purchased and streamline the checkout process.
- Identify individuals as they move around a shop.
- Detect when a customer enters or leaves a store.
- Track customer movements within the store.
All of these processes help retailers understand where customers are going and how much time they spend in each area. This can later be used for analyzing shopping patterns, optimizing marketing, and improving the layout of a store.
How can e-commerce retailers use computer vision?
Computer vision is not just a useful technology inside a store, but can be increasingly helpful with e-commerce businesses. One primary use case involves helping with product searching and classification. By understanding the details of a product and its features, computer vision can help shoppers find what they’re looking for quickly and accurately.
Additionally, computer vision plays a role in recognizing objects in photos that are uploaded by users. This allows them to search for similar products or related items. Customers might use a reverse image search on Google to find a photo of a celebrity dress they love. Computer vision with search algorithms then help customers by highlighting similar aesthetic pieces at various price points.
This can still be taken a step further. Computer vision can be used to provide customers with a more immersive shopping experience. By using computer vision to recognize objects in a retail environment, an augmented reality app can overlay product information and ratings on top of what the customer sees through their device’s camera. This gives customers a better understanding of what they are looking at. It also allows them to make more informed purchasing decisions.
Now, retailers can also explore Computer Vision with Shutterstock. Developers can utilize the massive array of Shutterstock images to train computer vision models. These models are at the very center of helping retail brands to recommend relevant products and packages to consumers and are continuing to be scaled to do so much more.
Want to learn more about computer vision and its applications before you dive in? Download Shutterstock’s Computer Vision White Paper.
See how Shutterstock can help train your computer vision models.
License this cover image via Login, Tohid Hashemkhani, Prostock-studio, and tele52.
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