Computer Vision in e-commerce: 5 ways it is transforming online shopping

Computer vision is a fast-growing field, and it is changing how businesses use technology. Recent advances in computer vision have led to new uses in many industries. E-commerce is one of them.

In this post, we look at how computer vision helps e-commerce and online marketplaces. We cover product search, content moderation, inventory management, image retouching, and virtual try-on.

These uses make e-commerce marketplaces more accurate, faster to run, and easier to use. That helps them scale, earn more, and succeed.

1. Improved Search

Computer vision can make product searches on an e-commerce platform faster and more accurate. Its algorithms look at each product image and pull out visual features such as color, shape, and texture.

The marketplace can then use those features to index its products. Search results get more accurate and more relevant.

To build this, an e-commerce store first trains a computer vision model on a large set of labeled product images. The model learns to spot and pull out the visual features that matter.

This is usually done with supervised learning. The model sees labeled product images, each paired with the features it should extract.

Once trained, the model works on new product images it has never seen. You feed each image into the model. Then you turn its output into a set of visual features for that product.

Those features are then used to index and categorize the products on the marketplace. Search results get more accurate and relevant, and that lifts user engagement and conversions.

2. E-commerce content moderation through computer vision

Content moderation means reviewing and filtering what users post on an e-commerce platform. The goal is to keep posts appropriate and in line with the platform's policies. This is a key task for e-commerce operators. Spam and inappropriate posts hurt both buyers and sellers, and they damage the marketplace's reputation.

Computer vision can automatically find sensitive or personal data in user posts, such as phone numbers or email addresses. That protects users' privacy and keeps their personal data from being misused.

Computer vision also makes moderation on a marketplace faster. The algorithms scan posts and flag anything that might be inappropriate. Human moderators then have less to review, so they can focus on the hardest cases.

3. Inventory management

Inventory management is another way to use computer vision in e-commerce. It means tracking and managing the stock of products on an e-commerce platform. A marketplace needs to get this right. Good stock control keeps products on hand when users want to buy them. It also prevents both overstock and stockouts.

Computer vision algorithms can read product images and pull out the details that inventory management needs. For example, a model can learn to recognize and classify products by size, shape, and color. That makes inventory tracking more accurate.

Computer vision can also spot defects or damage in products. Those items can then come out of the inventory fast.

4. E-commerce Image retouching

Image retouching improves how an image looks so that it is more appealing. In online commerce, it can improve the user experience and raise conversions. Computer vision is a key technology behind it.

In image retouching, computer vision algorithms analyze what is in an image. They can learn to spot specific features, such as blemishes, wrinkles, or other flaws. Once they find them, computer vision algorithms can apply retouching techniques on their own to make the image look better.

Computer vision also keeps product images consistent across a marketplace. An e-commerce marketplace can build a cohesive, professional visual brand by applying the same retouching to every product image. The algorithms can also catch and fix inconsistencies in the retouching, so every image meets the same high standard.

5. Virtual try on

Virtual try-on is one of the flashiest uses of computer vision in e-commerce. It lets users try on virtual versions of clothes and accessories to see how they would look. For online stores and marketplaces, it can raise conversions and improve the user experience. Computer vision plays a key role in making it work.

Computer vision helps virtual try-on in several ways. First, it analyzes images of the user's body to build a virtual 3D model. That model shows how clothes and accessories would look on the user's body. The algorithms also track the user's movements and update the try-on in real time.

Computer vision also improves the quality of the try-on itself. For example, computer vision algorithms can remove noise and other flaws from the input images. They can also improve the lighting and contrast in the virtual try-on scene. The result feels more realistic and more enjoyable for users.

Conclusion

Computer vision is a valuable technology for e-commerce and online marketplaces. It makes many tasks more accurate, faster, and easier for users, from product search to content moderation and inventory management.

Do you want custom computer vision solutions for your e-commerce store or marketplace? Our team of experts can help as part of our broader AI solutions for ecommerce. Contact us to talk about how we can improve your e-commerce and online marketplace operations.