3 Ways Online Retailers Can Boost Sales With AI Ahead of Black Friday

Artificial intelligence is already transforming retail, with almost seven of 10 (69 percent) retailers posting increased revenue after adopting AI, a recent Nvidia study shows. That sets the stage for AI to have an even bigger presence this year as the holiday shopping season approaches.

Above all, images are often cited as a critical factor when consumers make an online purchase decision, given that consumers are not actually in-store viewing or holding a product. Computer vision, (CV) an AI technology that enables machines to understand and interpret visual data, can help retailers stay ahead of the pack by leveraging insights from images, video and text to improve and personalize the customer experience and boost sales.

Computer vision makes it easier for customers to find products they want by searching by image or photo instead of keywords. By making that possible, retailers can connect consumers with products they’re more likely to purchase. To build a computer vision retail AI focus, retailers can start by:

1. Improving data quality. 

Images tell a story and connect to consumers in ways that words don’t. No doubt, every retailer has thousands of product images. They attach metadata — which is data about the data — to the images so that consumers can find what they’re looking for via the retailer's search engine or Google search and so on. This metadata is sometimes provided by vendors and can be disjointed, misleading and noisy. With AI to help provide metadata — or to verify already provided metadata — retailers can more quickly speed up the process and improve data quality. With humans as a final check, retailers would achieve more accurate search results and hence more revenue.

2. Enabling shoppers to do a visual search. 

Online retailers can use computer vision technologies to help consumers identify styles they like and then find them online. By enabling shoppers to do a visual search on company websites, consumers will be more likely to find what they’re looking for faster — and to find it on your site, not your competitor’s site. Again, technologies exist to make visual search as seamless as the more traditional keyword search.

One home goods retailer, for example, used visual search and built a snap-and-search app that allows shoppers to take pictures of product furnishings via their mobile phones and then match Pinterest pins to the retailer’s product catalog. This made it easier for shoppers to find what they wanted. Many shoppers may love a style when they see it, but don't know the words to describe it in a traditional keyword search. With computer vision tools, consumers identified styles on social media and then matched them to items visually similar. This ability increased basket size and average visitor revenue by 25 percent.

3. Personalizing the shopping experience.

A full 56 percent of consumers purchased again from a retailer that provided an online personalized interaction, research finds. Also, “personalized customer recommendations” ranked as the second AI use case noted by retailers in the Nvidia study, following “store analytics and insights.” AI tools analyze vast amounts of data, including data created as consumers view product images, to predict consumer preferences, recommend products, and optimize pricing.

In Early Innings

Even if retailers haven't invested yet in AI technologies, it’s not too late. McKinsey expects generative AI alone to unlock $240 billion to $390 billion in economic value for retailers, increasing margins by 1 to 2 percentage points. Given that AI didn’t hit the mainstream until the introduction of ChatGPT in 2022, the biggest gains are yet to come and computer vision will be a major part of that value creation.

Dr. Matthew Zeiler, founder and CEO of Clarifai, is a machine learning Ph.D. and thought leader pioneering the field of applied artificial intelligence (AI).