• December 21 2022 | 7 mins read

5 Applications of Visual AI for eCommerce

McKinsey predicts that by 2030, artificial intelligence (AI) can equip retailers with the tools they need to automate their decision-making processes, allowing them to make informed decisions in real-time. Also, research has shown that a whopping 80% of consumers prefer shopping at an online store where personalized product discovery journeys are available. Even if your store attracts like-minded shoppers, it is not realistic to assume that each customer would enjoy the exact same products, colors, styles, and designs.

In today’s competitive business world, visual product discovery journeys are set to win shoppers’ loyalty. So how can online retailers gear up for this?  

Below are a few examples of where and how computer vision can be applied in online retail for the most significant added value in the realm of personalization and beyond : 

Image Search

Visual Search is an improved alternative to traditional text-based search tools in the retail business. It typically comes with a highly convenient, user-friendly function: visual and/or image search. This is where the visitor uploads an image of a specific item, with the goal of ‘fishing it out’ from a retailer’s vast catalog. This image can be a screenshot from a camera roll, a picture sent by a friend, or an image taken in real-life (thus flexibly combining real and virtual worlds)!

The reason why smart search is a must-have is simple: shoppers do not always have the right words to describe the product they need. This is especially common in the fashion or home and living industries – with tens and thousands of design terms, customers may not be able to articulate their preferences for ‘cat-eye glasses’, ‘drop-waist sleeveless dresses’, or ‘yellow, L-shaped tufted sofa’. A simple image upload would be a powerful way to address this issue. 

The visual element of smart search is also helpful for sophistically designed items. Just imagine this: even if shoppers were design-savvy, it would feel tedious to articulate labels such as ‘D-cut vegan faux leather mauve handle bag with arched mahogany carved handle’. For customers who do not know English at a proficient level, a smart, visual search also implies reaching results without having to use potentially inaccurate translation software. Therefore, it goes to say that a visual-based AI can save customers from wasting precious time on keyboards. 

Visual Recommendation

Computer Vision technology does not only allow consumers to identify what they seek. Rather, it uses that as a baseline to encourage product discovery.

It can invite customers to ‘shop the look’, ‘complete the look’, or browse ‘visually similar’ items on your product listing sites and all the way to the checkout page. To illustrate, if a customer throws in a pink denim skirt in their cart, the system will suggest a matching jacket to go with it (you never know! The customer may end up loving the recommendation).

The AI solution can similarly pick up the idea that the customer may be into soft, feminine, or denim-based styles, thus introducing products that match that line of fashion. In cases where the consumer shows interest in a product that is temporarily out of stock, this AI solution can recommend alternatives for the time being – because why wait till restock when sales can happen right now? 

By using a visual recommendation approach – consumer data at scale can also be identified and organized effectively, allowing retailers to garner accurate insights into consumers’ preferences via click history and cart activity. Knowledge of what tends to catch the eye of consumers will help businesses plan more efficiently. It may also play a role in other forms of marketing, such as those ‘don’t forget me’ retargeting emails to customers who abandoned their shopping carts. 

Think about it this way: in brick-and-mortar stores, store assistants are usually required to introduce products that the consumer may find useful but not know about. The extended function of smart recommendations is to equip online retailers with a helpful online store assistant that shifts customers’ attention to new items they never knew they needed. 

Visual Merchandising

Fashion luxury brands operating offline stores globally hold themselves accountable to very high standards regarding brand quality and ensure a consistent brand image across their stores. They have mandates that the product display on shelves/walls follow a consistent layout and aesthetics in each store. Typically, this plan is created by a central visual merchandising team and shared with store managers globally for every new collection launch. A lot of this work is done manually with associates and managers tasked with this, which is time-consuming and several man-hours invested that can be instead reallocated to provide a differentiated customer experience

Leveraging computer vision solutions can provide real-time information about your store environment. The solution can automate their in-store shelf display audit process and launch global campaigns faster. The in-store staff can scan the entire wall using their hand-held device camera to instantly verify if the product placement is correct. If a product is out of stock in the store, other available recommendations are suggested for replacement.

AutoTagging

Visual AI can also be powerful when it comes to product tagging. For online retailers with thousands of products in their catalog, manual product tagging is time-consuming and implies huge operating costs. Human-led product tagging often comes with errors that businesses simply do not need.

These issues can be addressed effectively with smart tagging. Using visual AI features, smart tagging helps retailers tag thousands of products with thousands of attributes (whether relevant to style, cut, material, design, color, size, make, or model). This enriches business catalogs and makes products multiple times easier to find. 

When operated using visual AI, these tags can improve the search accuracy of an e-commerce platform, which will consequently leave an impact on consumers’ shopping experience. 

Smart Tagging

Augmented Reality (AR) and Virtual Reality (VR)

Although still a relatively new application, both augmented and virtual reality can play a significant role in the success of an e-commerce platform. This is particularly the case for fashion and beauty brands. In online spaces, where the product isn’t directly tangible, consumers can upload a picture of themselves and ‘try on’ the product virtually. Not only is it safer and more hygienic for the retailer (especially in times of Covid), but also it may turn out to be less time-consuming for the consumer, as try-ons take one simple click. No more nightmarish long lines in front of the fitting room!

Improved Visual AI Tools, As Close As One Click Away

At ViSenze, we aim to help online retailers create exceptional shopping experiences while uplifting AOV and increasing conversions. Having worked with 900+ global retailers – some of which include major brands in the fashion and home & living on several computer vision applications, our. – AI/ML experience and models have delivered results consistently. Feel free to read more about our industry-leading product, Visual AI SaaS platform, or simply request a demo to see what ViSenze can do for your business right here.

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