The growth of ecommerce over the past two years has led retailers to evaluate the online customer experience. Preventing lost sales and working to reduce factors that lead to cart abandonment—which has reached a staggering rate of 70%— has s become a top priority for ecommerce retailers. In fact, in 2020, 73% of global online businesses cited cart abandonment as an issue.
Mobile ecommerce use has seen a steady increase and is expected to grow another 15.2% this year. But mobile shopping has unique difficulties when it comes to cart abandonment. For instance, the limited space on a smartphone requires retailers to provide relevant, personalized product results to reduce the time spent scrolling and searching for a product—ultimately reducing lost sales.
A retailer can use image similarity technology to provide relevant product recommendations to consumers. The software generates recommendations based on artificial-intelligence-identified patterns between images. Using image similarity technology, retailers can improve and influence the shopping experience, from the time consumers first start browsing to checkout.
Provide upsell opportunities on shopper wish lists
Creating a shopping list is one of the first steps in the purchase process. A consumer recognizes the need or want for a product but might not be ready to buy it yet. Retailers can use mage similarity to influence shoppers to make a purchase inspired by their wish lists.
With ecommerce consisting of 46% of all apparel sales, this retail segment, in particular, is highly dynamic. This is due to the seasonality of items, customers’ unique fashion tastes, and the ever-evolving definition of what’s trendy and in style.
Using image similarity, if a shopper adds blue exercise leggings to their “favorites” list, artificial intelligence can display workout accessories and a top in the matching color, making for a perfect upsell opportunity.
Recommend similar products on item webpages
Once a shopper expresses interest in an item, software directs them to its unique webpage. There they can find more information about a product such as sizing and fit and view images and videos. On average, there are approximately eight photos on the product pages for clothing items.
Often, retailers will place additional products under the original item based on a variety of recommendation strategies. These recommendations can be calculated using image similarity to improve effectiveness.
For example, a customer may receive suggestions for a shirt like the one they selected initially—but ultimately did not buy—in terms of fabric, material, or color. This helps shoppers find their ideal products more quickly and reduces the likelihood of abandoning a website.
Counteract out of stock issues
Once a customer has decided to make a purchase, the next step is to place it in their online shopping cart and proceed to checkout. They will not face any distractions in an ideal world that could lead them to abandon a purchase. However, we know this is not a flawless strategy. A customer may open a new tab or step away from their device. As a result, there is a risk that a customer may return to their shopping cart only to find the item sold out.
To counteract the threat of lost sales, retailers should use image similarity to display alternative products that are visually like the sold-out item. Retailers can then define the filter criteria through artificial intelligence as it best fits the customer’s needs. For example, they can ensure that the items displayed are available in the clothing size and color of the sold-out product.
Reduce cart abandonment by understanding shopper habits
As ecommerce use continues to rise, retailers can improve the shopper experience from the first click to the point of purchase. What’s more, shoppers now expect this increase in service.
Using image similarity, retailers can better understand shopper habits to inform future merchandising decisions, achieve higher sales, reduce cart abandonment, and decrease the number of returns. These benefits will improve relationships with customers, both today and in the future.
GK Software specializes in software and services for the operation of stores owned by large retail companies.