AI and searching for sales in the data pile

Online shopping

In the past, casual browsing wasn’t something usually associated with online shopping. Not too long ago consumers would have carried out more considered purchasing in-store, where they can rely on the expertise of sales assistants to help them find that perfect product. But that is no longer the case.

While ecommerce used to be seen as more of a means to an end, consumers today go online both out of need and for enjoyment. With online sales now making up one in four UK purchases, a purely functional ecommerce experience is no longer acceptable.

Consumers today are looking for online stores that match the ease and level of service of in-person shopping and are looking elsewhere when this isn’t the case. For example, a customer browsing online for a new pair of shoes may not know exactly what they’re looking for, they need guidance in their decision, and if a site isn’t able to provide this, their search won’t end in a sale.

Learning from the losses

If our recent research at Google Cloud is anything to go by, this is an all-too-familiar scenario for shoppers across the UK. After an unsuccessful search experience on a retail website, more than half of consumers (54 percent) say they typically abandon their entire cart and go elsewhere if there’s at least one item they can’t find. This is having stark knock-on effects on the industry, which is losing out on around £124bn in potential sales annually because of inadequate ecommerce search functions.

But this can be avoided. Today, countless retail businesses are getting ahead in the online marketplace by putting data at their core. They’re learning from these losses, and turning to data processing, AI and ML tools to inform and ultimately transform the way they serve their customers.

AI-enhanced experiences 

One area where AI is already making an impact is in supporting brands to get a better understanding of their customers and allowing them to alter their offers accordingly. In understanding the customer base, businesses are in a better position to create bespoke online shopping experiences able to rival in-store. AI and ML solutions that can understand shopper preferences and provide recommendations are extremely useful here, offering retailers the capabilities to optimize product ordering and recommendation panels on their online stores, and drive tailored suggestions for repeat purchases. To return to the example of a customer browsing for a new pair of shoes, tools like Recommendations AI mean retailers can help them decide by directing them to products that align with what they love.

With the latest developments in GenAI, online retailers can simultaneously build even better customer experiences and simplify back-end processes. They can accelerate day-to-day tasks like online catalogue management, with GenAI tools able to use basic company data like inventory lists and product photos to simplify how products are onboarded, categorized, labeled for search and marketed. For example, product descriptions can be automatically translated in up to 100 different languages, and product images generated for different devices with just a few simple prompts. With the help of GenAI, retailers can drastically improve both the accessibility of their online store and cut down on the steps taken to do so.

Getting personal with Shopify

One such business benefiting from AI technology is international ecommerce platform Shopify, which recently announced a new integration with Google Cloud to enable brands using its enterprise retail solution to lean into advanced AI innovations.

In return for the volume of first party data that customers are now regularly sharing with brands, they expect to be understood and subsequently supported by hyper-personalized services and search capabilities. In the words of Shopify president Harley Finkelstein, delivering on this demand is a “complex and costly” problem, but one that can be achieved by putting the power of AI directly into the hands of brands.

Shopify intends to do exactly that. By supporting retailers with tools like AI-powered browse features, personalization capabilities and recommendation solutions, Shopify has empowered brands using the platform to create more fulfilling customer experiences. Shopify retailer Rainbow Shops is one brand already benefiting. Rainbow shops recently adopted Discovery AI, a tool which enables advanced query understanding and personalization, which in turn delivers better search and browse results as well as recommendations from even the broadest consumer queries. As a result, it saw a 48 percent uplift in search volume, whilst its site bounce rate decreased three-fold.

Our research found that nearly nine in 10 UK consumers (89 percent) are more likely to make repeat visits to sites that are easy to navigate. As Rainbow Shops demonstrates, delivering this user experience no longer needs to be complex, or costly.

Today, the capabilities of data and AI can be applied across the entire consumer journey, helping retailers to improve performance and enhance customer experiences in the long term. With the right technology in place, searching for sales in the data pile can be as easy as on the shop floor.