Young woman shopping online with credit card and laptop at home

With online sales up 44 percent year-over-year, the highest e-commerce growth in two decades — according to data from DigitalCommerce360 — Qubit aims to help brands take advantage of the enormous growth through its new CommerceAI.

Qubit, the AI-powered personalization company, has announced its new CommerceAI model, promising to help retailers in delivering advanced one to one personalization to unlock more value from its entire product catalogues.

“Although the growth of e-commerce exceeded all expectations last year, with no sign of slowing, many customers are still frustrated with the online shopping experience because they either can’t easily find what they’re looking for or the products being recommended are not individually targeted to the shopper,” said Graham Cooke, chief executive officer and founder of Qubit. “Brands can remedy this by using modern technologies like deep learning to better understand customer behavior and create truly tailored shopping experiences; ones that connect the visitor directly with the products they’re most interested in.”

Combining customer data — including intent — and design tools, the company says Qubit CommerceAI will drive up conversion rates and customer lifetime value while reducing abandonment. And further, through its use of deep learning, the solution aims to help brands learn more about their own customers to determine the products that will drive sales.

“The way CommerceAI enhances the customer experience is by making the online journey truly seamless within the first few seconds upon a visitor landing on site,” said Tracey Ryan O’Connor, chief revenue officer at Qubit. “Since shoppers can bounce quickly, this is imperative. With CommerceAI, the visitor is immediately able to find products that catch their interest as the technology enables an unparalleled understanding of both the entire product catalogue and the individual visitor. This enables the brand to react in real-time to present the most relevant products for each and every individual.”

Moreover, according to the company, deep learning “leverages more sophisticated algorithms than machine learning, enabling the processing and understanding of massive amounts of data in real-time to power the entire end-user experience and resulting in superior e-commerce outcomes.” And the data can be leveraged for insights that e-commerce teams are able to utilize when making important business decisions about merchandize, inventory, campaigns and more.

“Qubit’s differentiator lies in its decade-plus of retail sector expertise, coupled with its real-time industry-specific data schema and novel application of deep learning through a unique partnership with Google Cloud — including the integration of Google’s Recommendations AI — and other innovative ways that the company enables the processing and interpreting of massive amounts of data within a split second,” O’Connor said.

“Qubit’s personalized one to one approach marks a move away from a segmentation-first strategy while facilitating a broader understanding of the retailer’s entire product catalogue, of which the vast majority — about 80 percent — traditionally may have not been found and accessed by browsing visitors. As a result, this method engages and drives shoppers more directly to purchase by deeply understanding both the individual shopper and product catalogue, simultaneously.”

Because every brand’s needs vary, Qubit modules can be built for the specification that will make the most impact through improved customer engagement and e-commerce performance, including one to one product recommendations, one to one product badging, personalized content, abandonment recovery, visitor pulse and replenishment.

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