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The NRF Big Show arrives in New York on Jan. 14, and that means companies will be rolling out their latest technologies and partnerships to start off 2023 strong.
Google is getting a head start. Just ahead of the event, the company’s cloud division shared details on four new AI-powered releases for retailers on Friday. The technologies are designed to advance in-store shelf checking, as well as ecommerce browsing and recommendations.
The launches show how Google Cloud is expanding a suite of products for others. This is distinct from Google Shopping through the search giant’s own site, which has also gotten plenty of upgrades over the last year.
"Upheavals over the last few years have reshaped the retail landscape and the tools retailers need to be more efficient, more compelling to their customers, and less exposed to future shocks," said Carrie Tharp, VP of retail and consumer at Google Cloud, in a statement. "Despite uncertainty, the retail industry has enormous opportunity. The leaders of tomorrow will be those who address today's most pressing in-store and online challenges with the newest technology tools, such as artificial intelligence and machine learning."
For those looking to see how AI will play a role in commerce, Google’s technologies offer a few use cases, from store operations to personalized online shopping.
The technologies include:
A shelf-checking solution
This aims to ensure that shelves in stores don’t become low or empty. Built on Google’s Vertex AI Vision, this uses Google’s database of people, places and things to help recognize products. It uses two AI models: a product recognizer and tag recognizer.
The goal is to solve a particular problem: “how to identify products of all types, at scale, based solely on the visual and text features of a product, and then translate that data into actionable insights.”
The AI tool can identify products based on images taken from a variety of different angles. Currently in preview, the product allows retailers to retain their imagery and data.
An online window shopping tool
This feature is designed for browsing and product discovery.
Here’s how it works: Shoppers choose a category, such as “women’s jackets.” Then machine learning selects optimal ordering of products in the results. The system, which is powered by Discovery AI, learns the ideal order on each page, and improves over time with more data.
The feature can be used on browsing, brand and landing pages.
Typically, products are ordered based on best-selling items, or human-written rules. The AI tool essentially self-curates a selection. For retailers, the potential benefits are more revenue per visit and team time saved.
Personalized search and browsing results
This is designed to show customers products that align with their tastes and interests.
AI is employed to analyze a customer’s behavior on an ecommerce site, such as their clicks, cart, purchases and more. This helps to determine shopper tastes and interests, and AI then moves up products that match them in results.
Google said the results are based solely on an interaction on a specific retailer’s site through an account or first-party cookie, and not linked with Google more widely.
Upgrades to Recommendations AI
This is designed to help retailers arrange and coordinate recommendation panels that appear on ecommerce sites. New capabilities include:
- Page-level optimization to help an ecommerce site dynamically decide what product recommendation panels to show shoppers.
- Revenue optimization uses machine learning that helps to identify recommendations that will increase revenue per user session.
- A third tool, built with DeepMind, uses machine learning to analyze product categories, item prices, and customer clicks and conversions. It finds recommendations that balance customer satisfaction and revenue lift.
- Buy-it-again, which provides recommendations for repeat purchases based on a shopper’s history.
Trending in Operations
The cuts amount to 4% of the ecommerce platform's workforce.
eBay is set to become the latest ecommerce platform to conduct layoffs.
The company announced plans on Tuesday to lay off 500 employees, which amounts to about 4% of its workforce. Layoffs were set to take place over the next 24 hours, the company said Tuesday evening.
In an SEC filing, CEO Jamie Iannone said the decision to make layoffs came after consideration of the macroeconomic environment and where the company could best invest for the long-term.
Iannone said the moves “are designed to strengthen our ability to deliver better end-to-end experiences for our customers and to support more innovation and scale across our platform.”
“Importantly, this shift gives us additional space to invest and create new roles in high-potential areas — new technologies, customer innovations and key markets — and to continue to adapt and flex with the changing macro, ecommerce and technology landscape,” Iannone wrote. “We’re also simplifying our structure to make decisions more effectively and with more speed.”
eBay is one of the oldest ecommerce platforms, and remains an active marketplace for both new and resale items. The San Francisco-based company has yet to report results for the fourth quarter of 2022. In the third quarter, the company said gross merchandise volume was down 11%, and revenue was down 5% year-over-year.
Yet the company has also continued to invest. In 2022, it acquired collectibles platform TCGPlayer and myFitment, which provides parts and accessories for automotive and powersports. It also opened a secure vault for trading cards, and launched livestreaming.
eBay is also seeing a boost from advertising, with revenue driven by promoted listings up 19% in the third quarter.
With the layoffs, eBay joins other tech companies that provide the infrastructure of ecommerce in making layoffs. Amazon, Shopify, Salesforce, BigCommerce and Wayfair have all recently announced layoffs. Technology giants like Meta, Google and Microsoft have also made job cuts.
It comes as inflation is weighing on consumers’ discretionary spending, and the return to more in-person shopping throughout 2022 led to a correction following aggressive hiring during the pandemic.