Google Cloud introduces new AI tools for retailers

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NEW YORK, Jan. 13, 2023—Ahead of NRF 2023, the retail industry’s largest event, Google Cloud today introduced four new and updated AI technologies to help retailers transform their in-store shelf control processes and enhance their e-commerce sites with more seamless and natural online shopping experiences for customers.

A new AI shelf control solution, powered by Google Cloud’s Vertex AI Vision, uses Google’s database of data on people, places and things, giving retailers the ability to recognize billions of products to ensure in-store shelves are the right size and well stocked. Additionally, in an update to its Discovery AI solutions, Google Cloud has introduced a new AI personalization feature and a new AI-powered navigation feature to help retailers update their digital storefronts with more dynamic and intuitive shopping experiences. Finally, Google Cloud’s RecommendationsAI solution rolled out new machine learning capabilities that enable retailers to dynamically optimize product ordering and recommendation panels on their e-commerce pages and provide personalized recommendations for repeat purchases.

“The upheavals of recent 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, Google Cloud. “Despite the uncertainty, the retail sector has huge opportunities. Tomorrow’s leaders will be those who tackle today’s most pressing challenges in-store and online with the latest technology tools, such as artificial intelligence and machine learning.”

New shelf control AI helps retailers improve product availability

The issue of low or no inventory on store shelves is a concern for retailers. According to a NielsenIQ analysis of shelf availability, empty shelves are costing US retailers $82 billion in lost sales in 2021 alone. Although retailers have tried different shelf control technologies for years, their effectiveness has often been limited by the resources needed to build reliable AI models to detect and differentiate products, from different flavors of jam and jelly, to dozens of types of toothbrushes.

Now in global preview, Google Cloud’s new AI-powered shelf control solution can help retailers improve shelf availability, provide better visibility into what their shelves actually look like, and help them figure out where supplies are needed. Based on Google Cloud’s Vertex AI Vision and powered by two machine learning models, a product recognition and a tag recognition, the shelf control artificial intelligence allows retailers to solve a very difficult problem: how to identify products of all kinds, at scale, relying solely on the visual and textual characteristics of a product, and then translating that data into actionable information.

Resellers don’t have to spend the time, effort, and investment collecting data and training their AI models. Leveraging Google’s database of billions of unique entities, Google Cloud’s shelf inspection AI can identify products from a variety of image types taken from different angles and viewpoints, a particularly difficult task. Retailers will have a high degree of flexibility in the types of images they can provide to the AI ​​that monitors the shelves. For example, a retailer might use images from a ceiling-mounted camera, a co-worker’s cell phone, or a robot roaming the store checking shelves.

Now in preview, this technology is expected to be generally available to resellers globally in the coming months. Importantly, a retailer’s images and data remain proprietary and AI may only be used for product identification and price tags.

Artificial intelligence transforms the shopping experience into a digital showcase

People don’t always know what they want. That’s why they window shop or browse websites, looking for inspiration.

To help retailers make the online browsing and product discovery experience more modern, faster, more intuitive and more satisfying for shoppers, Google Cloud today introduced a new AI-powered browsing feature in its Discovery AI solutions for the resellers. The feature uses machine learning to select the optimal ordering of products on a retailer’s e-commerce site once shoppers choose a category, such as “women’s jackets” or “kitchenware.”

Over time, AI learns the ideal product order for each page on an e-commerce site using historical data, optimizing how and which products are displayed for accuracy, relevance, and likelihood of making a sale. The feature can be used on a variety of ecommerce site pages, from navigation, brand and landing pages, to navigation and collection pages.

Historically, e-commerce sites sorted product results based on category bestseller lists or human-written rules, like manually determining which clothing to highlight based on seasonality. This navigation technology takes a completely new approach, is self-healing, learns from experience and requires no manual intervention. In addition to generating significant improvements in revenue per visit, it can also save retailers the time and cost of manually curating multiple ecommerce pages. The new tool is now generally available to resellers worldwide and supports 72 languages.

More personalized search and browsing results with machine learning

Research commissioned by Google Cloud found that 75% of shoppers prefer brands that personalize interactions and appeal to them, and 86% want a brand that understands their interests and preferences.

To help retailers create more seamless and intuitive online shopping experiences, Google Cloud today introduced a new AI-powered personalization feature that personalizes the results a customer gets when they search and navigate a retailer’s website. The technology enhances the capabilities of Google Cloud’s new browsing offering and existing retail search solution.

The AI ​​behind the new personalization capability is a product pattern recognition that uses a customer’s behavior on an e-commerce site, such as clicks, cart, purchases and other information, to determine tastes and buyer preferences. The AI ​​then moves products that match those preferences into search and browses the rankings for a personalized result. A shopper’s personalized search and browsing results are based solely on their interactions with that specific retailer’s e-commerce site and are not linked to their Google Account activity. The buyer is identified through an account he has created with the retailer’s site or through a first-party cookie on the website.

As with all Google Cloud solutions, customers own and control their data, information about customer preferences remains with the reseller. This technology is now generally available to resellers worldwide.

AI boosts retailer profits with better recommendations

Product recommendation systems are now a critical component of any retailer’s ecommerce strategy for good reason: Online retail sales are predicted to reach more than $8 trillion by 2026. However, retailers have had to long struggled to determine which panels to display on their websites, how to organize them effectively, and how to coordinate relevant and personalized content. Google Cloud’s Recommendations AI solution uses machine learning to help retailers offer product recommendations to their shoppers.

New updates to Recommendations AI, announced today, can make a retailer’s ecommerce properties even more personalized, dynamic and useful for individual customers. For example, a new page-level optimization feature now allows an ecommerce site to dynamically decide which product recommendation panels to uniquely show to a shopper. Page-level optimization also minimizes the need for resource-intensive user experience testing and can improve user engagement and conversion rates.

Additionally, a recently added revenue optimization feature uses machine learning to deliver better product recommendations that can increase revenue per user session on any e-commerce site. A machine learning model, built in collaboration with DeepMind, combines an e-commerce site’s product categories, item prices, clicks, and customer conversions to strike the right balance of long-term satisfaction for shoppers and increased revenue for resellers. Finally, a new repurchase model leverages a customer’s purchase history to provide personalized recommendations for potential repeat purchases.

Compared to the basic recommendation systems used by Google Cloud customers, Recommendations AI has shown double-digit increases in conversion and click-through rates in vetted experiments from retailers using the technology. The new Page Level Optimization, Revenue Optimization, and Buyback templates are now available globally for resellers.

Availability of technology and Google Cloud at NRF

Google Cloud’s AI Shelf Control tool is now in global preview. New e-commerce technologies, including AI personalization capability, navigation feature, and updates to Recommendations AI (machine learning model for page-level optimization, revenue optimization model, and buyback model) are now available globally for resellers. NRF event attendees can learn more about the latest AI-powered innovations for retailers at event booth #1. 5607 by Google.

About Google Cloud

Google Cloud accelerates every organization’s ability to digitally transform their business. We deliver enterprise-grade solutions leveraging cutting-edge technology from Google, all on the cleanest cloud in the industry. Customers in more than 200 countries and territories turn to Google Cloud as a trusted partner to enable growth and solve their most critical business problems.

Source: Google Cloud

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