With technology innovations emerging from across the industry, the market’s biggest players can’t rest on their laurels. In its latest product launch, Google Cloud has announced new capabilities in visual search and product recommendation, in order to help its users stay competitive in e-commerce.
One of Google’s most well-known products is the Google Search tool and the company has leveraged this experience in its latest rollout. Machine learning (ML) technology takes existing data and analyses it for patterns and trends; these are then used to recommend behaviors and strategies. Due to the vast amount of data available to Google through its search tool, the machine learning solution is given a significant advantage.
Retailers can utilize Google’s latest ML architectures through the launch of Recommendations AI. This product integrates directly into the merchant’s existing e-commerce platform and has no impact on the user interface; visitors to the platform can expect the same customer journey they know and love.
However, the quality of any recommended items will be improved, due to the use of Google’s algorithm. By taking into account the customer’s previous shopper history with the retailer, as well as their current browsing behavior, the Recommendations AI tool is able to generate tailored product suggestions. It also takes into account any changes in inventory and pricing, to ensure a frictionless experience.
“As the shift to online continues, smarter and more personalized shopping experiences will be even more critical for retailers to rise above their competition,” said Carrie Tharp, VP of retail and consumer at Google Cloud. “Retailers are in dire need of agile operating models powered by cloud infrastructure and technologies like artificial intelligence and machine learning to meet today’s industry demands.”
Google Cloud also released its new Vision API Product Search tool, for general availability. As social commerce and mobile retail have grown in popularity, consumers are growing accustomed to a visual-first shopping experience. Younger generations in particular are increasingly likely to begin their customer journey on a social network.
With the Vision Search functionality, consumers can use an image to generate search results, instead of traditional word searches. Images can be from social media, the web, or photos taken of real-life items. ML-powered recognition programs will then detect the products within the retailer’s catalog that are most similar to the searched image, in terms of color and style. These results can also display complementary items, in order to promote add-on purchases.
Lastly, Google Cloud announced its new Search for Retail capability, available in Private Preview. Drawing on its knowledge of consumer behavior, this improved search uses predictive insights into customer intent and search context to help support search results. Users can improve the accuracy of their internal search, by better understanding what their customers are looking for.