With technological innovations from across the industry, the largest market players cannot rest on their laurels. At the latest product launch, Google Cloud announced new features for visual search and product recommendation to help its users stay competitive in e-commerce.
One of Google’s most popular products is the Google search tool. The company used this experience in its latest launch. Machine learning (ML) technology takes existing data and analyzes it for patterns and trends. These are then used to recommend behaviors and strategies. The machine learning solution has a significant advantage due to the large amount of data that Google has available through the search tool.
Retailers can take advantage of Google’s latest ML architectures through the introduction of Recommendations AI. This product integrates directly into the retailer’s existing e-commerce platform and has no user interface impact. Visitors to the platform can expect the same customer journey they know and love.
However, using the Google algorithm improves the quality of the recommended articles. By taking into account the customer’s previous customer history with the retailer as well as his current surfing behavior, the AI tool « Recommendations » can generate tailor-made product suggestions. It also takes into account changes in inventory and pricing to ensure a smooth experience.
« As the shift to online continues, smarter and more personal shopping experiences are becoming even more important for retailers to differentiate themselves from the competition, » said Carrie Tharp, Vice President Retail and Consumers for Google Cloud. « Retailers desperately need agile operating models based on cloud infrastructures and technologies such as artificial intelligence and machine learning to meet today’s industry needs. » Google Cloud also has the new Vision API product search tool for the general public Availability published. As social commerce and mobile retail grow in popularity, consumers are getting used to a visual shopping experience. Younger generations in particular are increasingly starting their customer journey in a social network.
With the Vision Search function, consumers can use an image to generate search results instead of the conventional word search. Images can come from social media, the internet, or photos of real objects. ML-based recognition programs then identify the products in the retailer’s catalog that most closely resemble the image in color and style. These results can also show complementary elements to encourage additional purchases.
Most recently, Google Cloud announced its new « Find Retail » feature available in Private Preview. This enhanced search draws on knowledge of consumer behavior and uses predictive insights into customer intent and search context to aid search results. Users can improve the accuracy of their internal search by better understanding what their customers are looking for.
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