Google has rolled out a new feature called Style Recommendations to help fashion shoppers find what they like faster. The tool uses visual search and machine learning to suggest clothing and accessories based on user preferences and browsing history. It appears in Google Search and the Google app when people look for fashion-related terms.
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This update aims to make online shopping easier for users and more effective for retailers. By showing personalized style ideas, Google hopes to connect customers with products they are more likely to buy. Early tests show users spend more time exploring options and click through to retailer sites more often.
Fashion e-commerce brands stand to benefit from this change. Products that match Google’s style signals may get more visibility in search results. Retailers are encouraged to use high-quality images, accurate product descriptions, and structured data so their items can be understood by Google’s systems.
The move reflects a broader shift in how people shop online. Many now start their journey with a general idea rather than a specific product name. They rely on visuals and suggestions to guide their choices. Google’s new feature meets this behavior head-on by blending search with discovery.
Retailers who adapt quickly could see better engagement and sales. Those who ignore image quality or skip technical SEO steps might miss out. Google says the system learns over time, so consistent updates to product feeds matter.
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Style Recommendations is now live in the United States and will expand to other countries later this year. It works on both mobile and desktop devices. No extra setup is needed for users. The feature activates automatically during relevant searches.