Has Google Raised the Search Bar on Online Personalization?

Google is piloting new product discovery elements designed to give users a more personalized shopping experience, including enabling ratings on products.

Among the new personalized shopping tools highlighted in a blog entry from Sean Scott, Google’s VP/GM of consumer shopping:

• Style recommendations: When searching for certain apparel, shoes, or accessories, such as “men’s polo shirts,” U.S. shoppers signed in via mobile browsers and the Google app will see a section labeled “style recommendations.” Similar to rating systems on Netflix or Tinder, they can rate merchandise options with a thumbs up or thumbs down, or a swipe right or left, to gain personalized results. Preferences are remembered. Scott wrote in the blog entry, “So when you’re looking for, say, men’s polo shirts again, you’ll see personalized style recommendations based on what you liked in the past and products you interacted with.”
• Brand preferences: U.S. shoppers searching for apparel, shoes, or accessories on mobile browsers, desktops, or the Google app can specify which brands they’d like in their searches. Once chosen, options from these brands appear instantly. Preferences around the brand can be further fine-tuned.
• Generative AI for product search: Google’s AI image generation tool for shopping is now available to all U.S. users who have opted into Search Generative Experience (SGE) within Search Labs. If searching for a specific item, like a “colorful quilted spring jacket,” users tap “Generate images” after their search to see photorealistic options matching their preferences. Since users’ search descriptions often vary, image-driven searches can help you “shop for apparel styles similar to whatever you had in mind.” Scott wrote, “For instance, someone might call something boxy, while another might call it oversized.”
• Virtual try-on: Google’s virtual try-on (VTO) tool, accessible in the U.S. on desktop, mobile, and the Google app, lets users see what an item, say a top, looks like on a diverse set of real models ranging in size from XXS to 4XL, including how the item would drape, fold, or form wrinkles and shadows.

Generative AI’s arrival has led to many experiments in online search capabilities, including Walmart’s introduction of its first generative AI shopping assistant in partnership with Microsoft in January. Amazon’s first AI-powered shopping assistant, called Rufus, was released in beta in February.

A survey of 462 U.S. consumers from Constructor last year showed product search on retail websites scoring low grades with consumers. Among the findings: 

• 60% think the online search function on retail websites needs an upgrade.
• 30% said it takes at least three minutes to locate the item they need when using the search function on retail websites, while only 28% called their product search experiences “quick.”
• When consumers shop with their favorite retailer, 34% said the site treats them like a total stranger each time they visit, presenting items that don’t reflect their preferences or prior purchases.
• Topping the wish list of what consumers want out of product search was results that more closely reflect what they’re looking for, cited by 46%. This was followed by better filtering of search results, 41%; more personalized results, 34%; autocomplete, to accurately finish their queries, 30%; more integrated online and in-store functionalities, 29%; and the ability to type full sentences into the search bar and have it understand, 23%.