Amazon is making product recommendations that shoppers are sure to ‘like’
Amazon is banking on social media icons and machine learning to improve its browsing process.
Taking a page from Facebook and Instagram, Amazon has added a new tool, called Scout - Style Explorer, that makes product recommendations based on user input. The online giant is using a mix of merchandise images, coupled with thumbs up and thumbs down icons, and machine learning to deliver streamlined product assortments that are purely based on customer preferences.
With every thumbs up or thumbs down post a shopper makes, Amazon’s machine learning algorithms get smarter at detecting customer preferences. Based on these responses, Amazon delivers the user-personalized merchandise recommendations across featured product categories.
Amazon’s Scout web page currently highlights merchandise across furniture, home decor, lighting, kitchen and dining, patio, bedding and women’s shoes. The online giant will also be adding new categories, such as toys, handbags and apparel, according to images on displayed on the website.
While Amazon is quietly launching the service, customers can access the tool through a link found on the pages of eligible categories. On top of each category page, a “Scout - Style Explorer” icon sits between "Shop by Room" and "Shop by Style.” (Women’s shoes preferences can only be accessed through the Scout page.)
The tool is a way to streamline how customers browse merchandise, and refine selections. "Amazon uses imagery from across its robust selection to extract thousands of visual attributes for showing customers a variety of items so they can select their preferences as they go,” an Amazon spokesperson told CNBC in an email.
The service also highlights Amazon’s commitment to improve and personalize a cumbersome browsing process.
"Amazon has desperately needed information on customer likes and dislikes. Everyone who’s shopped Amazon will tell you how easy and frictionless they’ve made it to buy something, but the product recommendations have always been terrible,” said Jennifer Sherman, SVP of Product & Strategy, Kibo.“Amazon is banking on our social-media-obsessed culture to feed them the consumer preference data they need – perhaps even hoping to gamify the experience.”
Taking a page from Facebook and Instagram, Amazon has added a new tool, called Scout - Style Explorer, that makes product recommendations based on user input. The online giant is using a mix of merchandise images, coupled with thumbs up and thumbs down icons, and machine learning to deliver streamlined product assortments that are purely based on customer preferences.
With every thumbs up or thumbs down post a shopper makes, Amazon’s machine learning algorithms get smarter at detecting customer preferences. Based on these responses, Amazon delivers the user-personalized merchandise recommendations across featured product categories.
Amazon’s Scout web page currently highlights merchandise across furniture, home decor, lighting, kitchen and dining, patio, bedding and women’s shoes. The online giant will also be adding new categories, such as toys, handbags and apparel, according to images on displayed on the website.
While Amazon is quietly launching the service, customers can access the tool through a link found on the pages of eligible categories. On top of each category page, a “Scout - Style Explorer” icon sits between "Shop by Room" and "Shop by Style.” (Women’s shoes preferences can only be accessed through the Scout page.)
The tool is a way to streamline how customers browse merchandise, and refine selections. "Amazon uses imagery from across its robust selection to extract thousands of visual attributes for showing customers a variety of items so they can select their preferences as they go,” an Amazon spokesperson told CNBC in an email.
The service also highlights Amazon’s commitment to improve and personalize a cumbersome browsing process.
"Amazon has desperately needed information on customer likes and dislikes. Everyone who’s shopped Amazon will tell you how easy and frictionless they’ve made it to buy something, but the product recommendations have always been terrible,” said Jennifer Sherman, SVP of Product & Strategy, Kibo.“Amazon is banking on our social-media-obsessed culture to feed them the consumer preference data they need – perhaps even hoping to gamify the experience.”