0 votes
by (2.1k points)

When you buy through our links, Insider may earn an affiliate commission. Have you ever seen an outfit on Instagram that you loved and wanted to recreate yourself, but didn't know where to start? StyleSnap is a new feature on Amazon made to help shoppers with this exact problem. StyleSnap uses AI to help you find looks you love. All you have to do is upload a photo onto the app and StyleSnap will analyze it to give you similar styles to shop. I tried the service and thought it was a cool way to shop and get fashion inspiration, though I felt limited by only having access to Amazon's clothing selection. Amazon Prime Day is coming soon. You can check out all of our Prime Day 2020 coverage here. Social media is one of my favorite places to find fashion inspiration. Yet, it's all too often I find an outfit I love and simply cannot figure out how to recreate it myself, no matter how hard I try searching for the exact same pieces.  A᠎rt᠎ic​le has ​been created with the ​help of G​SA Content Generator Demov᠎er sion.


If you've ever encountered this same problem, Amazon has a solution. StyleSnap is an AI-powered feature built into the Amazon app, and it's here to help you find looks you love quickly and easily. All you have to do is take a photograph or screenshot of an outfit, upload it onto the Amazon app, and you'll be presented with items that look just like the ones in the picture. Sometimes, they're even the exact same. It's truly that easy. I tried the new StyleSnap feature to see how it fared, and it probably took all of one minute. The results were speedy and the user experience was intuitive, even as a first-time user. I was surprised at just how quickly the app was able to analyze the photograph and provide similar items. Still, there are limitations. All of the suggested items are ones you can purchase on Amazon. While Amazon has a pretty robust fashion catalog these days, there are many clothing brands that it doesn't stock, which definitely limits the similar styles the app can provide.


Click the camera icon in the upper right-hand corner of the Amazon app. Once you find and click the camera icon, select the "StyleSnap" option on the left. This will lead you to the StyleSnap landing page. Once you're on the StyleSnap landing page, you can upload a photo or screenshot from the camera roll on your phone. Choose whether you'd like to upload your own photo or shop looks that are already on the app. If you don't have a photo to upload, you can peruse a selection of looks that have already been uploaded by Amazon fashion influencers. There are lots of looks already uploaded onto the app. Many of these have the exact products already linked up, as well as a variety of similar options. To test out StyleSnap, I found a picture from fashion influencer Janette Ok on Instagram. I love Janette Ok, known on Instagram as @inmyseams, for her amazing styling tips, fashion hacks, and fun outfits.


I took a screenshot of this look of hers to see if StyleSnap could help me find any similar items to recreate it myself. After I uploaded the photo, StyleSnap quickly started analyzing the image to find similar styles. This part felt high-tech, was fun to watch, and went by really quickly. Once it's done analyzing, you're presented with results of similar styles to those in the photo. The circles on the outfit are conveniently placed among the different items. When you click the circle, you'll be shown similar styles to that exact piece. I was a bit disappointed that the hat and sunglasses didn't yield any results though. Some of the similar styles were on point, while others were a stretch. The first few results were very similar to the shirt in the photo, while others like the graphic white T-shirt with a cat were a bit far off. I don't think the far-off items are necessarily a bad thing though.

Your answer

Your name to display (optional):
Privacy: Your email address will only be used for sending these notifications.
Welcome to FluencyCheck, where you can ask language questions and receive answers from other members of the community.
...