How to Find Merchandise in Photo?

Are you having difficulty finding an article of clothing, but can’t? Luckily there are apps out there to help!

Google Lens is an innovative visual search tool designed to identify clothing and accessories. Simply take a photo, and the app will give you links for similar items available for purchase.

Google Lens

Google Lens is an image recognition search technology for mobile devices. It can be used to translate text, identify landmarks and locate related products online. Google Lens can be found integrated directly into some smartphone cameras as an app download; its utility spans many uses but is especially beneficial to retailers looking to increase online sales.

Google Lens makes it easy to locate furniture featured in an Instagram post or TikTok post that strikes your fancy – or find similar pieces saved on your phone – wherever they may be found at various retailers and price points. Simply open up the Google app, tap on its lens icon, select your photo of furniture you wish to search for and drag a box around it if necessary to narrow results to that specific item.

Lens is a revolutionary technology with great potential to revolutionize how people shop online. It helps shoppers navigate complex online stores more easily and find what they’re after more quickly; and makes e-commerce sites more appealing to customers and increases sales capacity.

Google Lens can be found through both the Google App and Camera on Android phones, as well as through Google Photos on iPhones. To maximize its potential, make sure your website and apps are SEO-friendly while making sure images load quickly with high quality pictures. Also consider Google Catalogs or Verified Merchant Program to reach more shoppers.

Lykdat

Fashion businesses must create an intuitive search experience. While traditional online searches rely on text input, Lykdat’s visual AI technology utilizes image recognition to understand what customers are searching for and match inventory with customer demand, driving sales and engagement. Furthermore, Lykdat’s “Shop the Look” feature encourages shoppers to discover complementary items when an item becomes unavailable – particularly beneficial when an item goes out of stock.

Lykdat allows users to easily search clothing via photo uploads. Once uploaded, crop the photos so they focus on one piece and hit “Search.” Lykdat then analyzes your image and displays similar items from various e-commerce stores online sorted by price with additional customization filters such as gender, location and color for ease of use.

App is free to download on iOS and Android devices, easy to use, and features one of the best algorithms for finding clothes in images. Furthermore, it can detect multiple pieces at the same time in one photo and will provide separate results for each one.

Integrating Lykdat’s image search functionality into your website is simple, as its JavaScript SDK makes integration quick and painless. Once logged into Lykdat, two API keys will be provided: one publishable key for API endpoint access and one admin key that allows control over permissions. Additionally, there’s also a sample search UI included with the SDK so you can customize it to match your own site’s look & feel.

ASOS

ASOS makes it easier than ever for you to emulate looks you see on the red carpet or in magazines by offering an online visual search tool called “Style Match,” allowing users to take photos or upload any item, from shoes and clothing to accessories, then search their products for similar pieces.

This feature works by clicking on a camera icon in the ASOS app’s search bar, taking a photo, then uploading or snapping or sharing that picture for ASOS’ 85,000 product lines to find visually similar items that might meet your criteria. Once found, a list will be provided of both those currently in stock as well as ones available for preordering.

ASOS knows its audience of 20-something shoppers are likely to own smartphones, making this tool an intelligent move for reaching them and providing access to flash sales and promotions through their apps. Plus, the app also features curated shopping edits as well as back-in-stock notifications!

This company has invested heavily in technology to enhance their mobile app and website, using machine learning and data science to develop features that learn customer preferences over time and suggest items they might enjoy. As a result, sales on its mobile platform have seen an exponential increase – 70 % of UK sales come through its app alone! With 900 employees currently and 200 more planned to join next year, its app also hosts an independent boutique marketplace where these items may be sold directly.

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