Online sellers are no stranger to visual commerce – the act of leveraging imagery and videos to create better engagement with customers and gain more sales. As eCommerce becomes increasingly more visual, technologies and selling strategies are also evolving.
This includes the use of artificial intelligence, and more specifically, image recognition. From helping shoppers find products in a snap, to making it easier for companies to organize and list their products, image recognition technology is being used in many creative ways within eCommerce.
Image Recognition for the Shopper:
1. Image Recognition for Visual Search
Visual search has seen a boom in recent years, especially with Google’s Search by
By uploading or linking to an image via Google’s image search, the search engine brings up results relating to that image. Therefore, a photo of a product can bring up links to similar styles.
Pinterest’s tool works in a similar way, allowing users to click on an icon on any image they stumble across on the platform, which then brings up pins of similar-looking images in an image recognition library.
Neither of these image recognition tools are eCommerce or product-specific, but can be used by shoppers aiming to identify a product they can’t quite define, or find similar versions of a product they’re interested in, simplifying the shopping experience – all powered by image recognition software.
2. Next-Level Visual Search and Visual Commerce
A similar image recognition tool that takes visual search to the next level, and does relate directly to eCommerce, is Amazon’s StyleSnap, available on the Amazon app and focused on the fashion category. Users can take a photo or upload a screenshot of an outfit they like, and then browse through related product listings.
The image recognition app can pin-point products in a lifestyle image, presenting the shopper with links to matching or related products available for purchase on Amazon.
This image recognition tool makes shopping easier for customers, and also presents a massive opportunity for online sellers. Amazon sellers who have invested in optimized product images and SEO-driven product content will have a leg up on the items that appear when a similar product is StyleSnapped.
Image Recognition for the Seller:
3. Product Attribute Tagging
Speaking of sellers, there are many exciting image recognition applications that have emerged within the eCommerce industry. One such use comes in the form of product attribute tagging. It can be a challenge for retailers, manufacturers and brands to standardize their attribution process, or to manually create attributes for thousands of SKUs in a catalogue.
With a trained image recognition algorithm, a seller can upload a catalogue of product images, each of which would then be tagged with appropriate attributes and specifications. This type of algorithm exists in many forms available to sellers, and is something ginnie is in the midst of researching for our own customers – stay tuned!
4. Content Creation through Image Recognition
Taking product attribute tagging one step further, image recognition serves a great purpose in the creation of content based on those attributes and specifications. One major update the ginnie team is currently working on is the ability for a customer to upload an image of a product, have the image be tagged with attributes, and then have ginnie’s natural language generation capabilities develop a unique product description based on the attributes that were automatically defined.
This greatly simplifies attribution and content creation for online sellers, leading to less time spent working on your products and more time spent selling them.