6 Benefits of Visual Recognition in Fashion eCommerce

Over the last decade, visual content started to replace text and managed to become the main type of content on the Internet. In the fashion and retail industry, this leads to a cut-throat and stiff competition, that is pushing retailers to find new ways of adapting to these new search trends, while better monetizing their efforts and converting browsers into buyers.

Visual recognition provides a solution to this, based on algorithms that analyze images and help optimize tasks such as identifying, tagging and classifying every apparel, thus making customers experience and retailers job much easier.

Visual recognition has gained ground and has many advantages to offer to fashion online retailers.

 

1. Clothes from magazines & print ads become shoppable

fashion-magazine

Image recognition solutions allow customers to scan a picture taken from a fashion magazine or a print ad and instantly land to the product page where they can buy that exact item.

Customers can finally forget about scanning QR codes, looking up links manually, or tediously searching for specific brand names or describing clothing items in the store or search engine.

 

2. A way to expand information on the item

fashion-clothes

Any printed content can be linked not only to purchase pages where the customer can buy the item, but also to other kinds of digital content, such as videos where the apparel is showcased on a model. This can help customers get a better feel of the item, and may convince those who are hesitating.

Printed images can also be associated with special offers & discounts, as well as detailed product descriptions for information-hungry consumers.

 

3. Improving the search experience (and its efficiency!)

online-fashion-shopping

Every day, fashion retailers are increasingly integrating visual search features besides traditional methods such as text search.

Online shoppers can upload an image to the site, or take a picture in an app, to look for similar products in the Retailer’s catalog in a blink of an eye.

This paves the way for much better product discovery experience, as shoppers don’t need to wander through endless sub-categories to find that leopard print furry coat – especially that in many cases they may not even know how it’s called what they are looking for.

 

4. Find less expensive, similar pieces of clothing

find-similar-fashion

At some point in our lives, we all have fallen in love with an item, but found it too expensive to buy. With visual search solutions running in the app or website, Retailers can suggest similar-looking items in different price ranges, so the customer can buy a look-alike product at a lower price.

This feature can become a staple in e-commerce sites, as it can be used to offer relevant recommendations, based on items the shopper looked at but didn’t buy.

Of course, Retailers can also use such solutions to upsell to the customer, showing higher value alternatives that look alike.

 

5. Get the whole outfit in matching colors

fashion-colors

Colors can define seasons and trends in Fashion, and still, until recently, filtering by color in fashion retail websites was a rather disappointing experience, or limited to the very basics.

With cutting-edge visual recognition technology, retailers are able to group and filter items by a broader palette of color shades and use these in search and recommendations in an automated way.

For example, if we acquire a new pair of shoes in a specific shade of brown, we might want to find a color-matching bag. Color-matching accessory recommendations when looking at a specific piece of clothing will contribute to increasing the basket size and help grow sales.

 

6. Automated tagging or categorizing

ai

Apparel stakeholders can use visual similarity solutions to automatically assign tags or categories to the product images they upload to their content management system.

Moreover, the machine can be trained, so new tags and categories can also be defined. This can be really useful with the arrival of new seasonal trends, such as Bardot neckline or culotte pants. Visual recognition helps pre-categorize all the clothing items, saving the time and money of doing it all manually, and avoiding human errors.

 

Catchoom’s Solutions for Fashion eCommerce

Catchoom’s solutions have been designed to improve catalog managementboost conversion rates and improve customer experience. We use Artificial Intelligence and Machine Learning technology that has been trained to cope with the specific requirements of the fashion market.

Want to know more? Feel free to schedule a demo with our team and discover how to improve your fashion eCommerce operations and increase sales.