February 14, 2020
You scroll down your Instagram profile. Suddenly, a long red dress catches your eyes. You stop breathing. Your eyes pop up. This is it - you say to yourself. This is the most marvelous red dress you have ever seen. Seconds after, you feel a bit of disappointment because you have no clue where you can possibly buy this amazing piece of clothing. Your search ends here and you continue to scroll further, trying to forget about the pleasant visual experience you had seconds ago.
Time to give up on your dream dress or is there another option?
Let’s get back to your red outfit. Wouldn't be amazing if the moment you saw that gorgeous dress, you could discover additional information about it in a matter of seconds?
You will find out as you continue reading...
Let’s check out what the statistics say. Do you know that 90% of all the information transmitted to our brains is visual? How about our ability to process information 60.000 times faster than a piece of text-based information? This means that as human beings, we are programmed to register things visually.
Thus, it should not come as a surprise that the way we search for stuff online is changing. We use our eyes to see the things that surround us, so why not take advantage of this human ability? You know what they say - a picture is worth 1.000 words. This statement is completely applicable to the fashion industry.
We can now witness how Artificial Intelligence (AI) technologies can add value in every aspect of the fashion industry, starting from the designing process, manufacturing to sales and marketing of finished goods. Here comes into the spotlight the power of computer vision that makes us believe that the future of fashion is intelligent for sure.
What is visual search all about, and how can brands use this to their advantage? To understand this, let’s dive deeper into some of the main reasons that confirm the power of AI technologies.
Instead of text as a query, when searching visually, you use a photo. This allows you as a user to locate a related or almost identical product to the photo you have submitted. Machine learning (ML) is the engine behind it. ML analyses related characteristics within the photo you have uploaded and the photo archive available. It provides equivalent results based on an image search conducted pixel by pixel.
Furthermore, the results can also be found constructed by the metadata and keywords that go along with the image. The result is a more accurate and efficient visual search that provides you with highly related image results of that red dress you can’t take your eyes off.
Not only that you as a consumer will benefit from visual search, but this technology is also valuable for e-commerce managers. For example, let’s say that your potential consumer wants to find out some similar searches to the red dress they liked so much. Still, they are not familiar with the name of the retail store. As a result, they can’t Google the store.
This is the part where the power of visual search comes in your favor, lending a hand with the ‘discovery problem’. By cutting down endlessly scrolling through items and narrowing down the results, the user experience is instantly improved.
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At the discovery stage of products, less is more. Shopping cart abandonment is still a real issue and liking products is not a guarantee that the customer will eventually buy them. Using the power of computer vision, users don’t need to waste time browsing through as many products available before choosing.
Instead, they can search beyond the basic attributes. Search parameters are narrowed down to make the likelihood of discovering a product that closely matches the preferences of the consumer much higher. An AI interface skims throughout the entire catalog to come up with a list of products that are similar to the first image, or the attributes, specified by the customer. Simple as that.
Additionally, visual search presents e-commerce stores with the opportunity to cross-sell. This means that next to the image being suggested to the user, it will be shown other items (similar recommendations) to the first one. Blame it on human nature, but we can assure you that this might tempt consumers to consider those items and eventually buy some of them. At least, it will increase their overall spend on the site.
Major players in the fashion industry like H&M, ASOS, Forever 21, Zara and many more, have made great strides using AI to grow their business, there is still a lot to do. As the technology continues to move forward, experts state that the popularity of visual search will advance, improving along with it the accuracy of the search results.
So, the more people will conduct their searches visually, the more ML will become superior in identifying similarities in images and providing users with better results.
The progress of visual search will not be a threat to text-based searches. It won’t replace searching by keywords. Instead, both visual and text searches will work as a tandem to effectively provide the best results related to an image.
As we mentioned in the beginning, it has never been easier for consumers to find what you are looking for, especially when it comes down to clothes and fashion accessories.
At Pixyle, we are confident that online shopping should not only be about consumers finding the products they are looking for. Instead, we want to ensure that they find the right product for them. This is why we developed a powerful image recognition software that allows fashion retailers to deliver unforgettable customer experience online. Visual search, similar recommendations, and automatic product tagging are some of the AI solutions we offer.
If you want to know how you can adopt computer vision and help shoppers navigate your e-commerce site in a much more intuitive way, using the power of an image, instead of a text format, our solution is the perfect match for you. We encourage you to drop us a note on firstname.lastname@example.org. We are always happy to connect with you and take your business to the next level.