Computer vision and Artificial Intelligence(AI) have developed a lot during the past few years. As they can read and understand images better, visual search as a tool is gaining popularity, especially among online fashion retail brands and fashion marketplaces. Many retailers have already integrated visual search AI in their websites and mobile apps, reporting increased conversions and higher customer loyalty.
But, to understand the concept better, let’s start from the beginning.
What’s visual search?
Researchers from the University of Minnesota's Management Information Systems Research Center and 3M (Vogel et al., 1986) demonstrated conclusively how effective visuals may impact perception, attention, and behavior back in 1986. The research showed that viewers were able to understand information better when they were looking at visual content.
Translated into today’s e-commerce language, visual content can contribute to a better customer experience, especially when it reduces product discovery time.
Customers who locate the items they want easily are already a step closer to completing a purchase. But, what exactly is visual search? Instead of typing in keywords, users may utilize the visual search function to search for photos. They can use the Internet to download images, capture screenshots, or take photos of anything they're looking for. In exchange, customers receive a collection of photos that appear to be comparable.
Suggested read: The Essential Guide to Visual Search in Fashion Ecommerce
Combining computer vision and AI
Computer vision and machine learning techniques are combined in visual search. Although computer vision has been known for a long time, it wasn't until AI-based machine learning algorithms that it was able to comprehend visual context. Computer vision allows computers to not only see, but also to define what they perceive before determining what to do with the information.
Machine learning essentially provides the information that computer vision requires in order to understand what is presented in a photograph. AI engines can recognize an image's context and, as a result, discover photos with the most comparable context. When compared to keyword searches, online retailers can give more trustworthy results to their website visitors.
As it brings positive results, predictions say that the use of the technology will grow. In fact, by 2023, the rapid adoption of visual search AI will have increased its market value to $14,727 million, with a CAGR of 9%. This isn’t something we didn’t expect. Smartphones have made taking photos very easy for everyone. Not only do they keep track of places they visit, but they also keep track of objects they don't want to forget. These images become actionable thanks to visual search AI. A photo of your shopping list becomes a purchase from your favorite online store. A photo of your friend's new coat becomes the best coat you ever bought.
Visual search opens up plenty of new possibilities. Visual search will keep improving as AI technology advances. Furthermore, because AI is designed to learn continuously, the more people use visual searches and the more photos the AI is exposed to, the quicker it will be able to recognize objects and provide valuable information to the user.
Suggested read: How Visual AI Can Improve E-commerce
The benefits of fashion visual search
Product discovery made faster
You can reduce purchase mistakes by condensing the processes between getting the idea and discovering the product. Visual search driven by artificial intelligence removes the barrier between seeing and buying, resulting in a more seamless customer experience.
Users can utilize visual search to find the products they're looking for quite fast. They may literally take a picture of what they've found and it will be located immediately.
Take more visitors to convert
Even with perfect filtering, text-based search may be a time-consuming and exhausting task. The consumer may give up some time along the way because it might seem like too much work. Visual search eliminates the need to type a keyword, scroll through the results, try another term, and then another until they discover what they're looking for.
Without any typing, it provides exactly what your website visitor looks for in just a few seconds. As a result, site abandonment rates are lower, implying that your visitors become paying customers much faster than it takes to discover a product regularly.
Enhance your SEO efforts
The significance of SEO has grown as visual search has grown in popularity. This is due to the fact that picture search results are highly competitive. Metadata and schema markup are essential for SEO in this circumstance, since search engines may extract data from them. Online retail stores must improve if they wish to outperform their competitors. They will get greater results this way than they would with a strictly text-oriented SEO approach.
Fewer distractions during the customer journey
The cluttered volume of useless items that customers must filter through in order to discover a single product that they wish to purchase is one of the most complained-about e-commerce aspects. Customers want alternatives that are suited to their specific requirements. When they are overwhelmed with alternatives that do not fit their needs, on the other hand, the effect may be disastrous for a retail firm.
A consumer who can't identify the correct items amid the clutter will not only quit your online store to buy at a competitor's, but they will also be less inclined to return to an unpleasant purchasing experience in the future. Visual search helps your consumers to undertake a focused and product discovery that has a substantially better chance of ending in a purchase by filtering out the unnecessary information.
More useful analytics
In contrast to the difficulties of tying text-based searches to purchases, if a shopper does a visual search and then purchases the items, the transaction may easily be traced back to the visual search. A store can track when customers click on visual search results, which styles they choose, and, most crucially, when did they choose to buy the products.
This means you can pinpoint the specific items and product categories that regularly attract attention and convert, allowing you to focus your efforts where they are most effective.
Improved customer lifetime value (CLV)
Allowing your consumers to use visual search to locate items is simply listening to their problems and giving them the most straightforward way to find the items they want from your shop on their own terms. Consumer happiness skyrockets when you assist rather than impose the steps of a purchasing journey, which means your customers will always come back to you for more.
Conclusion
Over the last few years, visual search has advanced at a breakneck pace. Your online photos may be transformed into strong, actionable information by a qualified professional. People have been found to respond to images by taking action, improving understanding, and increasing satisfaction.
The AI approach to image processing may help you offer the correct pictures to your consumers, boosting their satisfaction, increasing your income, and shortening your time to market.
The visual search engine by Pixyle.ai will assist you in creating a smooth conversion path and a more personalized consumer experience. Make it simple for customers to locate your items, increasing consumer engagement. Most importantly, maintain user satisfaction and make visitors come back.
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