How Image Recognition Technologies Can Improve Your UX
Sep 27, 2017

IMAGE RECOGNITION TECHNOLOGIES CAN IMPROVE YOUR UX headerDesigning modern user experience without focus on visuals equals blinding your customers and driving your business into an equally blind alley. As the effective use of visual elements has become intertwined with UX, image recognition technologies had to follow suit and offer top notch tools to engage customers in the most efficient and intuitive manner. This is best seen in e-retail, whose customers are no longer easily charmed by fancy textual descriptions of the retailer’s products, preferring to shop based on their visual appeal instead of fanciful promises. As visualization of the user experience has become the name of the game, you are invited to stay with us to learn how the attractive image recognition technologies can reshape the UX you aim to deliver to your customers.

Scanning for the Look

 

First of all, you need to understand that image recognition technology works in synergy with the content or products you offer. These segments build bridges between you and your audience or customers, fostering digital interaction. Modern users expect visuals to be relevant, informative, contextual and personalized. Despite saying that images are better communicators than a bulk of words, they alone are not sufficient if you want to design user experience around the aforementioned attributes. That is why image recognition tech fits like a glove with another hot new technology – artificial intelligence.

Pairing these two technologies means that retailers can now help users make better sense of what they are looking for. First of all, they no longer rely on convoluted search phrases to get them the product they actually look for. Instead, image recognition technology integrated with their apps helps them identify objects in their physical reality and automatize their search for similar or identical products online. This means that identification of items the customers desire will result in taking their UX to a new level, as they will be directly taken to a site featuring desired products or offered an appropriate hyperlink.

For example, British retailer Snap Fashion uses software which allows its customers to take a picture of a piece of clothing with their phone, followed by providing them with links to an appropriate retailer which offers exact or similar products. After taking the picture of an object they observe, the customers are left in the hands of AI which recognizes the shape, color and size of an item and offers relevant search results based on this. Advanced AI paired with image recognition in this manner prevents the customers from experiencing fatigue in relation to abundance of choice as the offered products are narrowed down in line with their original user intent.

Cleaner and Intuitive Shopping Experience

 

Considering that 39% of all visual searches are related to apparel, image recognition technology will find its place among the companies that are fervently looking for a way to “visualize” their customers’ intent in order to offer better UX. With 74 percent of customers claiming that using textual keywords is lacking when they are looking for products online, uploading AI-recognized images for the purpose of easier product search will help the shoppers transcend the limitations of text. The shoppers will be better informed about the product, without being swamped by superfluous information. This is particularly evident in retail, in which the implementation of this technology aims for making it easier for customers to both reach appropriate retailer and pinpoint what they actually look for.

At the same time, image recognition technology does not outlive its usefulness once the shoppers reach their desired destination. An essential segment of contemporary UX is its personalization, which is achieved by combining product recommendation with visual appealing grouping of related products. This is based on our visual psychology that perceives items placed together as being related. In order to avoid having your customers suffer from cognitive overload, the images grouped in this manner will have to be sorted out by AI for the purpose of making shopping experience cleaner and more intuitive.

Image-Based Personalization

 

The potential of effective pairing of image recognition and AI technologies was recognized by Syte, a company whose proprietary solution turns images into highly actionable shopping offers. Combining the intelligence-based recognition of the customer’s intention with smart visuals, this solution promises to deliver a lot to forward-thinking retailers looking to reap the benefits of the latest tech.

Fashion retailer intu.co.uk uses Syte’s platform to provide its customers with an opportunity to look for items similar to the one they are currently looking at. Since this technology is based on deep learning and artificial intelligence, shoppers can simply hover over an image of an item and be presented with items similar in color, design, fabric or pricing. All of these suggestions are generated by AI which recognizes pieces of clothing based on set parameters in order to deliver hugely improved user experience of online apparel shopping.

This is how it works:

smart product recommendationsSyte’s technology recognizes both the images and customer’s preferences, with the AI visualizing user intent in form of smart product recommendations [Credit: Screenshot]

As it can be seen here, the model in question is wearing a black crushed velvet harness midi dress. The AI recognized the piece of clothing that was on display, making it possible for the visitors to hover over the image and be presented with attractive suggestions based on similar items (“show similar”).

In addition, this technology prevents annoyances that visitors are sometimes faced with while looking for particular products, such as items being out of stock or deficient with particular sizes. With the help of the Syte’s visual search engine, consumers are instantly offered the best alternatives to the currently missing items, which guarantees higher conversion rates and sale revenues. Once again, this is done in simple manner i.e. by hovering their mouse over such items, after which the customers are offered similar products that they can browse and ultimately find something they would like. As the next step in shopping personalization, this technology allows visitors to experience online what they are offered as default UX in physical stores – inquire shop assistant about items they are currently looking at.

Wrap-up

 

In today’s world of ecommerce, customer experience has become the new retail battlefield. Image recognition technology promises to transform user and shopping experiences across the board, with genuine prospects for widespread adoption. Its advantages comes to the forefront in its synergy with AI technology which allows it to make great strides in the fields of visual search and product recommendation, particularly in e-retail. Therefore, the key issue regarding its future is that of “when” it is to be adopted, instead of mere “why”. The image recognition tech for this game changer is to make your customers come back for more following its implementation.

 

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