In Computer Vision, Retail

3 Ways AI is Improving the Retail UX

By Monica Watson

Every retailer knows that delivering a satisfying, frictionless shopping experience is key, and consumer expectations have never been higher. According to studies by the Nielsen Norman Group, users will abandon your site within 10 seconds if they don’t see what they want.

Computer vision helps retailers improve user experience by not only accelerating the journey from inspiration to purchase, but also through offering new ways to help shoppers to source items that match their style. This directly impacts the bottom line: surfacing the right content to the right user at the right time, delivers larger average cart sizes, and keeps customers coming back for more. 

With that in mind, here are 3 ways AI is being used to improve that online shopping experience. 

1. ‘You Might Also Like…”

Intelligent product recommendations that shoppers might also like—driven by computer vision—are also increasing the likelihood of purchase. Recommendations powered by computer vision go beyond keyword search matches (i.e. 3 person sofa) to include visually relevant products that match other important characteristics, such as color, shape, and pattern.

The impact of visually similar product recommendations?

  • Offer specific, relevant purchase options to keep shoppers engaged
  • Deliver consumer satisfaction via a faster journey from inspiration to purchase
  • Reduce bounce rates and increase conversions

2. Out Of Stock Alternatives

Finding a product you like only to be told it’s currently unavailable is a frustrating experience. In the past retailers have tried to maintain buyer interest by implementing tactics such as in-stock email notification options. However, retailers are still losing billions of dollars thanks to these lost purchase opportunities.

Computer vision offers a significantly more effective way to handle out of stock scenarios by returning items that are visually similar to the unavailable product as an alternative to the customer, who is then able to complete their purchase quickly without looking at competing sources.

Impact of visually similar out of stock alternatives:

  • Maintain competitive edge by proposing relevant alternatives
  • Offer frictionless shopping experience - even when items are unavailable
  • Reduce bounce rates and increase conversions

3. Social Inspiration

Sometimes shoppers love a style, but they don’t know how to describe it for a keyword search. With the rise of social media sites like Pinterest, it’s easier than ever for consumers to curate images that match their taste.

Retailers are beginning to capitalize on this, by connecting consumers to the products that directly match their style by using computer vision to identify styles in the consumers’ social media to the items that are visually similar in their inventory. For example, a customer can connect their Pinterest board to a retailers website and be shown multiple items that correspond to the look. West Elm did exactly this with their Clarifai-powered Pinterest Style Finder.

Impact of social inspiration product recommendations:

  • Deliver exceptional user experience, connecting style to purchase
  • Increased basket size, with multiple purchases
  • Greater cross-sell and upsell abilities

This was just a small portion of the information you'll get in our full retail + AI guide! Check it out below: 

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