In Retail, Computer Vision

3 Ways Computer Vision Elevates the Online Retail Experience

By Monica Watson

Today’s consumers are overwhelmed by virtually unlimited choices across multiple ecommerce channels for almost anything they want to buy - whether it's a new dress, a house, or flight. Computer vision (CV), a form of artificial intelligence (AI), helps smart retailers ensure the right product is discovered at the right time, reducing friction and creating a seamless experience to ultimately drive revenue.

In this post, I'll run through 3 ways CV AI is making the retail experience better by making it easier for shoppers to find what they want. Want even more examples and details around how CV AI is impacting retail along with real use cases and results? Download your full free guide to driving revenue with computer vision here!

1. Product Discovery Through Improved Tagging

Product discoverability starts with effective inventory management, which can be made more efficient through the use of CV AI. Automating your workflow with computer vision saves you and your team time and labor, as well as significantly impacting your bottom line.

tradesy uses CV for image tagging - learn more in the full guide to CV AI in retail!Retailers lose countless hours hours fixing inconsistent, inaccurate product tags in their catalog trying to make their products easier to find. The problem often stems from suppliers, who rarely have a shared taxonomy for labeling retail products. Computer vision is helping many retailers solve this issue and boost efficiencies in their inventory management processes. How?

Attributes identified in product images are like a universal language—it doesn’t matter which supplier built the product or the source country. Computer vision automatically identifies these attributes and creates highly descriptive product tags.

Impact of automated product tagging:

  • Reduced time to listing helps maximize product exposure
  • Better product descriptions improves 3rd party search engine discoverability
  • Enhanced onsite search capabilities results in more product views

2. Snap and Search Fuctionality

Image search for retail featuring Homes.com

In this age of instant gratification, consumers expect to be able to purchase on the go. However, thanks to widespread adoption across the industry, mobile apps are no longer differentiators for retailers.

Mobile-enabled visual search (or ‘Snap and Search’) helps connect customers with precisely what they are looking for at the moment of inspiration. Customers simply upload photos via their mobile devices and are instantly returned your visually similar items.

Impact of snap and search functionality:

  • Shorten path to purchase by offering customers exactly what they want, when they want it
  • Connect offline inspiration to online purchases
  • Enable high intent customers to make impulse purchases

3. 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 millions 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

Computer vision's impact on retail is real and growing. Consumers today expect to be able to find what they want exactly when they want it, and CV AI enables any company with a retail experience to provide that and, ultimately, increase revenue. 

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