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Blog 20 Min Read

Give Your eCommerce Venture A Computer Vision Boost.

Ecommerce returns

E-commerce can be a tough gig, given rapidly evolving technologies,  changing consumer preferences, and a glut of choices. In this scenario, the most agile eCommerce companies are those that can adapt artificial intelligence (AI) driven technologies to automating back-end processes and freeing up human capital to discover more innovative ways to grow their business. 

Computer Vision is one such technology. 

What is a Computer Vision system?

A Computer Vision system is defined as one that “acquires, processes, and analyzes real-world images in order to produce numerical or symbolic information, often in the form of a decision.” Although there are building blocks common to all Computer Vision algorithms, as the applications evolve, each requires a specialized adaptation that enhances its capabilities.

Historically speaking, Computer Vision has been around for the last few decades. Lately, the commercial potential of Computer Vision has come to the fore, with applications in fields ranging from consumer-oriented (eCommerce, retail, medical, entertainment) to manufacturing (automotive, industrial) as well as security and surveillance. 

The forecast for the Computer Vision market is highly upbeat. It was valued at USD 13.75 billion around 2019 and is projected to reach USD 24.03 billion by 2027, growing at a CAGR of 7.8% between 2020 to 2027.

AI applications in retail
The applications of AI in retail and eCommerce are many and varied:

AI in Strategy

  • Intelligent demand forecasting
  • Intelligent pricing 
  • Competitor price monitoring

AI in customer-driven business development

  • Customer segmentation
  • Customer churn prediction
  • Personalized product recommendation
  • Predicting lifetime customer value
  • Automated content generation

How Computer Vision AI application drives eCommerce

  • Product image analysis
  • Digital asset management

eCommerce sites are nothing without their repertoire of product images. Managing said images  as part of the inventory as well as is a major task for an eCommerce site, especially when images run into the hundreds and thousands. Computer Vision makes it easier by facilitating the following actions:

  1. Ensuring high quality and fidelity of images. 

It is necessary for eCommerce sites to display product images that are optimized for the internet. Computer Vision scans upload images of the requisite high quality. Similarly, for aggregator or marketplace websites, it makes it easy for the administrators to ensure that their merchants upload visuals that meet the website standard for dimensions, pixel values, and watermarks (or lack thereof). Computer vision also ensures hygiene and optimizes storage space by identifying and eliminating duplicate images. 

ecommerce
  1. Automatic product categorization

This falls under the object detection feature of Computer Vision. Previously, when products were uploaded on the eCommerce website, it was necessary to sort them manually into their categories, such as T-shirts, mugs, clothing etc. Now, with object detection capabilities, this classification process can be automated.

Computer Vision also ensures that the right  image is lined up with the right description. Multilabel classification is enormously helpful when SKUs correctly fit several categories. 

Multilabel classification enables the system to extract attributes and use them to assign product images according to more than one category or class.

  1. Flagging inappropriate images

This is a highly useful safety feature of Computer Vision. It ensures that objectionable or explicit content is flagged and removed from the website before anyone spots it. In addition, images with copyright issues can be detected and moderated before the issue blows up out of proportion. 

  1. Establishing website credibility by detecting fake brands

Computer Vision makes it possible for the machine to scan and identify brand logos on a product image, and link it to the right company. This feature is useful for large marketplaces such as Amazon to pick out sellers that happen to be uploading their product pictures under a separate and fake brand name. In eCommerce, the smallest discrepancy or cause for doubt can lead to cart abandonment and the customer never coming back. Computer Vision helps you offset this eventuality. 

  1. Lining up personalized product recommendations for the customer

eCommerce websites nowadays have a personalized product recommendation line up for every customer, based on their previous purchases and browsing history. Computer Vision can scan the images even a random visitor is browsing, and identify what kind of product might be of interest to them. This capability has enormous potential not just in online retail goods but also in real estate. 

This feature is based on the “image similarity” detection capability, used by platforms like Pinterest to help customers find product images similar to the ones they like or have seen on social media. This allows the algorithm to detect how similar or dissimilar two images are. An image similarity model will compare two images and score them between the numbers 0 and 1. For example, completely identical images will be rated 0, and dissimilar images will score closer to 1. The closest selection will be presented to the customer or person browsing for products.

Return management
  1. Processing returns more efficiently

Returns management continues to be a major issue with eCommerce. It is difficult for retailers to keep track of every item ever returned, scan it for damages, and assign it to the correct bin post return or replacement.

Computer vision, however, can help detect errors much faster and with far fewer mistakes than the human eye. Saara’s computer vision system, for example, is able to highlight defects in returned goods and then communicate with the Saara supply chain system to mark a product as defective so it does not make its way into the inventory again.

In Conclusion

Computer vision to process orders and returns at scale is the future of eCommerce, and in a post-pandemic world, also allows more orders to be processed without human intervention.

Looking to adopt Computer Vision and other AI capabilities, platforms and tools to optimize your eCommerce potential? Talk to us at Saara.io for a solution that is just right for your eCommerce business. The payoff is sure to be big in terms of credibility as well as return customers, and enhanced customer lifetime value. 

Saara.io provides end-to-end automation on your eCommerce returns process, apart from powerful, AI-powered supply chain automation capabilities. For a customized demo and to see how Saara.io can help your eCommerce business grow better, please write to us at seema.t@saara.io

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