How Retail Is Being Reshaped With The Help Of Computer Vision?

By Paul Wynter January 8, 2020

The retail industry has come a long way since it emerged as one of the leading industries worldwide and cemented its place in our economy. The influx of numerous wealthy investors, recruitment of manpower, and industrial prowess has transformed the retail industry over the years incredibly. Yet none of that change amounts to the remarkable transformation that has been caused to retail through computer vision. Modern-day retail businesses just cannot do without maintaining a digital space, and computer vision has become indispensable for having a competitive edge there.

Why is computer vision so crucial for Retail industries?

The proper use of computer vision has reshaped the way customers interact with their retailers. It has provided an innovative experience to customers through process automation and several customer delights. It has also allowed retailers to cut down on costs significantly. Computer vision is responsible for making the customer experience more convenient and fruitful. Features such as visual search and automated query answers, etc., have reaped benefits on both sides of the spectrum. Technological marvels have led to warehouse automation and user customization, resulting in enhanced operational efficiency for the retailers.

Why is computer vision so crucial for Retail industries?

Among the many significant ways that retail has been affected by computer vision, the following proved to be the most important ones. Let us view them briefly.

1. Putting emphasis on Context

In the case of traditional brick and mortar stores, we have all come across situations where we have come across things we want to buy yet have no information about them. In such scenarios, a tool named Lens can come to our aid. It aids our in-store experience by providing us contextual information about objects that are scanned through it. Information might not be constant but specific to products such as the date of manufacturing or the maker's name.

2. Augmented reality for buyers

The whole "try before you buy" concept has been turned on over its head through the help of augmented reality, where real-world aspects are combined seamlessly with computer-generated versions of the product. For instance, if we want to see how a pair of shorts will look on us, we could just click a photo of our lower halves and blend it through the augmented reality application. It would place the product's foreground on top of our lower halves' background, making it appear as if we are wearing it in a real image. Precisely positioning the product and placing it correctly, thereby making it look authentic, requires a lot of computer vision. These immersive experiences have heightened customer delight who can now experience the entire try and buy benefit from the comfort of their couch with the help of AR tools and the Internet. Retailers have been trying to push such features into their online apps and woo their customers into buying their products more often.

3. Accurate searches based on product attributes

We can quickly come across many errors in product descriptions, especially when it comes to catalogs. This has a negative impact on search engines. The good thing is that computer vision can be used to negate this aspect by discovering the missing product attributes that are visual such as color, size, etc. Machine learning can be beneficial in addressing product attribution issues in large eCommerce catalogs. Deep learning algorithms can flag the impending error as a second opinion generated from the computer, which can aid humans in making the final decision on potential corrections.

4. Improving efficiency through Warehouse automation

A warehouse functioning involves a lot of physical items being moved around. With the help of computer vision and robotics, we can automate these repetitive and tedious tasks and save on human efforts and time. Robotics and IoT can also be used to read exact geographical locations of particular items that are being locomoted. Great examples of such automated warehouses are the Amazon ones, where Ai and computer vision combine seamlessly to enhance operational efficiency significantly.

5. Innovating delivery

The moment a package leaves the warehouse for delivery, computer vision can aid us through the entire delivery process as well. With the aid of AI and deep learning, computer vision can complement robotics in physically moving the package towards its intended destination. Significant labor can be negated in this process. The package can be tracked more effectively throughout its delivery process, and every return and payment procedure can be accounted for adequately.

Conclusion

Computer technology has been revolutionizing industries for a long time. The retail industry is no stranger to computer vision as well. It has been instrumental in boosting production, enhancing process efficiencies, and heightening customer experiences for most retail sectors—the remaining needs to catch up and utilize these benefits to their best results.

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