How AI is changing the retail landscape (1/2)

The applications and technology behind them

Deepak Singh


different AI spaces shown by graphic images

The application of AI is very interesting and fantasizing in the domain of healthcare, defense, and security. However, we do not see a lot of commercial applications reaching end-users. The papers are promising but very difficult to implement on the scale, also because of the regulations. However, in the Retail domain, the stakes are not that high as healthcare, hence, can be experimented with. Retail encompasses shopping malls to online purchases and from transportation to stacking of items in warehouses. Today we will talk about the commercial applications of AI in the Retail Industry and also take a glimpse of the technology behind it.

Most of the latest advancements in Retail are one or the other way due to the wake-up call from Amazon. Retail AI startups have already raised $1.8B across 374 deals from Q1’13 to Q3’18.

a chart showing invetment in AI startups
Source: CBInsights

Brick-n-Mortar stores are compelled to innovate to stay competitive and re-think their e-commerce strategies. Below are some latest trends, or rather use cases that are prevalent in the retail AI space as of now (2021):

1. Customer segmentation

2. Making brand visible on Shelves

3. Robotics in brick-n-mortar store

4. Voice shopping

5. Tackling shoplifting

6. Driverless deliveries with route/time optimization

7. Optimizing warehouses stocks

8. Marketing through deepfake

9. Cashier-less stores

10. Virtual shopping through AR

To discuss all of these is a topic of another day. What I would like to focus here today is more on the technology side instead of the business side. And that brings me to talk about the 4 key AI technologies that are being deployed to build AI applications for the retail industry:

  • Computer Vision
  • Natural Language Processing
  • Clustering
  • Advanced logistic regression

Let me dive a little deep into computer vision applications and some examples of their live use-cases. I will write about the remaining ones in the next part of this writing just so that the content remains digestible.

Computer Vision

The basic algorithm used for CV application is Convolutional Neural Network. Below you will find some applications with the reference links if you want to explore them further.

Customer recognition — Veriff

Veriff provides customer recognition services to companies who want to provide personalized experiences to their shoppers based on their face match and purchase profile from previous purchases.

Cashier-less stores — AmazonGo

As you already know, Amazon is expanding its ‘Go’ network outside Seattle. They call it “just walk out” technology where computer vision application is at peak in customer recognition and product pick/put identification. Use the linked URL above to explore more.

Deepfakes in advertising — Zalando Campaign

Zalando — A fashion brand used deepfake (a computer vision stream) to recreate thousands of video Ads from just one Ad of model Cara Delevingne in Europe. The deep-faked video had perfect lip-sync and accent as per the local place where that Ad was broadcasted.

Virtual fitting rooms — VironIT

VironIT is a CV application service provider which helps in installing virtual fitting rooms for retail stores so that a customer can try multiple clothes without the hustle of trying every cloth and size. A win-win for both the retail store and the customer walking into the store

virtual fitting room picture
Source: VironIT

Visual search while online shopping — Pinterest

Pinterest gives you options to click a photo of a lamp that you liked at a friend’s place and get multiple options of where to buy from.

Pinterest image search and shop feature
Source: Pinterest

Virtual shopping — IKEA

IKEA uses VR glasses and virtual rooms to virtually try a different combination of paint, flooring, curtains, and furniture in your house/room before even buying them. This is very useful as it is really difficult to decide them early on.

You can already see how computer vision has revolutionized the way people make selections. Though the technologies are not that perfect, they are advancing pretty quickly. And that is why the brick-n-mortar stores will have to innovate and re-think their e-commerce strategies to stay competitive. Big players like Walmart and IKEA are already ahead in the game.

I hope you learned a bit from this piece of writing. The second and final part of this article will be published soon. We will see how the other 3 key AI technologies i.e. NLP, Clustering, and Advanced logistic regression are changing the retail game. Stay tuned!



Deepak Singh

Product Enthusiast — Utilizing the power of AI and Design to rethink possibilities and reframe the problem statement! Website: