Opinions

How artificial intelligence is changing retail for good

I hate grocery shopping!

Especially grocery shopping. Usually, I get my home groceries from a supermarket, where I usually get lost in its humongous spaces, endless aisles, waiting for eternity to get fresh cheese, and end up wasting so much time wandering in the markets and brands jungle.

Not to mention, the long lines of the cashier, in which I feel the world is going to end before I get to pay for my groceries.

Wouldn’t it be nice, to have someone meet me upon entering the supermarket, greets me, checks my list, and guide in the jungle, of the never-ending aisles of the store.

Not only that, knowing me, he recommends me the products, I’d love to buy. Further, he shows me all the special offers, in which I’d be most interested in, and according to my mood, he can show me where the chocolate is, when I am sad from a long day at work.

When leaving, I wouldn’t have to stop in lines, he will just charge my debit/credit card when I leave. He knows what I took, and for that, charges me with no hassle.

Now, I know that having someone like that for every visitor is practically impossible. Though with artificial intelligence, this is not only possible, and it’s very accessible.

Here’s how A.I can get me to love shopping?

Let’s call my grocery jungle A.I Guide Azka*. Azka is deployed at the supermarket I usually go to.

The moment I enter the store, I’ll get a personalized notification on my phone from Azka, greeting me.

‘Hello Ahmed, How are you doing today?”

How did Azka recognize me? Just like any other human would, from my face. From the cameras at the front door, Azka recognized my face and sent me a message on my phone.

That’s called computer vision, and it is the ability for computers to basically analyze images and videos and take decisions accordingly.

Azka, also understands my speaking language with NLP (Natural Language Processing), by which computers understand the language we naturally converse with.

So, I can reply with, “Hi Azka, I have a lot of shopping to do today, here’s my list.”

Now Azka, takes my list, shows me the way to everything in the most efficient path possible, with the least waiting times.

Further Azka knows me from my past purchases, knows what I like, and what I will probably like. This is an conventional A.I application, usually done through a mix of “Predictive Analytics” and “Clustering” .

Azka has me in a cluster of buyers who like certain things, like a Gaming enthusiasts cluster and it predicts what I’ll buy today, based on my previous purchasing behaviors.

This is what we call a recommendation engine, by which computers can show me the items, I will most probably like and purchase.

Amazon has reported to have had 35% of their sales coming from recommendation engines in 2017, that is billions of dollars in revenues. Not to mention, Azka can recognize my current emotions and can have me go to the aisles, not only based on my past purchases but also, on my current mood.

Throughout my experience, I can ask Azka on any products in my natural language, whether through speech or chatting, and it can respond to me right away. Whenever I don’t find a particular product, Azka can take note of it, and send it home to me, whenever possible. Whenever Azka is unable to help me, it can send me a Human Agent, who can resume my journey through the grocery jungle.

Now after I am done, Azka has been monitoring my every move, and it understands what I bought and haven’t bought. When leaving, I don’t have to stand in endless cashier lines, I can just go and Azka will charge me accordingly.

Now, this experience might be more of a dream or sci-fi series or movie. But actually, everything that I described here is very accessible through readily available technologies TODAY!

Amazon Go, for example, is pioneering this concept with Amazon Go!

What’s in it for Retailers?

Now for retailers, this kind of experience will give any retailer a new level of competition. It will add so much to the customer experience and make retailers more aware of who their customers are, what they want to buy, and basically give them much more insights on how their products are selling.

Not to mention, that Azka, can track traffic flow inside the store, and can give so much insight and analytics, on how to optimize shelves, so as to increase customer purchases.

It can also, predict an Intent of buying, by analyzing certain behaviors, emotions, and past purchases, and can give me a positive or negative intent.

Furthermore, retailers can grow their revenues by never missing a sales opportunity, that whenever the customer can’t find a product, they can just send it later. Better yet, with machine learning, such as Azka, retailers can predict the demand per product, and always make sure their shelves are filled with the right products, for which demand exists and is predicted, based on day, month or time of day.

They can look at their denied opportunities, that is the products that customers were looking for, or were predicted to buy, but did not get, either they didn’t find it or just forgot about it.

Also, from tracking the customer behaviors, through their aisles, they can reorder their shelves, to increase basket sizes and convert more purchases. Of course, with such a superior experience, I would always come back to the same store, to buy my groceries.

Based on research, just a 5% increase in customer retention can upheave profits by a staggering 95%.

This is how Azka, or machine learning, and artificial intelligence ARE (not will) changing the retail business for good!

*Azka, is a research project, lead by Synapse Analytics with the purpose of building an A.I platform, that makes it accessible for businesses to access Machine Learning Technologies, such as Computer Vision and NLP.

Here’s a sneak peek:

This video showcases Azka, recognizing individual team members and identifying their emotions.

Ahmed Abaza

Ahmed Abaza

Founder at Synapse Analytics
Founder & Managing Partner at Synapse Analytics, a Cairo-based company that helps its clients grow their business, leveraging data analytics and machine learning applications, in their marketing, and operations. Ahmed can be reached at aabaza [at] synapse-analytics [dot] io.
Ahmed Abaza

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