The Retail Industry has a New Cornerstone- AI and Deep Learning


Retail is one of a handful of industries that enjoys the involvement of almost every person on the planet. While the recent advent of technology has created a deep divide between the online and offline space, the bottom line for both remain the same- sell customers what they need and if they don’t know what they need, figure it out for them.

While selling customers what they need is the easy part and accounts for the consistency in revenues, it is the figuring out of their needs is where the new avenues of business expansion lie. Retailers (both online & offline) are too well aware of this fact but predicting the behavior of every customer is simply not possible, at least for natural intelligence. But thanks to the advancements in information technology and consequent adoption by artificial intelligence development companies, we today have applications that perform such tasks like clockwork.

Like it or not, almost every activity we do online- from social media to shopping to reading news, is constantly under the lens of such technologies to analyze and consequently predict our next move. But since retail industry has the most to gain, the AI and deep learning technologies they employ not only predict but are already shaping the way consumers behave and hence are influencing the underlying structure of the business as a whole.

So let’s take a look at both the spaces and the ways technologies have penetrated to influence almost every dimension of retail:


There is a popular assessment in the tech industry that Amazon has turned the retail into some kind of science experiment. And that isn’t much far from the truth. Though almost every dimension of popular e-retailers today reek of AI, we will here look at the two most prominent ones that customers face directly: recommendations and price.  


This is one of the most common areas where the artificial intelligence is applied to keep customers engaged and consequently boost sales. No, we are not here talking about the mundane recommendations were if you are purchasing a mobile phone, the recommendations will show you similar mobiles in similar price range to choose from. This approach is inefficient on two levels- (i) it risks cannibalizing its own sales; (ii) customers may get confused and just leave.

What artificial intelligence developers do instead is, they create an application that analyzes huge data sets about that particular section in which customers lie. Since we all have today huge digital footprints, they can easily access our purchase history, reviews, likes, dislikes, and match such information with thousands of other customers with similar purchase pattern and tastes, to finally come up with things we might be most interested in and fits within our expenditure habits. So, if two people are purchasing the same mobile, the application may recommend a high-end headphone to one customer, while a cheap back cover to another.


Discounted prices are one of the main factors for users preferring online purchases, which results in e-retailers constantly racing against each other to offer best prices. Along with AI enabled bots that search and compare the prices of different items from competitive retailers, there are many more deep learning enabled strategies that come into play while offering optimum price to their customers.

While it is no hidden fact that e-retailers often show different prices of the same item to different customers, primarily based on their purchase history, few actually know that they also tweak the prices even for the same customer. These systems compare the traffic, interest on any particular item, and even the time of day to previous sales record in similar conditions and come with an optimum price that the customers are most likely to pay.


Recently, Business Insider published a series of posts on “retail apocalypse” backed up with extensive research and data sets that caused a lot of panic in the offline retail industry. But the key aspect that many missed was- they were talking about “retail as we know it”. So yes, if you are still carrying out your business like you did 15-20 years ago, there is little chance that you will even survive for the next 5 years. But there is still a section of retailers who have promptly embraced technologies to not only ensure their survival but to see this apocalypse as opportunity with fewer competitors.


What convenience is for online retailers, experience is for offline purchases. No matter how efficient and feasible shopping online gets, it can’t possibly match the experience of actually walking into a store and feeling the products before purchase.

Keeping that in mind, offline retailers today are fighting on their strength instead of going after prices and convenience that they are sure to lose. There is a growing tendency where when a customer walks into a store, they no longer have to interact with shop assistants but with smart bots and even a virtual catalog to match the competence and inventory of online services on one hand, while still keeping a human touch.


Instead of being just another spot for shopping, offline retailers are today transforming themselves to be more like a part of their customer’s community to form a more intimate relationship. The same AI and deep learning technologies that are used online for recommendations, can be used by these stores to bring together more like-minded shoppers and hence create an ecosystem around which they do not only sell products but also engagement.  

Final Thoughts

Retail industry, being one of the most comparative markets around, is also a constantly changing one. To survive and to ace in this industry requires not only efficiency but a relentless push for innovation and ideas. We have already seen once in late 90s, how a new technology, namely internet transformed the landscape of retail, and we are again at a similar tipping point with the next stage of transformation has just begun. So, no matter the channel you use for your retail business, there is no escaping from these technologies. If you don’t know how to start, consult a team of experts to guide you through.

  • By Mrityunjay Kumar, content developer at Konstant Infosolutions, a mobile app development firm based in India.

This content is original to AI Trends.