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We have come a long way from what ecommerce looked like two decades ago. From a non-existent entity, it has grown into a world-devouring business model that is a real threat to the traditional retail industry. It has moved from a basic static web page with limited product listings to a full grown virtual marketplace where anyone can buy or sell anything from anywhere at anytime at the click of a button. At the heart of this transformation are two things: customer experience and technology.

This is what Jeff Bezos, founder & CEO of Amazon, one of the world’s largest ecommerce sites believes:

We see our customers as invited guests to a party, and we are the hosts. It’s our job every day to make every important aspect of the customer experience a little bit better.

Now with the advent of AI, the retail space especially e-commerce is undergoing another major transformation that will redefine customer experiences and thereby once again change the dynamics of the industry.


So, how is AI-powered ecommerce actually changing the way shoppers shop?

AI-powered ecommerce makes search easy, accessible and intuitive

Looking for something? Type it! Say it!…Searching for a product you can’t name? No worries. Just show a picture.

“A lot of the future of search is going to be about pictures instead of keywords.” – Ben Silbermann, CEO of Pinterest

We take that statement with a pinch of salt. But we are reasonably confident that a lot of product search is going to be non-text based. Though text searches are common, voice and image searches in e-commerce are now gaining traction. AI makes it possible for the customer to move beyond simple text-based product search and search more easily and intuitively through voice and visual product searches. This also makes search more accessible. It uses Natural Language Processing to understand the customer’s natural language, be it in text or speech to provide more relevant search results. Visual product searches are made possible through a combination of computer vision, image recognition, and reverse image search algorithms.  

Amazon Echo, a home-automated speaker has a voice assistant Alexa that helps customers to buy products online by having simple conversations with Alexa. Slyce, uses a visual search feature, wherein the customer can scan a barcode, a catalog, and even a real image; just like Amazon’s in-app visual feature. Clarifai helps developers to build applications that detect images and videos and searches related content.

AI-powered ecommerce makes personalized product recommendations  

When you search for a product, the AI underneath recommends further options based on your search history or depending on what other users who have similar tastes found interesting.

Recommendations engines employ one or a combination of the three types of recommendation algorithms: content-based filtering, collaborative filtering, and complementary products. The relevance and accuracy of the results produced depend on various factors such as the type of recommendation engine used, the quantity and quality of data used to train the system, the data storage and retrieval strategies used amongst others.

For instance, Amazon uses DSSTNE (Deep Scalable Sparse Tensor Network Engine, pronounced as Destiny) to make customized product recommendations to their customers. The customer data collected and stored is used by DSSTNE to train and generate predictions for customers. The data processing itself takes place on CPU clusters whereas the training and predictions take place on GPUs to ensure speed and scalability.

Virtual Assistants as your personal shopping assistants  

Now, what if we said you can have all the benefits we have discussed above without having to do a lot of work yourself? In other words, what if you had a personal shopping assistant who knows your preferences, handles all the boring aspects of shopping (searching, comparing prices, going through customers reviews, tracking orders etc.) and brought you products that were just right with the best deals?

Mona, one such personal shopper, can do all of the above and more. It uses a combination of artificial intelligence and big data to do this. Virtual assistants can either be fully AI driven or a combination of AI-human collaboration.

Chatbots also assist shoppers but within a more limited scope. They can help resolve customer queries with zero downtime and also assist in simple tasks such as notify the customer of price changes, place and track orders etc. Dominos has a facebook messenger Bot that enables customers to order food. Metail, an AI-powered ecommerce website, take in your body measurements. With this, you can actually see how a clothing would look on you. Botpress helps developers to build their own chatbots consuming lesser time.

Maximizing CLV (customer lifetime value) with AI-powered CRM

AI-powered ecommerce in CRM aims to help businesses predict CLV and sell the right product to the right customer at the right time, every time leveraging the machine learning and predictive capabilities of AI. It also helps businesses provide the right level of customer service and engagement. In other words, by combining the predictive capabilities and automated 1-1 personalization, an AI backed CRM can maximize CLV for every customer!   

Salesforce Einstein, IBM Watson are some of the frontrunners in this space. IBM Watson, with its cognitive touch, helps ecommerce sites analyze their mountain of customer data and glean useful insights to predict a lot of things like what customers are looking for, the brands that are popular, and so on.  It can also help with dynamic pricing of products by predicting when to discount and when to increase the price based on analyzing demand and competitions’ pricing tactics.

It is clear that AI not only has the potential to transform e-commerce as we know it but that it has already become central to the way leading ecommerce platforms such as Amazon are functioning. Intelligent e-commerce is here and now. The near future of ecommerce is omnicommerce driven by the marriage between AI and robotics to usher in the ultimate customer experience – one that is beyond our current imagination.

A Data science fanatic. Loves to be updated with the tech happenings around the globe. Loves singing and composing songs. Believes in putting the art in smart.

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