5 Ways Artificial Intelligence is Molding E-Commerce

5 Amazing Ways to Use Online Shopping Analytics for E-Commerce

Thanks to the explosion in the amount of data collected through multiple channels – including the e-commerce channel – and the exponential growth in computing power, Artificial Intelligence is transforming the e-commerce sector. This has started to change the way e-merchants sell their products and services, but also the way customers buy them.

In e-Commerce, the customers are the power of a company, they have a lot of potential in their hands that can make or break a company. But this aspect can lead to a big profit as well as a humongous loss, the customers can compare prices between the e-Commerce platforms, and read give reviews, etc, and you lose in the game if you fail to give the customer a reason to buy the item from you.

E-merchants have become aware of the central and differentiating role that Artificial Intelligence will play in the future, in particular, to achieve the best possible performance. An active ecosystem of start-ups has started to develop innovative solutions for e-merchants, integrating a layer of Artificial Intelligence into the entire value chain: marketing, logistics, customer relations, innovative services. Bluehost, Groupby software, Kellontech, Yescatalyst are some of the major eCommerce solution companies.

Today, the challenge for e-merchants is to identify the solutions that will bring the most added value to their business model (Customer Experience, operational performance, commercial efficiency) and manage the implementation of these still limited solutions. technologically in order to be ready when they take off. Services like Groupby Inc. transform the way retailers can interact with the customers.

About one-third of the eCommerce platforms including the leaders, have already started testing or using Artificial Intelligence solutions within their organization, primarily on the personalization of the customer journey, inventory and supply management, the management of marketing campaigns, and the management of after-sales service.

Personalization and Improvement of Customer Experience:

AI makes it possible to identify customers through their characteristics and browsing behavior. Depending on the customer profile defined, navigation then becomes personalized on several axes: product recommendations, sorting, services, prices, etc.

AI algorithms make it possible to manage promotional campaigns for predictive and targeted marketing. They are able to predict the propensity of customers to spend on the merchant site with precise targeting, for example by identifying customers who need a promotion to trigger an act of purchase.

Automated and Intelligent Logistics:

The most common and mature application of AI in e-commerce today applies to logistics management, in particular through the management and anticipation of demand on stocks. In a context where omnichannel commerce is growing, merchants need to have a unified, reliable, and real-time view of their stocks in order to be able to optimize them.

Visual Search:

The recognition of shapes and images is a technology that is becoming more and more mature with direct applications in e-commerce, in particular through the use of mobile phone cameras. This applies in particular in the field of fashion to allow the search for products by images instead of words.

Management of Data References:

In order to manage ever-increasing volumes of data, in particular with the extension of product and information repositories, e-merchants (in particular Marketplace) have integrated AI to control and structure data: type of products, classification of products in the tree structure, management of missing or erroneous data, generation of key indicators and management tables… both global and individualized.

Customer Service Management:

About half of e-merchants use a more or less advanced chatbot on their site or on social networks to interact with the customer before and after the sale, 24 hours a day. These chatbots are able to collect data and offer a personalized experience.

The next step is the implementation of intelligent personal assistants to find products and order by the voice of the customer.


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