Artificial intelligence applications in e-commerce

The health crisis has changed consumer behavior. A growing number of users are now doing their shopping or purchasing online. As a result, e-retailers have to be more inventive in order to continue to increase their turnover and retain their customers. Artificial intelligence, or AI, and its applications are emerging as valuable allies in this quest for e-commerce innovation. What are the difficulties that e-retailers face in implementing them?

The artificial intelligence market, a growing market but an unknown technology!

The artificial intelligence market is growing rapidly according to forecasts by the statistics institute Statista.

It was worth 11.3 billion dollars worldwide in 2019, 17.3 billion in 2020 and is expected to grow fivefold by 2025. Nevertheless, for many of us, AI seems difficult to grasp, abstract and remote from our daily lives. However, contrary to popular belief, artificial intelligence often has concrete applications in our daily lives. Starting with e-commerce!

A growing number of buyers are now shopping online. E-retailers must therefore be more inventive in finding new functionalities. And improving the experience offered to their customers. AI meets this requirement by offering e-commerce a vast field of application. These include: personalizing the customer experience, improving search, optimizing inventory management. And responding to consumer requests and queries. What are the main applications of artificial intelligence in e-commerce?

1. The first application of AI in e-commerce: personalization and improvement of the customer experience. Thanks to personalized marketing.

How does it work in practice? User data (profile, purchase history) is stored and then reused thanks to algorithms. That will make product recommendations likely to interest consumers.

The aim is not only to better target potential buyers according to their tastes and interests and simplify their shopping experience. The aim is also to increase upselling.

This strategy is paying off and many companies have already adopted it. Amazon and Netflix have been pioneers in this field. Amazon saw a 29% increase in sales when it started using AI to make recommendations.

2. Second application of AI in e-commerce: visual search and virtual fitting

In the past, when an Internet user wanted to buy a product, he or she did a text search to find the item that met his or her criteria. Those days will soon be gone.

More and more companies are now using visual search. The aim? Always satisfy the consumer. And how? By allowing them to search through photos or images and test the product from a distance. For example, opticians offer their customers the opportunity to virtually try on the glasses of their choice using a webcam.

Riding the wave of the lockdown, L’Oréal Paris launched a free virtual cosmetics application called “Signature Faces” last November. The application offers a dozen filters and allows, during a professional connection or a video chat, to display one’s best profile. At the same time, it promotes the brand.

3. Third application of AI in e-commerce: stock management

Indeed, AI allows better management of stock-flow by making forecasts for the future, based on the study of customer behavior.

In other words, with AI, the management of stocks and logistics is perfected. How can this be done? Thanks to machine learning algorithms! Machine learning is an artificial intelligence technique that enables computers to learn from a database. But without having been programmed to do so! These algorithms spot future trends that are difficult to identify with traditional statistical or analytical methods. They anticipate which products are likely to sell well. They help to improve inventory accuracy and therefore reduce shortages or surpluses of goods.

These forecasts help e-commerce companies to improve the consumer experience. They increase customer satisfaction by significantly reducing delivery times and out-of-stock risks for certain products. Supply chain management benefits from the use of machine learning for equipment maintenance. Or the management of unforeseen problems during the delivery route. Such as weather conditions, for example. Thus the algorithm helps to :

• identify the best shipping route
• optimize a delivery driver’s route
• allocate goods to the most appropriate warehouse.

4. Fourth application of AI in e-commerce: chatbots for managing customer requests

Their use is multiple: to help find a product, track a parcel, give information, or place an order.

They are intended to replace the advice and expertise of the point-of-sale staff. But also to guarantee an optimal customer experience. This technology is highly appreciated by the young population, which is a major consumer of instant messaging.

Some chatbots go even further. The beauty and cosmetics sector rivals in this respect. The start-up “Sommelier du Parfum” uses its online messaging system and questions to find the fragrance that best suits its personality. At the same time, the company recovers useful data to understand the relevance and the adequacy between the offer and the consumers’ tastes. The L’Occitane brand, for its part, has developed the chatbot “My hand expert” to enable customers to discover their beauty routine. They receive a promotional code in exchange for sharing their data. The result? An average interaction time of 1 minute 35, 69% of subscribers shared their data, and 35% of respondents generated sales by using the promotional code (source: Numberly).

Implementation difficulties for e-merchants.

However, despite the vast field of applications and possibilities that we have just outlined and studied, artificial intelligence remains relatively little used at present in e-commerce.

Today, AI used in e-commerce remains basic and it is estimated that it will take several decades to see sophisticated AI applications in e-commerce.

AI cannot be bought, it has to be built: the transition from simple to advanced AI will be done through Deep Learning techniques that allow AI to learn and strengthen itself over time. This low exploitation is explained by the many challenges facing e-tailers.

Firstly, integrating this new type of application into an existing architecture is not easy.

Secondly, e-retailers also need to train their staff in these new methods. And to recruit talent with AI skills. A reconsideration of the division of labor between humans and machines is another challenge.

Finally, the sharing of innovation between competing companies is crucial. “The global e-commerce giants have several thousand engineers working on the subject worldwide. Many French e-tailers do not have similar resources and often cannot offer such a wide scope of solutions. Sharing the investments, risks and expanding the opportunities for start-ups is the way forward,” recommends the KPMG study (L’Intelligence Artificielle au service du e-commerce, 22 October 2018).

There is still a long way to go before e-commerce can fully benefit from the fruits of artificial intelligence.

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The Powerlab team is composed of experts in new technologies and online sales platforms.

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