E-commerce is a booming sector in the retail industry. Representing an estimated value of $102.7 billion of sales in the United States (U.S.) in 2016, it is poised to keep its exponential growth in the years to come. To maximize benefits, large firms are continuously exploring innovative means, especially Artificial Intelligence (AI), to enhance competitiveness and boost customer loyalty.
The most popular AI apps used by large firms
As AI is steadily infiltrating the retail market, there are certain common apps that are being adopted by large firms in the industry such as Ebay and Amazon. The most popular AI applications are:
These apps have been designed to respond to customer inquiries, to voice commands for basic tasks and to provide product recommendations through interactions using natural language.
Machine learning algorithms are being elaborated to use data to automate warehouse operations.
Recommendation engines are playing a key role in helping companies become more customer-oriented. These tools are facilitating their task in analyzing customer behavior on websites. At the same time, using algorithms to predict what products or services may appeal to customers and provide recommendations to the latter becomes a simple process.
How business leaders are using AI today
If there are some common patterns in AI apps being used by behemoths in e-commerce, the companies are, nevertheless, tailoring the apps for their respective businesses. Machine learning and recommendation engines are the two principal AI apps adopted by Amazon. Even if Alexa is a more visible app for the giant, machine learning is the company’s most lucrative tool. Machine learning is used to drive the algorithms that are at the center of Amazon’s marketing strategy, allowing the company to predict what products will most likely interest customers. Hence, based on customer searches, customized recommendations are released.
In similar efforts, Alibaba introduced Tmall Genie that has been designed to perform certain tasks such as controlling smart-home devices, checking the weather or a user’s daily schedule. Currently, it is only available in China and is programmed to receive commands in Mandarin language only.
Automation and robotics also play a decisive role in Amazon’s approach to warehouse operations. These tools improve delivery efficiency and reduce shipping costs too. Beijing-based JD.com has equally been quick to use automation and robotics in warehouse logistics. The company witnessed a drastic improvement in the efficiency and speed of product sorting and delivery, thereby reducing costs and ultimately increasing revenue.
Deep learning is viewed as a powerful tool in enhancing customer satisfaction and in subsequently driving sales. Amazon, for instance, has leveraged deep learning combined with computer vision and sensor technologies to know when products are being taken from the shelves or are being returned to the shelves. These products are kept track of in virtual carts and customers are charged via their Amazon accounts. In this manner, the traditional check-out system becomes void. The company is constantly improving the system to make it as flawless as possible, following various technical difficulties in tracking and processing large numbers of products and customers.
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