Ecommerce & Retail

The rise of AI technology is playing a huge role in the shift in consumer expectations. By bringing brands closer to their customers and making personalized service a normality, machine learning is introducing a host of new challenges to the retail industry. However, if AI is embraced, it also represents a huge growth opportunity.

The variety of AI use cases in ecommerce suggest that the ability to utilize mountains of previously unmanageable data is having far-reaching effects. In sales, AI is making it possible to accurately target valuable prospects, while virtual assistants can increasingly ask questions that improve individual recommendations and ensure a higher purchase rate. Machine learning models can also make use of data collected from the customer, analyzing unseen patterns in their behavior to ensure that the most popular products are always in stock. As the source of so many unique opportunities, it’s clear to see that a well-trained AI can provide a competitive edge for years to come.

Machine learning applications for the ecommerce industry

Sales improvement

Used correctly, customer data can be turned into a sales powerhouse. Developments in AI mean that it’s now possible to automatically retarget customers who have spent a lot of time looking at products, or even identify the kind of potential customers that can provide a constant source of business. By flagging unseen patterns in data, algorithms can help ecommerce sites to predict the likelihood of a product selling well with superhuman accuracy. It may even be possible to bring this technology into the real world through image or video tagging, providing the same insights by literally tracking customer time in store.

Virtual assistants

AI chatbots and virtual assistants can help retailers create a simple yet personalized customer experience. Advances in Natural Language Processing have made it possible to resolve customer questions without the help of a human, while also making individual recommendations based on the ensuing conversation. These models can also simplify the order placement process, either through asking questions or listening to voice commands. By simultaneously removing barriers to purchase and improving customer experience, the use of AI is proving the catalyst for a rise in customer loyalty.

Search relevance

Search relevance can make or break an ecommerce site. Through Natural Language Processing, AI is helping to ensure that search results remain consistent, regardless of what the customer types. By contextualizing search queries and comparing them to data about previous purchases, algorithms can learn to prioritize products which have high conversion rates. Developments in image tagging may also expand search possibilities, allowing AI programs to further hone a reliable, self-improving search engine.

Why Lionbridge?

In a world where customers expect personalized service, your model needs to have mastered a variety of languages and tones of voice if you want to engage your target audience. Lionbridge’s training data is founded upon native-level dexterity in 300 languages. Our range of specialist linguistic data services is the result of a decade of experience in cultivating a crowd of 500,000 certified language professionals. Whether your brand deals in slang, formalities or multiple languages, our scalable service can provide you with the gold standard you need.

How We Can Help

Chatbots

Draw in your customers by feeding your algorithm with training data from 500,000 language specialists working in 300 languages. LEARN MORE

Search relevance

Our scalable data annotation service is designed to provide you with the custom tags you need to build a search engine with pinpoint accuracy. LEARN MORE

Audio speech analysis

Whatever your target language or tone of voice, we can add richly detailed tags to your data that will guarantee your model’s gold standard. LEARN MORE