Understanding AI and how ecommerce businesses can use it
Vaishali Ravi
·March 12, 2025
These days, AI is everywhere: You’ve probably already used ChatGPT to help your brand optimize its product descriptions or build out ideas for a new marketing campaign. And many of the most powerful applications you use for your business—Loop included—are enhanced with AI features that help you automate key functions and drive new insights from your data.
We’re excited to tell you more about what we’re doing at Loop to harness the revolutionary potential of AI, but first, we’re going to dig into the fundamentals. In this blog, we’ll cover some of the key technology that underpins our AI products: machine learning, generative AI, and natural language processing. In our next post, we’ll showcase how we’re using these technologies to develop a best-in-class merchant experience at Loop.
Let’s get started.
Key AI technologies
Machine learning
Machine learning (ML) refers to algorithms that are trained on historical data to understand patterns in their relationships. Rather than being programmed with every single rule, ML algorithms can learn from the examples they’ve been given, and make predictions or decisions based on that. As you continue to feed it data, the algorithm adjusts its programs accordingly—helping it become more accurate over time.
For ecommerce brands, machine learning technologies can be used for a wide variety of functions to enhance your business’ performance and reduce costs, including inventory management and forecasting; dynamic pricing optimization (or “surge pricing”); fraud detection & prevention; and customer acquisition, churn, and retention forecasts.
Two subsets of machine learning technology—Generative AI and Natural Language Processing—can also be used to build out personalized and highly customizable experiences for your shoppers while helping you drive greater operational efficiency in your business.
Generative AI
Generative AI models, including ChatGPT, use neural networks to study patterns in existing content, which they use to generate new forms of content—including written language, visual content, and auditory content. Some common use cases for Gen AI in ecommerce include developing personalized marketing campaigns and facilitating VR/AR-enabled visual shopping tools.
You can set up prompts or build templates that ensure the content production is aligned to your brand’s requirements: For instance, when using the tool to design landing pages promoting your products, you can input your brand’s style guide to ensure consistency with your brand image.
While Gen AI is a valuable technology, you must pay close attention to ethical concerns when using it, such as avoiding the risk of copyright infringement or delivering misinformation. When used responsibly, however, Gen AI can serve as a transformative technology for your business.
Ecommerce brands utilizing AI is a major trend in 2025
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Get exclusive accessNatural language processing
Natural Language Processing (NLP) is a branch of AI that focuses on helping computers understand, interpret, and generate human language.
One common use case, Conversational AI, enables users to ask a question using natural speech, rather than requiring them to issue a pre-set programming command to generate a response. This technology is commonly used in chatbots and Virtual Assistant applications, and can dynamically generate responses to user questions based on real-time analysis of its data sources.
For instance, a customer might use your skincare line’s chatbot to ask a question about which products are right for their skin type, resulting in guided recommendations for products that fit their needs, drawing from real-time inventory availability. The shopper might follow up with a question about shipping fees, and be guided to relevant snippets from your website’s FAQ that cover those issues. Once the order is en route, they could ask “where’s my order?”, and get access to real-time carrier data showing the order status. By helping shoppers get the personalized information they need instantly, conversational AI tools can reduce reliance on live customer support and resolve issues more quickly.
NLP technology is also used for sentiment analysis, which interprets the emotional tone of language. It can classify text as positive, negative, or neutral, and even detect emotions like happiness, anger, or sarcasm based on context clues. Sentiment analysis can be used to generate insights around trends in perspective around a specific topic: For instance, you can use sentiment analysis tools to comb through your customer reviews and summarize their feedback. By adding notes such as “customers say this product runs small,” you’ll be able to add value when shoppers are considering a product, and help them gain confidence in their decision.
AI-powered applications are revolutionizing the way that brands connect with their customers, boosting operational efficiency, and helping them derive enhanced insights from their data. By incorporating best-in-class AI applications into your ecommerce tech stack, you’ll be well-positioned to guide your brand towards sustainable growth.
Up next, we’ll give you a peek under the covers at how Loop is leveraging AI to help you deliver a superior merchant experience while protecting your profits. Stay tuned!
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