Ecommerce has always been at the cutting edge of tech innovations, from the early adoption of mobile-friendly websites, to quick and easy checkouts. The online shopping experience has drastically changed from the early days, and as ecommerce continues to grow, AI will play a role in shaping the future of the industry.
Many businesses have already implemented AI tools for ecommerce to increase conversions, improve customer retention, and enhance their operational efficiency. This article will explore the different types of AI for ecommerce, some practical applications, best practices, and the benefits, risks, and future trends to expect as AI for ecommerce takes a foothold in the industry.
AI isn’t just one type of technology. There are various models available, but below are the most commonly used in ecommerce.
Natural language processing is the ability of a computer program to understand human language as it is regularly spoken and written. This enables computers to interpret inputs and generate responses in human language.
Generative AI refers to algorithms that can be used to generate new content, such as audio, code, images, text, simulations, and videos. These models are trained on large datasets to produce responses based on the existing data.
Machine Learning (ML) enables computers and machines to imitate the way humans learn and perform tasks, and also improves their performance and accuracy through exposure to new data. Classic ML relies on human intervention and experts to learn, by providing the structured data and input required.
Deep Learning is a specific branch of Machine Learning, and it uses artificial neural networks to learn from data. Inspired by the human brain, Deep Learning algorithms can be used to solve a wide variety of problems and perform tasks like classifications and feature learning.
There are many ways that ecommerce brands can use all of the different types of AI described above to accomplish tasks. Here, we’ll cover some of the main applications for AI in ecommerce:
Collecting and processing customer data is invaluable for ecommerce brands, and the more you know about your customer, the more you can personalize the entire shopping experience.
AI can analyze the ads that generate a sale, which path the customer takes before completing a purchase, and utilize this information to simplify the buying process. Additionally, AI algorithms can generate product recommendations based on past purchases and browsing history to offer personalized suggestions. Cross-selling and upselling are common ways that ecommerce brands can use AI to increase potential revenue.
AI for ecommerce can analyze customer interactions with the brand, and use that information to predict the best time to send emails to optimize for conversions. Additionally, AI-driven segmentation can ensure highly targeted marketing campaigns are more efficient. For example, Triple Whale’s Recency Frequency and Monetary Value (RFM) customer audiences are generated using an AI algorithm, and can then be used to create targeted campaigns.
AI helps businesses to optimize stock levels by analyzing demand fluctuations to determine when new stock may be required to prevent understocking issues. On the flip side, AI can also help to analyze whether an item is moving fast enough to prevent overstocking. With a reliable forecast, ecommerce brands can better manage supply chains and inventory.
With historical and real-time data, AI can analyze past sales to anticipate seasonal spikes in demand, which can help businesses to prepare effectively. With Triple Whale’s Moby AI, a simple question about anticipated revenue can generate a forecast for the year ahead.
With dynamic pricing models, ecommerce brands can use AI to alter product prices based on demand, customer behavior, or their competition. They can use these dynamic pricing strategies to maximize revenue during their peak periods, but also to maintain their competitive advantage during low traffic periods.
The most commonly used AI for ecommerce, chatbots have changed the game for ecommerce websites. The main benefit is the 24/7 availability for customer service, which provides customers with prompt responses that take the load off real human customer support representatives. As AI for ecommerce improves, chatbots can also collect customer data and handle simple transactions like orders and refunds.
The chatbot on Kiehl’s website is there to guide customers through the whole skincare buying process by suggesting certain products based on skin types or concerns, which helps customers feel confident they are purchasing the right product.
Search isn’t only text-based any longer. With visual search, customers can upload images or screenshots of items they seek. AI can then analyze the image and retrieve similar products to present to the customer.
Some benefits of visual search include:
With AI, ecommerce brands can generate content like text, product descriptions, marketing content, and more. Since AI can generate content much quicker than human creators, this can greatly reduce the hours required to generate this type of content that is often time-consuming. However, human oversight will still be necessary to ensure the generated content is high quality and innovative.
Shopify Magic can generate or rework existing product descriptions right in the product page, so if your copy is feeling a little stale, see what a little magic can do!
With generative AI in ecommerce, brands can also personalize their messaging to customers based on customer input, which can lead to better customer experiences.
AI can analyze the end-to-end transaction data when a customer makes a purchase to identify patterns that may look fraudulent. AI can evaluate factors like the cost of the transaction, customer purchase history and frequency to determine if a transaction presents a risk to the brand. It can also cross-reference shipping and billing information and identify any discrepancies that might point to identity theft.
Decreasing the amount of time brands spend on tasks, especially repetitive ones that a machine can handle, are relevant for all of the above applications. Some especially labor-intensive tasks that AI can relieve include inventory management, customer support, optimized web search, and personalized product recommendations.
While most of these features AI can help with are customer-facing, the capabilities of AI can also significantly reduce the amount of manual labor required to manage backend operations for ecommerce brands.
If you haven’t already integrated AI in your ecommerce strategy, here are some potential applications and strategies that might benefit your brand:
Using machine learning, brands can create hyper-personalized customer experiences that improve customer satisfaction and loyalty. In the days before AI could do these things for us, personalization was limited to broad demographics and preferences.
But with AI, we can dig into deeper customer insights by utilizing first- and zero-party data to personalize marketing on a more granular level. A report from McKinsey indicated there’s a 10-15% increase in potential revenue and retention when implementing omnichannel personalization strategies.
A simple way to implement this as an ecommerce brand would be to utilize an AI-powered feature that makes product recommendations based on what the customer has in their cart, by suggesting items “people also purchased” that are relevant to that specific customer.
A tool like Attentive AI can utilize the consumer data along with generative AI to create SMS and email messages that are relevant and helpful for the individual customer, which makes them feel known and valued by the brand.
A chatbot can act as a virtual assistant for your customers, and also deal with customer service inquiries, field customer questions, and facilitate online shopping by providing tips to customers on the website in real time. These bots can also help customers to stay engaged on the site by triggering conversations, offering help, or making product suggestions. Amazon’s Rufus was introduced in late 2024, and is a generative AI-powered conversational shopping assistant that can surface customer reviews, product details, and also compare products right in the Amazon App.
Using conversational AI and NLP, an AI chatbot for ecommerce can analyze the customer input and intent before generating a response that sounds (nearly) human. Chatbots can even serve as an AI shopping assistant, providing product recommendations, suggesting bundles, or answering inquiries in real time. This can help with customer satisfaction and hopefully quicker resolution to any issues that may come up while a customer is shopping.
Chatbots can also be used to collect leads, either through interactive conversations, questionnaires, or quizzes that make it fun for customers to provide you with relevant data about them.
To help users discover better search results, AI can unpack user intent, decipher more complex prompts, and deliver answers in an accessible way for the customer. They typically use NLP to better understand the human meaning behind the inquiry.
In the past, a simple Google search would have used keywords to provide relevant answers to a query. But now, an algorithm assesses several factors before producing those results. And Google now has AI Overviews, where it pulls what it has determined is the most relevant answer to your search and presents it at the top of the result page.
On a website, AI-powered ecommerce search can help visitors find the specific product they’re interested in from the search bar. Behind the scenes, the NLP of a site’s search tool can decipher the specific product attributes from a customer’s search, including the product style, material, color, and type to present the correct search result. A search tool with better understanding can help increase conversions by presenting the product a customer is searching for quickly and easily, to remove friction. For example, a search for seamless on Gymshark’s website automatically pulls up their most popular seamless leggings for women ahead of other products, as the smart search has assumed this is the product I’m looking for.
As you may have gathered from the content described above, there are several benefits to using AI for ecommerce.
When you’re able to gather and analyze sales data, you can personalize your sales funnel to generate more conversions. Simba Sleep improved their return on ad spend (ROAS) by 30% on their Meta ads by using Triple Whale’s RFM (Recency, Frequency, Monetary Value) audiences to better target their high-value customers. They synchronized the audience created via Triple Whale’s AI algorithm to Meta, created a lookalike audience, and were able to generate a boost in sales.
Using AI tools for ecommerce, like Triple Whale’s Summary Page, ecommerce brands can significantly improve their efficiency and ability to make strategic decisions. Origin was able to recover 40% of their Business Analytics team’s time by utilizing Triple Whale, allowing them to focus on other parts of the business.
AI solutions for ecommerce customer service can improve customer satisfaction because there’s 24/7 availability, which means a customer can achieve resolutions to their issues at any time.
The instant support will make customers feel seen and heard, and the more customers interact with support bots, the better the AI will get at answering customer inquiries. When AI provides relevant product suggestions and personalized offers, ecommerce businesses will benefit from improved engagement and enhanced customer loyalty.
While AI has many benefits for ecommerce, its use is not without risks. Below we will list a few drawbacks and some potential solutions or ways to mitigate them.
AI systems for ecommerce glean copious amounts of data from customers, including personal, financial, or medical data, which raises concerns about data security and privacy. Any ecommerce brand will collect data like names, addresses, purchase histories, and financial information about customers, and if the information isn’t properly secured and AI systems can access it, it opens the brand up to security breaches or identity theft.
How to mitigate AI in ecommerce security risks:
There are concerns about AI generating deep fakes, often featuring celebrities, that can make it seem like they have said something when they truly haven’t. Therefore, AI-generated content can mislead customers if it’s not properly monitored. Social manipulation and misinformation, like generating false customer reviews, can get brands into trouble and affect customer trust.
A human creator can generate a piece of digital art by entering a text prompt into an AI system, but who owns that content? Additionally, the data that algorithms are trained on have been accused of stealing and/or copying the work of true artists, which is a concern. AI has been advancing faster than legal systems can keep up, so guidelines will be necessary to clarify ownership rights.
Since algorithms are trained on historical data, there’s an inherent risk for bias. Biased data can happen when data is collected poorly or when there’s a lack of diversity in the data. When the algorithm is biased, it could mean that products are suggested to the wrong people, for example.
How to mitigate AI in ecommerce ethical concerns:
As AI improves for ecommerce, it’s possible that more human jobs could be replaced by artificial intelligence. This is a concern as it can reduce the need for customer service representatives, warehouse workers, or marketers. Automated systems are excellent at analyzing data and predicting trends, but they still require human oversight at this time. In the future, though, it is possible AI will be good enough to operate autonomously for ecommerce tasks, leaving humans without work.
A newer development in agentic AI are agents built specifically to assist with ecommerce tasks, like Moby Agents. These agents can be deployed to automate analyses and surface insights that would have taken a human hours or days to accomplish, which can help human operators save time for more strategic work.
How to mitigate job displacement in AI for ecommerce
The current evolution of AI tools for ecommerce are already extremely beneficial for accomplishing tasks and improving operational efficiency, but the things AI can do will only continue to improve. Some future trends in ecommerce expected for AI in ecommerce are outlined below.
Blanket marketing to general populations just doesn’t cut it anymore.
AI ecommerce personalization is possible with advanced data analytics and machine learning tools that analyze users’ preferences, behaviors, and historical interactions to create tailor-made experiences in marketing. The goal? To make customers feel like they’re being communicated one-on-one, rather than as part of a general audience.
AI can process all of the gathered data to predict customer needs, which will enable brands to deliver highly personalized and relevant content in real-time.
For example, segmenting customers based on demographics or preferences enables businesses to identify their target audiences. A fully-customized experience for a customer meets them at their preferred touchpoint, whether through the website, mobile apps, email, or social media.
Hyper-personalization with AI will allow for even more granular personalization in the future, with features like personalized storefronts when you visit an online store, as well as immersive experiences with dynamically changing billboards.
At the current moment, the quality of AI-generated content is still not as good as human-designed content. However, with time, this is expected to improve, and content marketers will need to step up their game to stand out. As AI content generators continue to learn and improve, the line between AI-created content and human-created content will become blurry. AI content will be churned out at an inhuman rate, and marketing plans and efforts will change as a result of the modified advertising landscape.
Some companies have tried to jump on the AI bandwagon, with questionable results. Toys ‘R’ Us created a commercial about the origin of the company using OpenAI’s Sora, and the resulting video was referred to as both “creepy” and “an abomination” by critics.
Even Coca-Cola’s attempt to recreate one of their classic ads from 1995 with a fully AI-generated spot garnered mostly negative reviews. While the imagery was pretty and nostalgic, many said it was “devoid of any actual creativity.” If an advertisement can no longer connect with a consumer on a human level, can it be truly successful? Brands should take care not to lose the human touch that drives brand affinity and connection.
Visual search will continue to evolve further, and an augmented reality (AR) integration will allow customers to interact directly with products in an immersive environment. This will include virtual try-ons so customers can see what clothing or accessories might look like in real life, which will improve buyer satisfaction and reduce returns.
With AI-driven dynamic pricing, brands can take all of the data they collect about customer behavior, consumer demand, and current market conditions to then set agile prices to optimize profit margins.
Advancements in AI models will enable businesses to develop personalized pricing strategies in the future, so that unique deals can be offered dynamically to specific customers based on their preferences. Dynamic pricing can be modified based on demand, competition, or customer segments depending on the needs of the business. In the future, advanced computing power and improved algorithms will make it possible to enable real-time pricing decisions.
Advancements in AI for ecommerce continue to enhance a brand’s ability to streamline operations, generate content, and create personalized marketing campaigns based on the data brands collect about website visitors and customers.
While there are significant benefits to using AI for ecommerce, including driving revenue and enhanced customer satisfaction, brands should also be aware of the drawbacks: security and ethical concerns, data biases, and potential job displacement. By adopting AI tools for ecommerce in a responsible and strategic manner, ecommerce brands can make significant advancements to their marketing efforts to drive revenue.
Interested in adopting AI tools for your ecommerce business? Sign up for a demo of Triple Whale today!
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