AI has become the Stanley Quencher of retail tech: everyone still wants it, but the initial hype died down sometime around early 2024.
As we head into the trough of disillusionment with GPT technologies, it’s time to clear the fog around the use of AI in e-commerce and start framing your decision making around the practical and profitable use of AI technology.
In this article, we’ll share 10 common use cases for leveraging AI to deliver real value to your Amazon or retail business. Let’s dive in.
10 Practical AI Use Cases for Retailers
Natural language processing (NLP). Large language models (LLMs). Generative pre-trained transformers (GPTs). In the beginning, simply understanding AI was the biggest nut to crack.
But that was then. These days, the hardest part is knowing how to execute and where to start in order to extract real value from AI.
Let’s explore some of the latest ways e-commerce brands are using AI to increase their e-commerce success.
1. Personalized Product Recommendations
Personalized product recommendations are like jet-fuel for your e-commerce conversion rates, accounting for nearly a third of e-commerce revenue. And thanks to a growing number of personalization engines and marketplace tools, they’re now accessible to most e-commerce sellers.
For example, Amazon Personalize helps sellers analyze customer browsing history, purchase history, and offer different types of product recommendations depending on the scenario. Sellers on Shopify and other channels can use predictive solutions like Dynamic Yield and Nosto to predict future buying behavior and tailor recommendations based on shopper intent, visual similarity to past purchases, geotargeting and more.
2. Chatbots and Virtual Assistants
Many e-commerce companies already use AI-powered chatbots to field and direct customer service queries. These bots can help answer routine questions and can even understand when to pass customers along, as well as which agent to pass them to. But there’s more that AI-powered virtual assistants can do.
European e-commerce giant Zalando is one of a handful of marketplaces offering shoppers the chance to chat with an AI-powered shopping assistant. Features like Klarna’s ChatGPT plug-in let shoppers tell a bot the exact specifics of what they need and get a relevant product recommendation, e.g.“belated Hannukah present under $50 for my friend who loves her dog way too much.”
3. Visual Search
While there’s been much talk about conversational AI search on marketplace platforms, visual search may still be winning the AI race. Tools like Google Lens and Pinterest Lens make it easy for shoppers to search for your products based on what they (or their smartphone cameras) can see.
Depending on your resources and strategy, implementing visual search on your own site may or may not be a goal. But any seller can take advantage of the rising demand for visuals by optimizing your product images for Google, creating ads that align with search results, and analyzing competitor images to ensure yours stand out.
4. Dynamic Pricing
Airlines and hotels have been using dynamic pricing strategies (a.k.a. yield management) since the 1980s, adjusting pricing based on long-term market conditions and shifts in supply and demand. However, in retail, the playing field is more crowded and the marketplace is more complex. Pricing changes need to happen fast.
AI-powered dynamic pricing assesses numerous variables at once to help retailers set the best prices for attracting customers while protecting profits.
Amazon sellers can take advantage of AI automatic pricing tools, while Walmart sellers can try the platform’s Repricer tool. On Shopify, sellers can choose from a variety of AI dynamic pricing apps that analyze variables like market conditions, competitor prices, and customer behavior to help you set the best price.
5. Fraud Detection
Preventing online payment fraud is trickier than most people think. On one hand, fraudulent payments cost US e-commerce businesses at least $38 billion in 2023. On the other, false declines are estimated to cost over $600 billion each year in lost sales and likely much more in customer churn.
Sellers need ways to stop fraudulent payments without inadvertently declining — and alienating — honest customers at checkout. AI and machine learning solutions like Shopify Protect and Amazon Fraud Detector can analyze transactions, score risky payments, and detect suspicious behavior, while minimizing the risk of false positives by analyzing historical payment data and understanding evolving fraud tactics.
6. Marketing Automation
You already know there are plenty of ways to use AI to automate, personalize and optimize your marketing. For example, you can use AI to analyze key customer data points, including social media interactions, browsing history, past purchase behavior, and more.
Among many tools, Bloomreach’s AI solution, Loomi, can create hyper-personalized emails, SMS messages, and real-time mobile notifications. AI-powered marketing tools can also help you determine each customers’ level of current intent to help you send more effective recommendations, messages, and reminders.
7. Social Listening
AI tools aren’t just important for marketing segmentation. They can also help you analyze and interpret social media mentions, helping you stay ahead of any negative online mentions and giving you valuable insight into customer sentiment. You can find out exactly what customers are saying about your products and brand without spending dozens of hours in Meta groups and comments sections.
With easy-to-execute market research, you can use these data-driven insights to improve your existing products, launch new ones, and streamline the customer experience. Social listening also enables you to track mentions of competing brands and sellers, making it a powerful competitive intelligence tool. Use it to understand what is and isn’t driving traffic and customer satisfaction for your competitors, and compare your share of voice.
8. Demand Forecasting and Inventory Management
Machine learning is known for its ability to rapidly crunch large amounts of data and extract key patterns from, which can be critical for successfully aligning sales and inventory. AI-powered inventory platforms have algorithms that analyze your historical sales data to help you better predict demand and optimize your inventory levels to avoid over- or understocking.
In some tools, these algorithms can even identify and correct outliers in your sales data, such as viral trends, extreme weather events and more, to avoid inaccuracies due to past unexpected stockouts or sales peaks.
9. Supply Chain Optimization and Visibility
From delivery route planning and improved supplier selection to IoT tools that track shipments and inventory, AI in supplier relationship management can help you source from faster, more affordable, or more sustainable manufacturers.
For omnichannel brands,you can get deeper visibility into your supply chains, increasing on-time shipments and preventing delays before they happen. Some solutions also automate functions like purchase order generation, warehouse management and more.
10. Creative Assistant
Perhaps the most well-known use case for AI is in creative processes, like brainstorming and generating images and text. Retailers can use AI to assist with creating copy, generating customer communication transcripts, creating product images, optimizing their e-commerce websites for search engines, and so much more.
For example, the designers at Nike recently recruited the help of AI in brainstorming new product ideas based on specific customer needs. For Amazon sellers, tools like A+ Content can help with writing product descriptions and optimizing your product detail pages, but there are endless other tools on the market designed to help you improve your creative processes.
Top Dos and Don’ts for AI Adoption
With so many possibilities for adopting AI, it can be challenging to know where the guardrails are.
Here are some basic principles to keep in mind as you get started.
Do: Stay on top of how marketplaces like Amazon are using AI
One of the most significant uses for AI in e-commerce is in enabling marketplaces to more efficiently assess third-party sellers. For example, Amazon uses AI to aggregate and summarize customer product reviews, rate sellers, and evaluate seller complaints to determine if they’re legitimate.
While there’s little you can do to fix a bad review summary, you can fight back by using Amazon’s AI to write product listings that lead to better reviews. The key to winning with AI is to proactively assess its risks and maximize its benefits to stay competitive on every sales channel.
Don’t: Adopt AI for the wrong reasons
There are a million potential use cases for AI, but not all of them are worth your time. The wrong investments could cost cash, time, and resources — including staffing and training costs, data acquisition expenses, legal issues, and other hidden risks.
Before adopting any new tool, make sure you have a measurable goal in mind and a clear plan to make it happen. Take the time to do your research and avoid adopting AI tools while still in beta.
Do: Use AI to save time
Newer customer service chatbots use AI, machine learning, and NLP to offer conversational customer support. They can help process returns, answer common questions, and in some cases, even make product recommendations.
But be careful not to overdo it. A common practice is to use AI chatbots as “greeters” to get customers oriented and figure out what they need. From there, the aim is to get them to real human support as soon as it’s needed. You can also use AI tools to assist your human agents in generating faster, pre-written responses so that they know exactly what to say when they log on.
Don’t: Blindly outsource to AI
The reality is, AI tools just aren’t sophisticated enough to logic their way through relationship-building and problem-solving the way a human would. They’re prone to offending customers and generating false information that could even get you sued.
Even when they aren’t behaving badly, AI tools can frustrate and annoy customers. While it’s ok to trust AI with basic functions, always make sure there’s a human behind the wheel to actively guide and supervise the process.
Do: Use AI to get inspired
Generative AI can help you brainstorm slogans, captions, hashtags, and other short-form copy, as well as re-write or customize existing content in different voices for different audiences. It can help with image generation and ideation for original content. Some AI tools, like MarketMuse, can study your competitors’ content for gaps and help you develop stronger marketing campaigns, all of which can lead to better ROI.
Don’t: Forget that you’re in control
Without smart, creative humans at the helm, you could put your brand at risk of using plagiarized content, deceiving and manipulating your customers, or simply boring them senseless.
Instead of replacing your brilliant team members with lines of flawed code, invest in tools that automate their most tedious or overwhelming tasks, and help them perform at their best.
Get Real Results from Artificial Intelligence
With the right approach, AI can be a powerful tool to increase sales and boost operational efficiency. But as with any tool, you’re only going to get what you put in.
With clear expectations and a well-planned roadmap for success, you can get more out of your investment in AI and start using it to deliver real value to your customers and business.
For more on the future of retail, check out our growing resources hub. Looking for hands-on help? Explore our full suite of financial solutions to see how we can support your growth journey.
