Industry experts compare the launch of AI to the invention of the printing press or the first personal computer. It has become one of the leading software development areas with vast growth potential. Over 50% of businesses have already adopted AI to their operations, and 76% of enterprises report increasing investments in AI in 2023. Statista’s data suggests that the...
E-commerce is on the rise. Every 1 of 5 retail dollars is spent online now, and this share is steadily growing. Why? Online shopping is easy, fast, and convenient – we all know that.
However, it is not all roses. Shoppers cannot feel, touch, or try on a product online, so, the possibilities for building customer connections are rather limited. And on top of that, advanced technologies bring new security threats.
Good news? Using AI in e-commerce can smooth out the bumps. This article shares remarkable examples of AI that help online retailers solve issues and master wonderful opportunities the technologies bring to the industry.
This is a part of the “AI in retail” series, where we showcase all aspects of AI implementation for small and mid-sized businesses. Other articles on this topic include:
- How retailers benefit from AI innovations;
- The general overview of the AI in retail niche with trends and challenges to solve;
- How AI solutions transform offline stores;
- Top 10 things to consider before AI implementation;
- How to choose between custom and ready-made AI tools.
How AI Transforms E-commerce: Market Overview
Online shopping is way faster and more convenient than roaming around offline shops. That’s a fact. But let’s get back to a few years ago and remember the pandemic shock. Back then, shopping online was the only choice we all had, be it Europe or Americas. Covid only accelerated the inevitable market growth.
What we witnessed back then was an incredible e-commerce boom. Americans alone spent 1.7 trillion USD online between 2020 and 2022. It’s 609 billion USD more than in 2018-2020. If you own an e-commerce business, you know exactly what we’re talking about.
But what’s coming next?
We all understand how hard it is to say ‘no’ to convenience, and the lowest are the chances that people will stop buying products and services online. Statista states the e-commerce market is likely to reach 5,026 billion USD, growing steadily with a 10.15% CAGR. In other words, consumers will consume even more.
Examples of AI in online shopping can play a huge role in this market rush. There is hardly a more effective technology that can help businesses cope with a growing demand and improve nearly every operation.
According to Precedence Research, the market of AI-powered e-commerce can reach 22.6 billion USD in 2032 compared to 6.63 billion USD in 2023. The niche is developing by leaps and bounds.
Now, we can prove to you that artificial intelligence is not only for corporate giants. It can be a tiny improvement in, let’s say, your customer service that won’t cost you a fortune. Here is a great deal of AI use cases in e-commerce examples to introduce you to new business opportunities.
AI for Hyper-Personalization in E-Commerce: Learnings from the CHI Software Case
Let us start with what we know best – the project we built ourselves. It is a story about a renowned US beauty retailer and an innovative solution for hyper-personal recommendations.
The Project Context
Personal tips work great for selling skincare and makeup, especially in brick-and-mortar stores where sales assistants can help. But things get tricky in e-commerce.
First, people often shop off-hours, like late night, when no human sales assistant is available for advice. Second, online experts cannot analyze your skin well and have to go by what you describe. Consultancy of this kind will not make your customers fully happy.
To tackle the problem, our client came to us. Their idea? A user-friendly app with a conversational AI chatbot for e-commerce and in-store shoppers. This software would diagnose skin issues and recommend relevant makeup and skincare products.
Curious about how it all works? Let us take a step-by-step journey through the flow.
- Selfie: A user takes a selfie using the app for a skin check.
- Face mapping: The savvy algorithm quickly spots a face in the photo and pinpoints up to 126 key face areas.
- Analysis: The app studies the features, comparing them to a vast library of samples to spot where the skin might use some help.
- Tailored recommendations: The app uses advanced AI to select beauty products in stock that fit the skin’s needs.
- Chat and guide: A friendly GPT-powered chatbot shares the results and suggests skincare routines. It is like having a beauty expert right in a pocket!
- Deeper personalization: Users can get even more personal results by adding allergies, product preferences, or budget details. The more the app knows, the better it can serve.
Are you ready to see the outcomes? Here they are:
- Boosted sales: With spot-on recommendations pushing more relevant products, our client achieved a 10% jump in sales and revenue from cross-selling and upselling.
- Happier customers: By offering choices that hit the mark, the client created a stellar shopping experience that led to a 5-7% growth in customer loyalty and satisfaction.
- Smarter inventories: Inventory management becomes easier with insights based on customer favorites and purchases. The big win? Fewer stock run-outs and a 5% dip in inventory costs.
Our AI in e-commerce tool does a lot of helpful things at once. It serves as a skilled beauty adviser giving tips on skincare, and it is a friendly virtual assistant that helps in real time. And that is just the start of what AI can do in e-commerce!
Artificial Intelligence in E-Commerce: 15 More Use Cases to Discover
Many mind-blowing AI solutions for e-commerce are appearing right now. We will discuss generative algorithms, virtual fitting rooms, and security-enhancing software. Using AI in e-commerce, you can address almost any problem to create an unforgettable experience. Let us jump to the examples!
1. Chatbots and Virtual Assistants
We showed how the ChatGPT-based virtual assistant can suggest products personally for your customers. But AI chatbots for e-commerce can do much more. They can answer questions, assist with payments, collect reviews and complaints, help with post-sale services, or even do all these tasks simultaneously.
The Use Case Highlight: IKEA
Ikea started using an AI chatbot named Billie to help with customer service. Billie can track orders, change delivery times, provide store hours, and help with missing or damaged deliverables. Since its introduction in 2021, the chatbot has addressed 3.2 million customer problems, saving Ikea about EUR 13 million. Good job, Billie!
2. Personalized Search
AI in e-commerce understands your customers way better than you think. They can analyze user behavior, preferences, and historical data to offer them tailored search results.
What will your customer eventually receive? It can be items similar to already viewed, personalized (absolutely unique) recommendations, and answers to queries. It feels like communicating to a consultant who knows everything at once and provides help on the first request.
3. Virtual Fitting Rooms
Online shoppers can try on items in a virtual fitting room before making a purchase. AI-powered e-commerce overlay an item on users’ photos or videos to create a general understanding of how it would fit. This way, customers can be sure they get what they want, while retailers reduce shopping returns.
The Use Case Highlight: Walmart
The US retail behemoth has upped its online shopping game with a new virtual fitting room. Shoppers could initially preview outfits on 50 diverse virtual models. Now, Walmart has leveled up, allowing customers to use their own photos for a personalized try-before-you-buy experience.
4. Conversion Rate Optimization (CRO) Testing
CRO testing is crucial if you aim to improve website performance and boost sales. This is one of the many machine learning use cases in e-commerce that can help you optimize your site based on data-driven decisions and not just a plain guess.
Everything from website design to CTA placement have their impact on your business performance, and you can explore every opportunity for improvement by using just one application of AI in e-commerce.
5. AI-Driven Voice Shopping
As stated by Statista, 19% of US millennials and 14% of those over 55 are now shopping with voice commands, primarily because it is so user-friendly.
Voice shopping weaves together retailers’ websites and shoppers’ home assistants or smartphones into one system. Such AI solutions for e-commerce use speech recognition and natural language processing to help users start purchasing by just saying a couple of phrases.
The Use Case Highlight: Carrefour
The French grocery retailer offers its customers shopping through Google voice assistant. Users can add items to shopping lists and modify them by voice, using common words (i.e., chocolate or butter) or specific product names. Then, Google Assistant converts the list into a shopping cart on the Carrefour website, where shoppers can finalize their orders, make payments, and pick a delivery option.
6. Customer Segmentation
AI solutions for e-commerce are more capable of fast (!) and detailed research than no other instrument. They analyze your clients from head to toe, including their demographics, purchase history, browsing behavior, and social media activity, to identify distinct customer segments.
AI in e-commerce can uncover patterns and similarities among customers while you’re busy with other tasks. All you have to do is to use the collected data for marketing strategies and product offerings tailored to a certain segment. It gives way to targeted messaging, customized promotions, and a more personalized shopping experience. You only need your customer data, while AI does the hard work.
7. Social Commerce
Social commerce marketing strategies have never been as advanced thanks to AI in e-commerce. Marketers traditionally use the well-known likes and shares to analyze the customer’s behavior on social media and, with that, boost traffic on the full-scale online shopping platform.
AI-powered e-commerce uses keyword research and social media data to provide a more comprehensive approach to social commerce efforts. And there is more. Algorithms can generate social media content faster than humans. In other words, you always have real-time analytics at hand and can act immediately using these insights. Guess how fast you will expand your reach and audience!
8. Image (Product) Recognition
If you use the visual power wisely, your clients will definitely notice your efforts. In many cases, product appearance is crucial for decision-making, so why not use this information as a business benefit?
With image recognition, customers can simply snap a photo or upload an image to find similar products or explore fashion trends with ease. AI use cases in e-commerce analyzes the image’s visual features and matches them with relevant products in the inventory.
Just think of all the long hours users spend looking for a perfect item. Finally, you can save this time and earn solid customer loyalty!
The Use Case Highlight: ASOS
ASOS offers a visual search tool called the Style Match feature. Customers can upload a photo from a library (or make one) of an item they’re interested in, and the platform will do the hard search work. It shows all matching or similar items available in stock by analyzing every detail from colors to patterns.
9. Price Optimization
Establishing optimal prices is easier said than done. Businesses must analyze customer behavior, market trends, competitor pricing, and inventory levels – all at once. You know the drill. But what if we tell you there is an easier way to do that?
Artificial intelligence in e-commerce can dynamically adjust prices in real-time, considering demand, seasonality, and customer segments. It hardly can be any easier, right? Algorithms can go even further and help identify pricing strategies that resonate with customers, such as personalized discounts or pricing based on individual preferences. What a magical combination of profitability and customer satisfaction!
10. AI for Security
In 2023, merchants are expected to lose 38 billion USD to e-commerce fraud. Dealing with swindling transactions causes money losses, and declining legit purchases leads to client losses. Using AI for identifying scams in e-commerce significantly reduces the chance of giving way to fraudulence.
The Use Case Highlight: Rainbow Apparel
Rainbow Apparel uses AI-powered tools to tell legit purchases from scams. As a result, the share of declined transactions reduced from 2% to 0.5% in 2 years.
11. Advanced Analytics
We’ve talked a lot about different kinds of data in this article. Is there any other way to use it? Artificial intelligence in e-commerce has more to offer.
Think of what you can get if you analyze customer behavior, purchasing patterns, and preferences with AI’s help. It can also perform cohort analysis, customer lifetime value calculations, and product recommendation systems. From now on, all of your decisions, as well as marketing strategies and user experience improvements, will be based on complex analytics collected in real time.
12. AI-Generated Content
Listing descriptions take up some space on any e-commerce site. After all, what is the other way to describe what you’re selling? But you can hardly find a more monotonous task than creating hundreds of listing descriptions one by one. Generative AI can give a hand! It creates clear and informative texts based on a product name, category, and keywords with no human involvement required.
The Use Case Highlight: eBay
The e-commerce giant introduced a ChatGPT-powered plugin to help sellers create detailed item descriptions based on the product’s title, category, and characteristics.
13. Supply Chain Optimization
Supply chain efficiency is extremely important for an online shopping experience. Skip only one tiny operation, and you risk delaying deliveries and losing a big portion of customer loyalty. Of course, there is a way to change things for the better.
Artificial intelligence in e-commerce can analyze historical sales data, market trends, and external factors to accurately predict demand. It will help you keep inventory optimized and reduce out-of-stock situations.
What else? AI for e-commerce can optimize routing and delivery schedules to minimize transportation costs. Finally, algorithms can detect anomalies, e.g., supply chain disruptions or quality issues, to help you proactively solve emerging issues.
14. Omnichannel Experience
Online retailers are getting smarter by offering multiple ecommerce platforms and offline shopping options for customers. Instead of sticking to just one shopping scenario, businesses integrate several alternatives to expand their reach.
This interconnected approach is a key part of omnichannel ecommerce strategies, which guide customers through different platforms before bringing them to the final destination. The combination of AI and e-commerce are valuable in this process, as it helps businesses create consistent marketing materials and content across all platforms. The software behind these tools is constantly improving to ensure the generated text looks and reads well, making a stronger impact on the audience.
The Use Case Highlight: IKEA
IKEA has gone further than providing an intelligent chatbot. To bring its omnichannel vision to life, the company has created a tool called Demand Sensing that understands and predicts how customers will shop across its online and in-store channels. Demand Sensing uses AI to collect and analyze data from 200 sources in real-time.
By considering shopping preferences during festivals, in-store visits, customer paydays, past buying patterns during holidays, seasonal changes, and weather forecasts, IKEA can predict local shopping behavior more accurately. The key takeaway is that using reliable data can enhance the customer experience, increase engagement, and drive sales.
15. Using AI for Review Management in E-Commerce
95% of customers read online reviews before shopping, and 58% say they are ready to pay more for products with good reviews. So, e-commerce retailers are using generative algorithms to make reviews trustworthy and easy to read.
The Use Case Highlight: Amazon
Amazon is leveraging AI to summarize customer reviews on its e-commerce platform and present one generalized opinion on every listing. Algorithms also help detect fake reviews and delete them even before publishing. Thus, in 2022, Amazon blocked 200 million suspected fake reviews.
Online shopping has become a new normal. We got used to its comfort and speed. To stay competitive, retailers need to offer something extra.
Artificial intelligence in e-commerce may sound like a buzzword, but it hides far more opportunities beyond the common use cases we mentioned. The best time to explore how AI and e-commerce tie together is now, and the best way to do it is to talk to experts in the field.
Our AI development services are powered by qualified technicians who are in love with all the latest trends available in the field of innovations. Every project we take on is an exciting journey towards success.
So let’s discuss your business needs. What are you aiming to achieve? Drop us a line to start your AI journey.
How to use ChatGPT in e-commerce?
ChatGPT can chat with customers, offer product recommendations, answer queries, and provide support throughout shopping. To implement ChatGPT effectively, you might consider a conversational AI chatbot development service for e-commerce, which ensures the chatbot is fine-tuned for your needs and customer interactions.
What is the best AI application in e-commerce?
One of the best AI applications in e-commerce is personalized product recommendations. By analyzing customer data and browsing habits, AI algorithms can suggest items that customers are more likely to purchase.
What are examples of using AI for e-commerce?
Examples include AI-driven chatbots for customer service, personalized shopping experience through machine learning algorithms, fraud detection systems for secure transactions, and AI-powered search engines that improve product discoverability. AI can also optimize logistics and supply chain management, ensuring efficient stock levels and delivery processes.
How to use AI for personalization in e-commerce?
With the help of AI personalization, you can provide unique product recommendations, tailored emails, and even customize user interface based on the client's interests and behavior.
Alex is a Data Scientist & ML Engineer with an NLP specialization. He is passionate about AI-related technologies, fond of science, and participated in many international scientific conferences.