Here’s the thing about AI: it’s smart, efficient, and takes off hours of manual labor AND it is transforming the way eCommerce brands operate.
With real-time insights and analytical data into customer preferences, AI in eCommerce is instrumental to delivering product offerings and promotions that directly affect the bottom line.
Naturally, the best eCommerce brands are riding the wave.
There are many different ways brands use artificial intelligence in eCommerce:
1. AI conversion software makes it possible to collect and analyze vast amounts of customer data, allowing brands to accurately target the right customers and deliver the right message.
2. AI-driven marketing tools help personalize the shopping experience for customers, improving product recommendations and optimizing the customer journey.
PS: Here are 20 GREAT email personalization templates for you to try.
3. Natural language processing and automated chatbots can provide customers with an easy to navigate shopping experience and address their questions quickly.
4. By leveraging AI, brands are able to create tailored and engaging content that resonates with customers and drives them to take action.
5. AI-driven order processing helps brands save time and increase efficiency, while also delivering better customer experiences.
All of these efforts are helping eCommerce brands increase their conversions and build long-lasting relationships with their customers.
13 Brilliant AI in eCommerce Examples For You To Be Inspired By
As the leading digital retailer, Amazon has been experimenting with AI for a while. From dynamic pricing to personalized search and optimized customer service, AI is an essential element for Amazon.
Perhaps one of the most creative applications of AI for Amazon has been voice-enabled search. Using machine learning and natural language processing, it understands audio cues and contextual overlays to find the right products.
The algorithm also uses deep learning to identify similar products in order to provide more accurate recommendations for users.
Fun fact: It can also differentiate between complementary terms. For example, it understands the difference between a book and a journal. Of course, this service is only enhanced the more you use it.
Sephora’s virtual try-on experience is remarkable - and has actually helped bring in a larger audience for the brand.
It's an interactive, immersive experience that uses the latest in computer vision technology to give you the space to explore their many products and see what would best suit you.
It scans and analyzes your face to determine which products would be best for your skin type, hair type, eye color and more.
3. Stitch Fix
Stitch Fix has AI built into its core: it’s a personal styling service that uses algorithms to determine product recommendations and what you should wear each week.
The service sends you a box of five items you can try on at home, and you send it back if you don't want any of the items. The company has a team of data scientists who work with product managers to find the right items for each client based on their style preferences and what they’ve been buying recently.
The product recommendations are then sent to a stylist so they can lay out the clothes within Stitch Fix’s selection. The AI engine helps stylists determine which items customers will like based on their previous purchases.
The company also uses machine learning to predict which customers will be most likely to order a new box, or who might want to skip the next box.
Hey, have you seen this? Product Recommendations: Strategies, Examples, Do's/Don'ts
As a larger part of their operations, Walmart relies on AI in eCommerce to improve its inventory management and supply chain capabilities.
Walmart's data scientists use machine learning algorithms to identify patterns in data that can be used to predict trends in product demand and inventory levels. For example, they can predict when certain types of products will become popular based on historical sales data.
The company then uses these predictions to optimize its inventory levels and shipping schedules. They also use data analytics tools to track what products are sold and optimize the route from the warehouse to the customer's home.
Keep Reading: 11 Ways to Improve Inventory Turnover Ratio in eCommerce
As a way to improve their community marketing efforts, Nike has developed an AI platform that can customize workout plans for different users based on their fitness level, age and other factors.
The system uses machine learning and artificial intelligence to analyze users' data from sensors in their shoes — like GPS trackers, accelerometers and gyroscopes — and then recommend workouts for them to complete.
The platform uses data from millions of Nike users around the world to create personalized workout routines based on their individual needs. The Nike Run Club app also uses algorithms to determine how hard someone should run or how much weight they should lift by analyzing how fast they are moving, how long they hold each position, etc.
It then adjusts these factors based on information about your body type and fitness level so that you can get the most out of your workout session without causing injury or overtraining
H&M uses AI to ensure quality control in its products. The company uses computer vision technology to scan pictures of products before shipment to ensure that they meet the standards required for delivery.
Their machine learning algorithms look out for any defects (whether that’s a tear in the material or a stain on the piece) and sort out the severity of the defects based on a series of pre-set systems. Those that have serious defects usually call for human intervention.
Described as a “friendly, easily distracted bot”, Insomnobot3000 is designed for insomniacs and people who are struggling to fall asleep. It works as a friend who keeps them company through the night, especially from 11PM to 5AM.
Casper brought in Insomnobot3000 to amplify its community marketing efforts and drive a larger emotional connect with their customers. Pretty cool idea, eh? Just as cool as its design.
It’s a classic chatbot that works on natural language processing and machine learning and responds to customers in real-time with human responses, bedtime stories, meditation and soothing exercises.
8. Function of Beauty
A hair care company that specializes in building products that are unique to each customer, Function of Beauty uses AI in every step of product customization.
When customers first sign up, they’re asked to complete a survey that understands their hair type, texture, and styling preferences. The company uses an AI-powered algorithm to analyze these responses and design a unique formula for the customer.
Once this formula is in place, the eCommerce brand runs it through a manufacturing process that can handle customization at scale with AI. They then send the product to the customer and gather secondary insight into whether the product actually suits their needs.
With this data in place, they use AI to determine customer feedback and improve their services. By understanding customer satisfaction, they’re able to refine the algorithm and improve their process of customization.
9. Dollar Shave Club
With more than 30 kinds of razors, soaps, and other shaving products, Dollar Shave Club aims to deliver a simple, hassle-free experience to an everyday essential. AI helps them do just that.
AI in their eCommerce setup has been about optimizing already existing processes, including customer service, product recommendations, and marketing. A big plus has been in predictive inventory management.
The eCommerce brand uses machine learning, artificial intelligence and big data analytics to identify trends in customer behavior as well as forecast changes in the market. For them, it’s a way to predict what customers want before they even know it.
The biggest advantage with dynamic pricing is that it attracts every customer at a price point that works for them. Here, the prices tend to vary as per supply and demand, market trends, and past customer behavior.
How do you achieve this? With AI. That’s exactly what Allbirds does.
With AI algorithms, they continually tailor prices based on the demand of the product as well as the customer’s purchase history, browsing history, clickstream data, and competitor prices. They use this data to optimize prices for different customer segments.
Customers that have been seen to be price-sensitive are targeted with discounts and offers, while other customers are more likely to receive upsell & cross-sell incentives. This helps them to offer competitive pricing and relevant incentives to customers while also meeting their bottomline.
PS: Pick the right product price: 8 eCommerce pricing best practices
11. Whole Foods
Perhaps the most common way brands use artificial intelligence in eCommerce is with chatbots. They’re easy to set up, don’t cost too much, and help improve customer experience by a mile.
Whole Foods has an excellent AI chatbot that can hold conversations and answer questions about the brand’s products and services.
The chatbot can also suggest new products that might interest you, based on what it knows about your preferences, past purchases, or your location. It also provides personalized recommendations for activities or diets that you might enjoy.
The bots are also able to answer customer service inquiries in real-time, which helps Whole Foods meet their goal of providing exceptional service while also making it easier for customers to find what they need when they want it.
With dynamic content, brands have the flexibility to alter content based on the customer’s geographical location. This helps make the content more personalized and relevant to each customer.
Skandium nails geocontent with content curated by people, enhanced by AI. Their algorithm tracks thousands of previously published posts by the locations in which they performed well to predict which content would work best for a given location.
They run content through geotags and geofencing measures to identify trends in different locations and then send targeted messages to the people who are most likely to engage with a particular content piece.
Now that you know how the best eCommerce brands are using AI, you can see why it helps them gain a competitive advantage. Not only can it help improve the customer experience, it also helps boost conversions with smarter analytics and fulfillment.
AI is helping ecommerce brands to gain a competitive edge by boosting conversions and providing better customer experiences. By leveraging AI, brands can gain real-time insights into customers’ preferences and tailor their product offerings and promotions accordingly. This can help brands gain an edge in the competitive online marketplace.