Online shoppers are surrounded by product choices. When an ecommerce store has hundreds or thousands of products, customers may struggle to find the items that actually fit their needs.
AI can make product discovery more relevant by analyzing browsing behavior, purchase history, cart activity, product information, and other signals. Modern AI product recommendations can then suggest products that are more likely to interest each shopper.
For merchants, this can also create opportunities for cross-selling and upselling without requiring employees to manually create recommendations for every customer.
What Are AI Product Recommendations?
AI product recommendations use machine learning and other AI techniques to identify products a customer may be interested in.
Instead of showing the same recommendations to every visitor, an AI system can consider signals such as:
- Products previously viewed
- Purchase history
- Current cart contents
- Search behavior
- Similar customers’ purchases
- Product attributes
- Real-time browsing activity
The system can then recommend products at different points in the shopping journey.
Common placements include product pages, shopping carts, checkout experiences, homepages, email campaigns, and post-purchase messages.
How AI Helps With Upselling and Cross-Selling
AI can support two important ecommerce strategies.
Upselling encourages a customer to choose a higher-value version of a product.
For example:
Basic Laptop → AI Suggests Higher-Spec Model
Cross-selling recommends complementary products.
For example:
Running Shoes → Recommend Running Socks + Sports Shorts
AI can determine which products are more relevant based on customer behavior and product relationships instead of relying entirely on manually created rules.
This can help increase average order value while making recommendations more useful to shoppers.
Best AI Upselling Tools
Klaviyo
Klaviyo combines customer data, ecommerce marketing, and AI-powered recommendations. Its recommendation features can use browsing history, purchases, product catalogs, and customer profiles to suggest relevant products across channels such as email and SMS.
Best for: Personalized ecommerce marketing and post-purchase recommendations.
Nosto
Nosto focuses on ecommerce personalization, including product recommendations, search, merchandising, and personalized shopping experiences.
Best for: Growing stores that need broader onsite personalization.
Shopify Search & Discovery
Shopify’s Search & Discovery app can provide related and complementary product recommendations. Merchants can also customize recommendations for individual products.
Best for: Shopify merchants looking for a native recommendation solution.
Rebuy
Rebuy is designed around ecommerce upselling, cross-selling, bundles, and personalized offers.
Best for: Shopify stores focused on increasing average order value.
LimeSpot
LimeSpot provides personalized product recommendations and merchandising capabilities that can be used across different parts of an ecommerce store.
Best for: Stores looking for onsite personalization and product discovery.
The Shopify App Store also contains a large ecosystem of AI-powered upsell, cross-sell, and recommendation applications, ranging from simple offer widgets to AI shopping assistants.
How E-commerce AI Personalizes Recommendations
A typical workflow looks like:
Customer Visits Store → AI Collects Signals → AI Predicts Intent → Products Ranked → Recommendation Displayed → Customer Responds
For example, a returning customer might browse several running products. AI can combine that behavior with previous purchases and recommend complementary products or a higher-value alternative.
The recommendations can change as the customer’s behavior changes.
This is an important difference between AI personalization and traditional static recommendations. AI systems can continuously use new behavioral information rather than relying exclusively on manually written rules.
Where to Use AI Recommendations
Product Pages
Show similar, complementary, or frequently purchased products while the customer is already considering an item.
Cart Pages
Recommend products that complement the current cart.
For example:
Camera → Memory Card → Extra Battery → Camera Bag
Checkout
Offer carefully selected add-ons that make sense for the customer’s purchase.
Send personalized recommendations after purchases or based on browsing behavior.
Post-Purchase
AI can predict the customer’s next likely purchase and recommend related products at an appropriate time. Klaviyo, for example, supports personalized product recommendations in customer-facing experiences and messaging.
How to Implement AI Upselling
Start with one high-intent location rather than personalizing the entire store immediately.
- Connect your product catalog.
- Make sure product information is accurate.
- Connect available customer behavior data.
- Choose one recommendation placement.
- Define products that should never be recommended.
- Launch the recommendation workflow.
- Track clicks, conversions, and average order value.
- Improve the recommendations based on results.
Shopify recommends starting small and measuring metrics such as click-through rate, conversion rate, and average order value.
Common Problems With Ecommerce AI
AI recommendations are only as good as the product and customer data behind them.
Poor product descriptions, incorrect categories, outdated inventory, and incomplete catalogs can produce irrelevant recommendations.
Another problem is excessive upselling. Showing too many offers can make the shopping experience feel aggressive rather than helpful.
Stores should also prevent AI from recommending unavailable products or products that customers have already purchased when that recommendation would not make sense. Modern recommendation systems provide controls for excluding products and categories.
ADVANCED INSIGHTS
The strongest e-commerce AI systems are moving beyond simple recommendation widgets toward real-time shopping assistants.
A more advanced workflow is:
Customer Data → AI Understands Intent → AI Selects Next-Best Product → Personalized Offer → Purchase → AI Updates Customer Profile
AI shopping assistants can also interact directly with customers, answer product questions, compare options, and recommend products through conversational interfaces.
This creates a more dynamic experience where recommendations are based not only on what someone bought previously, but also on what they appear to want right now.
Final Thoughts
AI product recommendations can help online stores make product discovery easier while creating new opportunities for cross-selling and upselling.
Klaviyo is strong for customer-data-driven recommendations and marketing, Shopify Search & Discovery is a practical option for Shopify merchants, while platforms such as Nosto, Rebuy, and LimeSpot offer broader personalization and upselling capabilities.
The best AI upselling tools should make recommendations more relevant—not simply show customers more products.
Start with one high-intent placement, measure the results, and gradually expand personalization across your store.
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