Personalization is no longer a nice feature. Customers expect it every time they shop online. According to McKinsey, 71% of consumers expect companies to deliver personalized interactions. 76% get frustrated when they do not receive them.
People want to see products that match their interests. If they cannot find what they need, they often leave the store without buying anything.
This is where AI can help. Adobe Commerce Product Recommendations uses Adobe Sensei to study customer behavior. It then suggests products that each shopper is more likely to buy. Businesses that invest in Adobe Commerce development can take full advantage of AI-powered capabilities.
Adobe’s 2026 AI and Digital Trends report found that nearly half of customers (49%) would use AI to get personalized product recommendations. This shows the growing demand for AI-powered shopping experiences.
These recommendations help customers discover new products. They also make cross-selling and upselling feel natural. As a result, businesses can increase sales while giving customers a better shopping experience.
In this blog, you’ll learn how Adobe Commerce Product Recommendations work, why they matter, and how they can help grow your online store.
How Do AI Product Recommendation Engines Work?
Have you ever seen sections like “You May Also Like” or “Customers Also Bought” while shopping online? Those suggestions are created by a product recommendation engine.
The system watches how people use your store. It looks at the products they view, search for, add to the cart, and buy. It then finds patterns and recommends products that are most relevant to each shopper.
Adobe Commerce Product Recommendations uses Adobe Sensei to do this automatically. The more people shop, the more data it collects. Over time, the recommendations become smarter and more accurate.
The AI can use data such as:
- Products viewed
- Search history
- Purchase history
- Cart activity
- Wishlist activity
- Popular products
- Similar products
Instead of showing the same products to everyone, your store gives each customer a more personal shopping experience.
AI recommends products based on each customer’s shopping behavior.
How Do AI Product Recommendation Engines Work?
Many online stores recommend products. The difference is how those recommendations are created.
Basic recommendation tools use fixed rules. For example, they may show products from the same category or brand. These suggestions stay the same unless someone updates them.
Adobe Commerce Product Recommendations works differently. It uses AI to study customer behavior in real time. It learns what shoppers like and updates recommendations automatically.
This means customers see products that match their interests instead of generic suggestions.
Adobe Commerce Product Recommendations helps you:
- Personalize every shopping experience
- Increase product discovery
- Improve cross-selling
- Improve upselling
- Reduce manual work
- Increase conversions
The result is a better shopping experience for your customers. It also gives your business more chances to increase sales.
AI recommendations increase sales and improve customer shopping experiences.
How Does Adobe Commerce Product Recommendations Work?
Adobe Commerce Product Recommendations is a cloud-based service. It works with your Adobe Commerce store to suggest products automatically.
Once you enable the feature, it starts collecting shopping data. It looks at what customers search for, what they view, and what they buy. Adobe Sensei then uses this information to find products that each shopper is likely to purchase.
The AI keeps learning as more people visit your store. This helps improve recommendations over time without extra effort from your team.
You can show recommendations across your website. They can appear on product pages, category pages, the shopping cart, and other key pages.
Adobe Commerce can recommend products based on:
- Customer browsing history
- Purchase history
- Popular products
- Similar products
- Frequently bought together items
- Recently viewed products
The entire process runs automatically. This saves time and gives customers a more personal shopping experience.
Adobe Sensei analyzes customer data for smarter product recommendations.
How Do You Set Up Adobe Commerce Product Recommendations?
Getting started is simple. Adobe Commerce guides you through the setup process. Once everything is connected, the AI begins collecting data from your store. A well-planned Adobe commerce implementation helps ensure these features are configured correctly from the start.
As customers continue to shop, the AI learns from their activity. The recommendations become more accurate with time.
The setup process includes:
- Enable Product Recommendations
- Connect Adobe services
- Sync your product catalog
- Choose recommendation types
- Select where recommendations appear
- Review performance reports
After setup, the system works in the background. It keeps improving recommendations while your team focuses on growing the business.
Final Thoughts
Customers expect every shopping experience to feel personal. They want to find the right products quickly. When they do, they are more likely to complete their purchase.
Adobe Commerce Product Recommendations helps you deliver that experience. It uses AI to suggest products that match each shopper’s interests. The recommendations improve as more customer data becomes available.
Better recommendations help customers discover more products. They also increase cross-selling and upselling opportunities. This can lead to higher sales and better customer satisfaction. As part of a broader eCommerce strategy, AI-powered recommendations can help businesses create more personalized shopping experiences.
If you want to make shopping more personal, Adobe Commerce Product Recommendations is a smart investment.
Need help getting started? Ziffity’s Adobe Commerce experts can help you set up, customize, and optimize Product Recommendations. We’ll help you create a better shopping experience that drives more sales.
