A complete guide to Magento AI product recommendations for 2025

If you're running a Magento store, you're always looking for ways to get that average order value up and turn casual browsers into loyal customers. You’ve likely spent countless hours manually setting up "related products," only to realize it's a huge time-sink that often feels like a shot in the dark. It just doesn't scale, especially when you have a big catalog.

This is exactly where AI can lend a hand, helping you create a shopping experience that feels less like a generic storefront and more like a personal consultation.

This guide will walk you through everything you need to know about Magento AI Product Recommendations. We’ll get into the tech that makes it all work, compare the different ways you can set it up, and look at a more modern approach that connects product discovery with your entire customer support setup.

What are Magento AI Product Recommendations?

So, what exactly are Magento AI Product Recommendations? Think of them as a super-smart digital salesperson working on your site 24/7. Instead of you having to manually define static rules (like always showing a specific case for a specific phone), these systems use artificial intelligence to make smart suggestions on the fly.

They watch how customers behave on your site, what they click on, what they add to their cart, and what they’ve bought before, and mix that information with your product catalog data. The result is a shopping journey that feels tailored to each person, which can seriously help with conversion rates, AOV, and just making customers feel understood. When finding products is easy, people are happier.

How Magento AI Product Recommendations work

So how does this all work? It’s not as complicated as it sounds. At its heart, a recommendation engine is looking at two main things: what it knows about your shoppers and what it knows about your products. The AI model then steps in to connect the dots.

The data that powers smart recommendations

Good AI recommendations always start with good data. It generally falls into two buckets:

• Behavioral Data: This is all about what shoppers do on your site. We're talking about which products they look at, what they add to their cart, the search terms they use, and their purchase history. This gives the AI clues about what someone is looking for.

• Catalog Data: This is everything you know about your products: name, price, brand, and any other details you have. The more detailed your product info, the better the AI can find items that are similar or go well together.

The recommendation engine: Native tools vs. third-party apps

Once the data is flowing, an AI engine gets to work making sense of it all. In the Magento world, this usually happens in one of two ways:

• The Native Way (Adobe Sensei): If your store runs on the Adobe Commerce platform, your product recommendations are powered by Adobe Sensei. It's Adobe's own AI and machine learning tech, baked right into the platform. Sensei crunches your store's data to power different recommendation types without you needing to install a separate tool.

• The Extension Way (Third-Party AI): Plenty of Magento extensions bring their own AI algorithms to the table. Some, like the Webkul extension, use a cool "embedding technique." It basically turns your product info into a string of numbers so it can find other products that are contextually similar, not just tagged the same.

The result: What your shoppers see

The whole point of this is to show different kinds of product suggestions at just the right moment. Here are some of the most common types you'll see:

• Upsells: Suggesting a slightly better, more feature-packed version of the product a customer is looking at.

• Cross-sells: Offering things that go with an item, usually on the cart page (like offering batteries for a remote control car).

• Customers Who Viewed This, Also Viewed: This is a classic, based on what other shoppers have browsed.

• Recommended for You: These are highly personalized suggestions based on an individual's own clicking and buying habits.

• Visual Similarity: Using AI to find products that just look similar. This is perfect for stores selling fashion or home goods.

• Trending Products: A real-time look at what’s popular across your entire store right now.

Choosing your path: Native vs. third-party tools

So you’re ready to get started with AI recommendations. You’ve got a couple of main roads you can go down: use the tools that come with Magento or integrate a third-party extension. Each route has its own set of pros and cons.

Magento Open Source: The manual approach

If you're using Magento Open Source, your built-in options are pretty basic. You can manually assign related products, upsells, and cross-sells to every single item in your catalog.

• The good: It's free and already there.

• The bad: It’s a ton of manual work, there's no AI involved, it's not personalized, and it's basically impossible to manage if you have more than a handful of products.

Adobe Commerce: The native approach with Adobe Sensei

For those on the premium Adobe Commerce platform, you get AI-powered recommendations right out of the box with Adobe Sensei.

• The good: It's built right into the Magento admin, uses a pretty sophisticated AI, and gives you a lot of different recommendation types to play with.

• The bad: You have to be on the pricey Adobe Commerce plan to get it. It can also be a bit of a beast to configure correctly, and it keeps you tied to the Adobe ecosystem. You won't have the same flexibility you might get with a dedicated third-party tool.

Third-party extensions: The flexible approach

There's a whole world of third-party extensions out there that can help. Companies like Nosto, Searchspring, Klevu, and Webkul all offer powerful recommendation engines that plug right into Magento.

• The good: You have a lot of options to choose from, often with more niche features or easier-to-use dashboards. Some can also be much friendlier on the wallet than a full Adobe Commerce license.

• The bad: Getting them to play nicely with your other extensions can sometimes be a headache. The quality of the tool and the support you get can vary, and your data is often being processed on someone else's servers, which might be a concern for some.

Feature	Adobe Commerce (Native AI)	Third-Party Extensions
Recommendation Logic	Powered by Adobe Sensei (AI/ML)	Varies by provider (AI, rule-based, or a mix)
Setup & Configuration	Integrated, but can be technically tricky	Varies; some are plug-and-play, others need a developer
Personalization	Strong, real-time personalization	Often very powerful and sometimes more customizable
Cost	Part of the high-cost Adobe Commerce license	Ranges from a one-time fee to pricey monthly subscriptions
Flexibility	Limited to what Adobe offers	High; you can pick the perfect tool for your needs
Best For	Big companies already bought into the Adobe world	Stores of any size looking for choice, flexibility, or specific features

Common challenges with AI product recommendations and a smarter alternative

Product recommendation engines are a fantastic start, but they do have a blind spot. They’re amazing at showing products, but they don't see the whole picture of what a customer might need help with.

Frustrations with siloed recommendation tools

• They only know about products: A recommendation engine knows your product catalog inside and out. But it has zero clue about your help center articles, return policy, or past support tickets. That means it can't help with simple questions like, "Do you ship to Canada?" or "Will this fit a Model X?"

• They can't have a conversation: These tools are passive. They can show you a product, but they can't understand a customer's problem or offer help. They wait to be acted upon, which means they can't stop a support ticket from being created or answer a pre-sales question.

• Setup can be slow and complicated: Getting tools like Adobe Sensei or other enterprise-level systems running smoothly can take a lot of developer time and a long onboarding process.

A unified way forward with eesel AI

This is why thinking beyond just product recommendations is so important. Instead of a tool that only does one thing, what if you had something that could handle product discovery and customer support? That’s the idea behind a platform like eesel AI.

While eesel isn't a traditional Magento recommendation extension, it offers something that can be far more valuable: an AI Chatbot built for e-commerce.

Here’s how it creates a much better experience for everyone:

• It knows more than just your products: The eesel AI chatbot can connect to your e-commerce platform (like Shopify or Magento through a custom setup) and all your other knowledge sources at the same time. Think of your help desk, your internal wikis in Confluence, and even your team's Google Docs. It can recommend the perfect product and answer a question about your warranty in the same chat.

• Get it live in minutes, not months: Forget about those long, drawn-out setups. With eesel AI, you can connect your knowledge sources with a few clicks and have a smart AI chatbot on your site in minutes. It's a completely self-serve platform, so you don't have to sit through a mandatory sales call just to try it out.

• It's a complete support platform: The same AI that runs your chatbot can also work as an AI Agent to automate replies to support tickets, or as an AI Copilot to help your human agents work faster. It’s one solution for the entire customer journey, not just a small piece of it.

This infographic shows how eesel AI connects various knowledge sources, going beyond simple product catalogs to provide comprehensive customer support, a key benefit over traditional Magento AI Product Recommendations.

Pricing for AI product recommendations

Pricing for Magento AI Product Recommendations is all over the map. Big platforms like Nosto and Searchspring usually want you to book a call for a custom quote. Extensions on the Magento marketplace are more straightforward. For example, the Webkul AI Product Recommendation extension is a one-time purchase of $249 for the Open Source version.

eesel AI, on the other hand, keeps its pricing transparent and simple, without any weird per-ticket fees.

A screenshot of the transparent eesel AI pricing page, which simplifies the cost considerations for implementing advanced AI beyond just Magento AI Product Recommendations.

Plan	Price (Billed Annually)	AI Interactions/mo	Key Features
Team	$239/mo	Up to 1,000	Train on website/docs; Copilot; Slack integration.
Business	$639/mo	Up to 3,000	Everything in Team + train on past tickets; AI Actions; bulk simulation.
Custom	Contact Sales	Unlimited	Advanced actions; custom integrations; multi-agent orchestration.

Wrapping up on Magento AI Product Recommendations

Using Magento AI Product Recommendations is a solid way to make your store a better place to shop and, hopefully, boost your revenue. You can stick with the native AI in Adobe Commerce if you're on that platform, or pick from dozens of third-party extensions to find the one that fits your budget and needs.

But the future of e-commerce is about more than just showing people the right product. It's about giving them the right answer, right when they need it. Standard recommendation tools are stuck in their own little world. By moving to a unified AI platform that connects your products with all of your support knowledge, you can go beyond basic suggestions and create smart, conversational experiences that build sales and loyalty at the same time.

Ready to see how a unified AI can change the game for your store?

Connect your knowledge sources and launch an AI chatbot in minutes with eesel AI. Start your free trial today.