Published
May 30, 2025
Discover how modern product recommendation engines drive personalization, increase AOV and boost conversions.
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Meet the authors
Recommender System
AI Commerce Search
Article
Recommender system
Published
05
/
30
/
2025
Discover how modern product recommendation engines drive personalization, increase AOV and boost conversions.
Imagine a shopper entering your online store and feeling like the entire experience was crafted just for them.
With the expansion of AI and machine learning, personalized product recommendations have become the go-to tool for businesses that want to boost customer engagement and drive more revenue.
Recent studies show that:
This article will explore how AI-driven recommendation engines transform retail. We'll explore the top 5 product recommendation engines, so you can choose the right fit for your business. We'll also touch on how these tools support upselling, cross-selling and smarter personalization.
Think of a product recommendation engine as your top-performing salesperson.
A recommendation system analyzes customer data and behavior to show products your visitors will most likely love and buy.
Product recommendation systems ingest behavioral data: clicks, carts, conversions, wish lists and even dwell time. Then, they find patterns, e.g., “People who bought noise-canceling headphones also tend to buy these ergonomic chairs”.
Modern engines typically use:
These engines follow the customer journey. Recommendations are:
Not all suggestions work equally well. Here are some high performers:
When done right, recommendation engines improve user experience and quietly grow revenue, one “You might also like…” at a time.
Showing everyone the same ten “best-selling” products doesn’t cut it anymore.
Traditional product recommendation engines are easy to implement, but they lack context. They treat all users equally, ignoring intent, timing and individual preferences. The result? Missed opportunities, irrelevant suggestions and bounces.
Modern hybrid recommendation systems use content-based, context-aware data filtering systems to understand purchase history and user behavior. Here's what we mean:
Whether you're optimizing for conversions, customer retention or want a better user experience, choosing the right recommendation engine is essential. Here are five that commerce teams trust.
Enterprise businesses need more than a plug-and-play customer data widget. You need an entire system that understands, adapts to and acts on customer behavior in real time, delivering personalized experiences without bogging down.
Enter: Loadstone.
Built by e-commerce professionals with 12+ years of expertise, it's a holistic, composable martech ecosystem that combines advanced AI, personalization and omnichannel strategies under one platform.
It's ideal for large-scale retailers, multichannel commerce brands and enterprises managing many high-traffic customer segments and multi-platform experiences.
There's a reason why our customers stay with us for an average of 6+ years: our software adapts to your needs, handling millions of users and infinite possibilities.
The Loadstone product we’re focusing on today is the AI Recommender System that delivers personalized shopping experiences across digital and physical retail environments.
It uses over 35 advanced algorithms to analyze user behavior, preferences and contextual data, enabling precise product suggestions that drive engagement and sales. Here are some of its key features:
Loadstone AI Commerce Search can double or even triple your conversion rates with to its modular, composable architecture. It consists of interchangeable components—recommendation engine, audience segmentation, real-time messaging and product bundling—that you can activate individually or integrate. For example, get the Loadstone loyalty campaign module alongside your existing CRM; then plug in its promotional marketing for dynamic targeting.
💡Curious how Loadstone fits into your tech stack? Talk to our expert or get a quote.
Loadstone's open API architecture gives you freedom. Whether you're using Salesforce Commerce Cloud or Shopify Plus, Loadstone can connect to it so you can:
Considering a switch from Salesforce? Check out our breakdown of the top Salesforce competitors and how they compare in features, flexibility, and pricing.
Dynamic Yield is an AI-powered personalization platform designed for large retailers. The tool helps create tailored experiences across every digital touchpoint.
It's best for omnichannel retailers and enterprise brands looking for personalization and experimentation across web, mobile apps, email and kiosks.
Dynamic Yield offers integrations and flexible APIs. You can connect it to:
Algolia Recommend is an AI-driven product discovery platform. It has a developer-friendly ecosystem that provides a recommendation engine.
It's best for commerce teams and developers looking to build customized recommendation strategies and experiences within a modern headless or composable architecture.
Algolia Recommend is modular; it can work in a composable or headless environment:
Not sure whether you need a CDP or a CRM? Our guide breaks down the key differences between CDP vs. CRM to help you choose the right tool for your business.
Nosto is a commerce experience platform that helps retailers deliver personalized shopping journeys. It combines real-time data, AI and merchandising tools into one cohesive system. It's best for mid-sized to large commerce brands.
Nosto is built for commerce, so it works with multiple e-commerce platforms and marketing tools:
Klevu combines AI-powered search, product discovery and personalized recommendations in a commerce-optimized platform.
It's built for e-commerce and is best for retailers who want to turn every search and navigation interaction into a personalized product discovery opportunity.
Klevu is designed for commerce-first integration. It supports major platforms and has flexible APIs for custom setups:
A product recommender system is more than an upsell tool. It's a driver of revenue and customer loyalty.
As shopper expectations rise and digital journeys become more complex, you need a solution beyond generic suggestions—one that understands user data, intent, adapts in real time and scales with you.
Choosing the right platform depends on your brand's needs: the level of personalization you want and the flexibility you need. Pick a tool that fits not just your stack, but your strategy.
For enterprise retailers operating at scale, Loadstone delivers measurable impact. Its intelligent product recommendation engine drives higher conversions, larger basket sizes and stronger customer loyalty. Moreover, its composable architecture ensures integration across channels and systems, adapting as your business evolves.
Explore what Loadstone can do for your team, talk to our expert and get a quote today.
It’s a system that suggests relevant products to users based on their behavior, preferences or context. It helps businesses personalize the shopping experience and increase conversions.
Loadstone is a powerful example. Enterprise retailers use it to deliver real-time, AI-driven product suggestions across web, mobile, email and even in-store experiences.
It analyzes data like browsing history, purchase behavior and contextual signals using AI and machine learning to suggest products that are most likely to convert. Loadstone’s engine goes further by integrating into the full customer journey.
For enterprise retailers seeking excellent performance, flexibility and deep personalization, Loadstone stands out with its composable architecture and intelligent, customizable recommendation capabilities.
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e-commerce expert
Meet the authors
Serge Seregin
VP of Recommendations
Meet Sergey Seregin, VP of Personalization and AI, a visionary leader driving customer-centric innovation and value creation through AI-powered personalization, with a distinguished 20-year career marked by exceptional results and a passion for delivering tailored customer experiences.
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