AI Product Recommendation Engine
Boost Conversions with Personalized AI Product Recommendations
Personalize product suggestions using behavior, history, and trends
kriatix
Creator
E-commerce Solutions
Category
30
Pages
210
Downloads
English
LanguageTrusted by growing startups
See AI Product Recommendation Engine In Action
The AI Product Recommendation Engine by Kriatix delivers real-time, personalized product suggestions across your website, app, and emails. Powered by machine learning, it analyzes user behavior, purchase history, and browsing data to show each customer what they’re most likely to buy exactly when they’re ready to act.
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What Is the AI Product Recommendation Engine?
It’s a plug and play AI system that tailors product suggestions based on user interactions clicks, views, purchases, carts, wishlists, and more. It leverages collaborative filtering, content based filtering, and deep learning to generate dynamic, hyper relevant recommendations that adapt in real time.
Upload your product catalog, connect it to your website/app, and let the AI do the heavy lifting no coding required. Ideal for boosting AOV (average order value), reducing bounce rates, and driving personalized shopping journeys.
Who Is It For?
| Role | How They Benefit |
|---|---|
| E-commerce Teams | Increase conversion rates and basket size effortlessly |
| Marketing Teams | Personalize email campaigns and landing pages |
| Product Teams | Understand user behavior and optimize recommendation logic |
| UX Designers | Deliver better on-site experiences |
| Retailers | Push trending or high-margin products with precision |
Key Features
- AI powered collaborative & content-based filtering
- Works with web, mobile, and email
- Smart widgets: “Frequently Bought Together”, “You May Also Like”, “Trending Now”
- Real-time personalization engine
- Easy API and SDK integration
- No-code dashboard for managing rules and algorithms
- Auto-sync with inventory and product catalog
Benefits
- Increase average order value with smart bundling
- Reduce cart abandonment with timely suggestions
- Personalize the user journey without manual effort
- Launch faster with no-code implementation
- Adapt suggestions based on seasonality, trends, or user segments
- Improve retention with data-driven recommendations
How It Works
- Connect your product catalog and user activity feed
- Choose your recommendation logic (manual, hybrid, or AI-driven)
- Drop pre-built widgets into product pages, cart, and homepage
- The engine auto-learns from clicks, purchases, and scroll behavior
- Update logic or target segments anytime via dashboard
Add-ons & Integrations
- Shopify, WooCommerce, Magento
- Mailchimp, Klaviyo, HubSpot
- REST API for advanced custom setups
- Google Analytics integration
- Kriatix AI Content Generator (for product descriptions and emails)
Deployment & Access
- SaaS-based and cloud-native
- Mobile-first architecture
- Global language and currency support
- Optional white-label version for agencies
What Our Partners Are Saying
"Kriatix helped us launch an automated claims workflow in just 3 days saving weeks of dev time. The modules were easy to integrate and let us focus on scaling, not infrastructure."
Amara Patel
CTO at Medinova Health
"The platform transformed our customer service operations. We've reduced response times by 68% and increased satisfaction scores across the board."
Marcus Johnson
Head of Customer Experience at TechSolutions
"Implementation was smooth and the ROI was immediate. Within two months, we saw a 40% increase in conversion rates and significant cost reduction."
Sophia Chen
CEO at GreenPath Innovations
Frequently Asked Questions
How does the AI Product Recommendation Engine personalize suggestions?
The engine uses real-time behavioral data like product views, cart additions, purchase history, and search patterns combined with AI models such as collaborative and content-based filtering to generate personalized recommendations for each user.
Can I integrate this with my existing e-commerce platform or CMS?
Yes. The engine supports integration with major platforms like Shopify, WooCommerce, Magento, and custom-built sites via REST APIs and SDKs. No major code rewrites are needed.
Will it slow down my website or app performance?
Not at all. The recommendation engine is optimized for speed and performance, with lightweight JavaScript widgets and asynchronous loading to ensure seamless user experience.
Can I control or customize the recommendations manually?
Yes. While the AI handles most of the work, you can override or fine-tune logic using the dashboard for example, to boost certain products, apply seasonal logic, or create custom bundles.
Is the recommendation engine scalable for large catalogs and traffic spikes?
Absolutely. The platform is cloud-native and built to handle millions of SKUs and concurrent users without performance drops, making it ideal for scaling brands and seasonal surges.