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Google Vertex AI Product Recommendations for Magento 2
Elevate Conversions with Google Vertex AI Personalized Product Recommendations.
Integrate Google’s Vertex AI Product Search seamlessly with your Magento 2 store. Utilize advanced machine learning to deliver precise, personalized product recommendations that enhance user experience, improve discovery, and increase sales performance across your storefront.
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graphQL Compatible
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Hyvä Compatible
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REST API Compatible
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B2B Compatible
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Innovative
- Magento Version Compatibility
- Magento Open Source: 2.4.0.x - 2.4.9.x
- Adobe Commerce (EE): 2.4.0.x - 2.4.9.x
- Adobe Commerce Cloud (ECE): 2.4.0.x - 2.4.9.x
Hyvä is now open-source and free. All MageDelight extensions are already fully Hyvä-ready at zero extra cost to adapt a blazing-fast Hyvä experience with full confidence. to raise a free compatibility request for Hyvä Checkout or Mage-OS.
Your Magento Edition
$399
- Update and support prolongation -
$269
Pay $399 Now for the first year.
Next year onwards $269 per year to receive updates and support.
You can cancel anytime.
- No Auto-debit setup
- Transparent Policy & No Hidden Fees
- Lifetime Access to Original Source Code
- 1 Year Access to Free Technical Support
- 1 Year Access to Free Compatibility and Feature Updates
- 30 Day Money Back*
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Feature Highlights
Overview & Descriptions
FAQs
Technical Specifications
Release Notes (Changelogs)
What User Speaks (2)
Ask us your query
Feature Highlights
- Instant Personalization for Max Conversions
- Strategic Revenue Diversification
- No-Code Front-End Placement Control
- Zero Performance Impact on Store Speed
- Automated Catalog & Event Tracking
- Support for AI-Driven Strategy & Page-Level Optimization
- Effective Customer Retention Engine
- Rich Product Attribute Utilization for High-Accuracy Content-Based Recommendations
- Seamless Magento Admin Integration
- Secure & Scalable Google Infrastructure for Enterprise-Grade Reliability
Overview & Descriptions
This solution brings the capabilities of Google's enterprise-grade machine learning directly into the Magento 2 ecosystem. For growth-oriented agencies and merchants, personalization has become a core competitive advantage rather than an added feature. This extension bridges Magento and Vertex AI, simplifying complex integration processes and enabling immediate access to intelligent, data-driven product suggestions. By continuously analyzing both real-time customer actions and historical behavior, it predicts what each shopper is most likely to purchase, ensuring every interaction contributes to higher engagement and conversion.
The primary business advantage lies in its ability to recreate the contextual relevance of an in-store sales associate at scale. Whether a customer lands on your homepage, browses a category, or proceeds to checkout, the Vertex AI engine automatically selects and displays the most appropriate recommendation type. Examples include "Recommended for you" on the homepage or "Frequently bought together" during checkout. This precision-based approach minimizes choice fatigue, increases average order value (AOV), and improves essential KPIs such as click-through rates and overall revenue.
The extension is also designed with operational efficiency in mind. It automates the entire product recommendation process, removing the need for manual curation or merchandising updates. The AI models continuously adapt to changing customer behavior and new product introductions without requiring configuration changes or developer involvement. This frees your team to focus on strategy and insights rather than repetitive management tasks.
Implementing this Vertex AI integration is a forward-looking investment in personalization and scalability. It equips your Magento 2 store with the intelligence and adaptability of leading global retailers, delivering a seamless, predictive shopping experience that nurtures loyalty and accelerates business growth.
This Magento 2 extension provides everything required to integrate and manage Google Vertex AI Product Search recommendation models across your online store. At its foundation is a robust synchronization system that ensures your complete product catalog and user event data-such as views, clicks, and purchases- all accurately transmitted to Vertex AI. This continuous synchronization maintains data accuracy and allows the AI models to deliver precise, real-time recommendations.
Merchants gain access to multiple AI-driven recommendation types optimized for different stages of the buying journey. "Recommended for you" panels engage visitors on home and category pages, "Similar items" and "Others you may like" enhance discovery on product detail pages, and "Frequently bought together" suggestions increase order values during cart interactions. Additionally, a "Buy it again" model supports repeat purchase strategies based on past behavior.
The extension includes an intuitive configuration interface that allows non-technical users to control where recommendation panels appear and which models power them. This flexibility supports experimentation through A/B testing and performance optimization. The integration also supports the "Page-level optimization" model, which dynamically arranges multiple recommendation types on a single page to maximize overall engagement and conversion efficiency.
Performance has been prioritized throughout the design. All machine learning computations occur on Google Cloud's high-speed infrastructure, while Magento only processes lightweight API calls to retrieve personalized product IDs. This architecture ensures fast load times and an uninterrupted customer experience, both essential for maintaining SEO rankings and conversion rates.
Vertex AI Product Recommendation Models
The following table details the specific AI models available through the extension, showing where and how each one delivers maximum impact across your e-commerce storefront.
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Model Type |
Description |
Typical Usage Location(s) |
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Recommended for you |
Predicts the next product a user is most likely to engage with or purchase, based on their individual shopping and viewing history. |
Homepage, Category Pages, or where general personalized discovery is needed. |
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Others you may like |
Predicts the next item a user is most likely to engage with, based on their history and its relevance to a currently specified catalog item (e.g., the product they are viewing). |
Product Detail Pages (PDP) to encourage further browsing or an initial purchase. |
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Frequently bought together |
Predicts items commonly purchased alongside one or more specific catalog items within the same shopping session. |
After an Add-to-Cart event, on the Product Detail Page (PDP), or on the Shopping Cart Page to increase AOV. |
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Similar items |
Predicts other catalog items that share the most similar attributes (color, material, category, brand, etc.) to the current item being considered. |
Product Detail Page (PDP) for alternatives, or when an item being viewed is out of stock. |
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Buy it again |
Predicts items a user is likely to repurchase, based on their historical purchase patterns and recency. |
Detail Page View, Home Page View, Shopping Cart, or Category Page for re-engagement. |
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Page-level optimization |
Automatically optimizes the entire page by intelligently selecting and arranging multiple recommendation panels for maximum engagement. |
Detail Page View, Add to Cart, Shopping Cart, Category Page View, and Home Page View. |
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On sale |
Recommends products that are currently discounted or part of a sale promotion. |
Home Page View, Add to Cart, Shopping Cart, Category Page View, and Detail Page View to drive urgency. |
Vertex AI Model Minimum Data Prerequisites
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Model Type |
Primary User Event Required |
Minimum Data Requirement (for training) |
Additional Context |
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Similar items |
None (Content-based) |
Product Catalog Data (Minimum of 100 product SKUs with rich attributes). |
This model relies on product features (description, category, attributes) for similarity, not user behavior. |
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Recommended for you |
detail-page-view, add-to-cart |
At least 60 days of relevant user events (views or adds-to-cart) in the last 90 days, and 10,000+ total events. |
The specific event type required depends on the selected optimization objective (e.g., Click-Through Rate requires detail-page-view events). |
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Others you may like |
detail-page-view, add-to-cart |
Similar to 'Recommended for you', requiring 60 days of relevant user events and 10,000+ total events for the chosen objective. |
This model needs user events and the current item context (the product being viewed) for its predictions. |
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On sale |
detail-page-view, add-to-cart |
Requires a minimum of 60 days of relevant events (views or adds-to-cart) in the last 90 days, and that product pricing data is consistently updated. |
Relies on user behavior data to determine which on-sale items are most engaging/converting. |
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Frequently bought together |
purchase-complete |
At least 90 days of purchase-complete events in the last year, and 1,000+ total purchase events. |
This model needs transactional history to find co-occurrence patterns. A longer history (1-2 years) is often recommended for best results. |
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Buy it again |
purchase-complete |
Requires a history of purchase-complete events tied to the user's ID to learn repurchase patterns. |
Focuses purely on an individual user's purchase history for repeat transactions. |
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Page-level optimization |
detail-page-view, add-to-cart, home-page-view |
Prerequisites are met if the minimum data for the underlying individual models (like Recommended for you and Others you may like) it uses are met. |
This is a meta-model that orchestrates multiple recommendation types on a single page. |
Key Data Requirements Summary
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Product Catalog: Must be complete, high-quality, and constantly synchronized (ideally daily) to avoid recommending out-of-stock or stale items. Required fields include ID, Name/Title, and Categories. Providing rich attributes (size, color, material, description) significantly improves the Similar Items model.
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User Event Types: You must track and send the following events for optimal model training:
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detail-page-view (Product page views)
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add-to-cart
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purchase-complete (Transactions)
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Real-Time Data: While historical data is used for training, providing real-time user events ensures the models can instantly use the customer's current session activity for the most accurate, immediate personalization.
Benefits
- Higher Average Order Value: Automated complementary suggestions encourage larger basket sizes.
- Improved Conversions: Personalized, relevant recommendations drive engagement and sales.
- Reduced Manual Effort: Eliminates the need for constant merchandising updates.
- Better Product Visibility: Ensures a balanced exposure between popular and long-tail items.
- Customer Retention: Personalized experiences enhance satisfaction and encourage repeat purchases.
- Enterprise Scalability: Leverages Google Cloud’s infrastructure to support growth and high traffic volumes.
Feature For Customers
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Faster Product Discovery: Helps customers find what they need quickly with intelligent, context-aware recommendations.
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Personalized Experience: Delivers content tailored to each shopper’s preferences and behavior.
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Relevant Alternatives: Displays suitable substitutes when products are unavailable or out of stock.
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Smart Bundling: Encourages additional purchases through “Frequently bought together” suggestions.
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Streamlined Checkout: Reduces friction and shortens the path to purchase.
Supported AI Integration Platform
Google Vertex AI Search for commerce
This extension integrates Magento 2 with Google Vertex AI Search for Commerce, a third-party AI service provided by Google Cloud.
Visit: https://cloud.google.com/solutions/vertex-ai-search-commerce
- This Magento 2 extension depends on Google Vertex AI Search for Commerce and requires a separate active Google Cloud account with billing enabled.
- All Google Cloud costs (AI training, API usage, storage, inference) are billed directly by Google and are not included in the extension price.
- AI model training is mandatory to use this extension; a standard training script is provided with the purchase.
- Complimentary AI model training assistance is limited to 15 calendar days and applies only to the provided custom script and standard Magento catalog structure.
- Any bespoke AI model tuning, custom data structures, ranking logic, or advanced training is out of scope and offered as paid professional services.
- The customer is solely responsible for Google Cloud project setup, permissions, quotas, and compliance with Google’s terms.
- Search relevance, performance, and AI results depend on product data quality and Google’s AI algorithms and are not guaranteed.
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Your Question
Technical Specifications
Dev Environment Required: Click Here
- Magento OS: 2.4.8-p3 and above (or latest)
- Adobe Commerce: 2.4.8-p3 and above (or latest)
- Adobe Commerce Cloud: 2.4.8-p3 and above (or latest)
- JavaScript must be enabled in browsers.
- Supported Browsers: Click Here
- PHP Compatibility: Click Here
- Required extensions: Click Here
- Safe_mode off.
- Memory_limit no less than 4Gb (preferably 8GB).
- Max Execution time no less than 90 seconds.
Operating System:
- Magento recommends to use Linux operating system for development. It may have few problems with windows/other operating system.
Dev & Test Environment:
MageDelight has below development environment.
- Standard Vanilla Magento (Open Source) version 2.4.8-p3 and above & up to latest version
- Standard Vanilla Adobe Commerce version 2.4.8-p3 and above up to latest version
- Standard Vanilla Adobe Commerce (Cloud) version 2.4.8-p3 and above up to latest version
- Theme: Magento Luma (Default)
Magento Compatibility:
- We provide 100% compatibility with standard/vanilla Magento with supported editions and versions
3rd Party Compatibility:
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You may need some minor fixes to work with other 3rd party themes and extensions.
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We do not guarantee that the extension will function with other third-party themes or extensions because we have not tested it with your third-party themes or extensions, so if you require some minor code compatibility with your third-party themes or extensions, please contact us. We will surely assist in resolving issues caused by code conflicts if it requires less efforts (up to two hours). If it will need a significant amount of time and effort (more than four hours of development), it will be evaluated for paid development support. Third-party modules or themes are those that are not produced or given by Magento/Adobe and are sold by other vendors/developers.
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On-Demand Custom Features Development
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The features mentioned on the description comes as standard extension features. Apart from this if any of the features you require for your business requirements will be considered as bespoke development and it will be considered as additional development on top of extension features.
Note:
This extension does not provide AI search functionality; it uses Google Vertext Search services to provide Product Recommandations for eCommerce.
Release Notes & Changelogs
Version number:
1.2.3
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Feature Enhancement
- Stability: Stable
- Compatibility: Magento Community-2.4.0, Magento Enterprise-2.4.0, Magento Community-2.4.9, Magento Enterprise-2.4.9
- Added support for Magento 2.4.9 and PHP 8.4, ensuring seamless compatibility with the latest Magento platform and improved overall stability.
Version number:
1.2.2
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Bug Fixes
- Stability: Stable
- Compatibility: Magento Community-2.4, Magento Enterprise-2.4
- Resolved an issue affecting the successful export of products to Google Vertex AI, improving integration reliability.
- Resolved a bug in the search functionality that resulted in empty API responses.
Version number:
1.2.0
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Feature Enhancement with Bug Fixes
- Stability: Stable
- Compatibility: Magento Community-2.3, Magento Enterprise-2.3, Magento Community-2.4, Magento Enterprise-2.4
- Performed minor bug fixes and ensured compatibility with PHP 8.4 for improved stability and performance.
- Added Event Sync Log functionality with a dedicated admin grid, enabling store owners to monitor real-time event synchronization. Introduced cron configuration for automated log cleanup, along with options to manually clear and refresh logs. The grid also supports filtering for real-time and sample data events.
- Introduced Model Overview functionality, allowing store owners to view recommendation model status directly from the Magento Admin panel without accessing the Google Cloud Console. Added cron configuration for automated model status synchronization, along with a manual refresh option.
Version number:
1.1.0
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Feature Enhancements And Bug Fixes
- Stability: Stable
- Compatibility: Magento Community-2.3, Magento Enterprise-2.3, Magento Community-2.4, Magento Enterprise-2.4
Feature Enhancements
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Improved overall code quality and module structure.
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Enhanced existing REST APIs for better performance and reliability.
New Features
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Added GraphQL APIs to support extended integrations.
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Introduced a separate Sample Data Module for managing data synchronization and console commands.
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Implemented real-time user events:
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shopping-cart-page-view -
remove-from-cart
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Bug Fixes
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Fixed issues to improve overall module stability and functionality.
Version number:
1.0.0
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Initial Release
- Stability: Stable
- Compatibility: Magento Community-2.4, Magento Enterprise-2.4
- Initiate Release of Google Vertex AI Product Recommendations for Magento Open Source
- Initiate Release of Google Vertex AI Product Recommendations for Adobe Commerce
- Initiate Release of Google Vertex AI Product Recommendations for Adobe Commerce Cloud
Note: Free Support of AI Model Training included with this version for next 15 days including custom script and bespoke production data.
Customer Reviews
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Overall Ratings
Powerful Google AI Integration for Better Discovery
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Review by
Sara Lay
March 25, 2026
Functions as Described
4
Developer Support
5
Usefulness
4
Overall Rating
5
This extension enhances product discovery with accurate search results and smart recommendations. It works best for high-traffic stores. Initial configuration is complex, but once set, it delivers strong results.
Yes, I recommend this extension.
Advanced AI Search for Scalable Magento Stores
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Review by
Dakota Knox
March 25, 2026
Functions as Described
5
Developer Support
4
Usefulness
5
Overall Rating
5
I implemented this extension and saw a clear improvement in search relevance and recommendations. It handles large catalogs well. Setup requires technical effort, but the performance boost makes it worthwhile.
Yes, I recommend this extension.
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Google Vertex AI Product Recommendations for Magento 2
$399