Recommendations AIBeta

Deliver highly personalized product recommendations at scale.

Give customers more of what they love

Earn your customers’ trust and loyalty by proving how well you understand them. Google has spent years delivering recommended content across flagship properties such as Google Ads, Google Search, and YouTube.

Recommendations AI draws on that experience and expertise in machine learning to deliver personalized recommendations that suit each customer’s tastes and preferences across all your touchpoints. 

What's new

Fully managed service

No need to preprocess data, train or hypertune machine learning models, load balance or manually provision your infrastructure to handle unpredictable traffic spikes. We do it all for you automatically.

Get up and running fast

Integrate data, manage models, serve recommendations, monitor performance, all from an intuitive graphical user interface. Quickly connect data with your existing tools like Google Analytics 360Tag Manager, Merchant Center, Cloud Storage, BigQuery.

State-of-the-art AI

Take advantage of Google's expertise in recommendations, powered by state-of-the-art machine learning models. They can correct for bias and seasonality and excel in scenarios with long-tail products and cold-start users and items.

Maximize value of your data

Put all your data to work producing great predictions by incorporating unstructured metadata like product name, description, category, images, product longevity, and more.

Deliver at any touchpoint

Offer first-time users and loyal customers alike high-quality recommendations via web, mobile, email, and more, anywhere in their journey from homepage to shopping cart to order confirmation and beyond.

Choose your strategy

Customize recommendations to deliver your desired outcome: engagement, revenue, or conversions. Apply business rules to fine-tune what customers see, diversify product displays, and filter by product availability, custom tags, etc.

Automatic global scale

With one click, you can seamlessly deliver curated recommendations with low latency to customers anywhere in the world. It supports international product catalogs and multiple geographies.

Your data, your models.

Your data and models are yours and yours alone. They’ll never be used for any other Google product nor shown to any other Google customer. You’re never locked in, and can delete your data and models anytime. Learn more.

GDPR compliant

Recommendations AI is compliant with the General Data Protection Regulation (GDPR). Compliance with the GDPR is a top priority for Google Cloud and our customers. See terms for more information.

Dramatic improvements to meaningful metrics

Recommendations AI uses Google’s latest machine learning architectures, which dynamically adapt to real-time customer behavior and changes in variables like assortment, pricing, and special offers. Early results from retailers around the world have shown dramatic improvements on previous recommendation systems, with some achieving up to the following results.

How it works

Customer stories

Recommendations AI was easy to integrate with our existing recommendations framework, and enabled us to deliver next-gen recommendations without a ton of work. We are steadily investing in data science and it is very helpful for us to be able to integrate and test different algorithms. Recommendations AI performs really well on our product detail pages and increased conversions and revenue significantly.

Oliver Herren, CIO, Galaxus


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Technical resources


Pricing for Recommendations AI is based on operations such as training and tuning (per node per hour) and requesting predictions (per 1000 predictions). Prediction cost is tiered by number of monthly prediction requests.

You can try Recommendations AI with a $600 free credit. This free credit is typically sufficient to train a model and test its performance in production through a two-week A/B test.

View pricing details

Take the next step

Start building on Google Cloud with $300 in free credits and 20+ always free products.

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