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An AI service that delivers a personalized user experience

Create rich, tailored interactions

Boost usability and user satisfaction with reinforcement learning–based capabilities only available through Azure. Prioritize relevant content, layouts, and conversations through an easy-to-use API. Use Personalizer as a standalone personalization solution or to complement an existing solution—with no machine learning expertise required.

Automatic model optimization based on reinforcement learning, allowing AI to achieve the goals you set

Apprentice mode provides a smooth transition by only letting Personalizer interact with users after the service reaches a level of confidence in matching the performance of your existing solution

User-friendly interface to monitor and adjust the learning loop according to your parameters and KPIs

No machine-learning expertise required

Improve user experiences with real-time learning

Give users relevant experiences that improve over time, based on their behavior. Unlike recommendation engines that offer a few options from a large catalog, Personalizer presents the single best outcome for a user, every time they interact with your app.

Get up and running quickly

Embed Personalizer by adding two lines of code. Easily inspect the accuracy of predictions and optimize as needed. Personalizer works with your data in any form. Start with no data or tap into you’re an existing dataset to jump-start reinforcement learning.

Once embedded, Personalizer can skip the learning curve with apprentice mode. When the feature is switched on, the service learns alongside your existing solution without being exposed to users until it meets your performance threshold.

See more about apprentice mode

Easily gauge how it's working

Interpret and evaluate Personalizer through the interface. Validate results by reproducing them, and gauge effectiveness of parameters with a stack-ranked view. For example, evaluate the impact of age, gender, and time of day on content engagement.

Evaluate your models

What customers say about Azure Personalizer

"We've always been sitting on a lot of data, but we needed Azure and AI to unlock its potential and find the interesting nuggets in those billions of data points."

Charlie Rohlf, Associate Vice President, Stats Technology Product Development, National Basketball Association

The largest compliance portfolio in the industry

Take charge with flexible pricing

Pay only for what you use, with no upfront costs. With Personalizer, you pay as you go based on number of transactions.

Documentation and resources

Get started

Read our documentation

Explore best practices and concepts

Learn how to use Personalizer responsibly to deliver a positive experience for your users.

Frequently asked questions about Personalizer

  • Personalizer and other Cognitive Services offerings guarantee 99.9-percent availability. No SLA is provided for the Free pricing tier. See the SLA details.
  • Personalizer learns from the collective behavior of users, through the features or attributes about them that you send to the service. It uses this information to train a shared model that’s updated with information from every interaction, improving personalization outcomes for all users.
  • Personalizer works best when a rank call has 50 or fewer items. To personalize a choice from a larger list or catalog, reduce the number of items by using a recommendation engine or sorting technique.

    Learn more about scalability and performance

  • Our algorithms and innovation are based on continuous work by Microsoft Research and on applied use of Personalizer in Microsoft businesses such as Xbox and Windows. Learn more about our approaches and reinforcement learning.
  • Personalizer works with or without user sign-in but delivers richer, more relevant interactions for signed-in users.
  • Yes. Personalizer learns in the background, in real time, via apprentice mode. When the service has learned enough from users' actions to approximate your existing personalization system, you can use Personalizer in production with confidence to let it learn by interacting with your users and support a positive user experience.

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