<aside> <img src="/icons/bullseye_gray.svg" alt="/icons/bullseye_gray.svg" width="40px" /> Monitor your integration to guarantee the best recommendation experience on 3 main levels

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<aside> <img src="/icons/heart-rate_pink.svg" alt="/icons/heart-rate_pink.svg" width="40px" /> Scale & recommendation system reach

Monitor the number of items and users exposed to recommendation to ensure that recommendations are being generated for a significant portion of items and users

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<aside> <img src="/icons/heart-rate_pink.svg" alt="/icons/heart-rate_pink.svg" width="40px" /> Recommendation engine monitoring

Keep track of recommendation events for insights:

• to assess how often content recommendations are being generated and served to users
• to identify any issues with the recommendation engine or integration, ensuring a smooth user experience. </aside>

<aside> <img src="/icons/heart-rate_pink.svg" alt="/icons/heart-rate_pink.svg" width="40px" /> Personalized recommendation integrity

Monitoring interaction distribution patterns over time is crucial for personalized recommendations.

• Verify the interactions integrity between your platform and our recommendation system.
• A diversity in interactions enhances user's recommendation performance. </aside>

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<aside> <img src="https://s3-us-west-2.amazonaws.com/secure.notion-static.com/3a70692e-9df6-4e62-b329-495247117f43/rumoicone.png" alt="https://s3-us-west-2.amazonaws.com/secure.notion-static.com/3a70692e-9df6-4e62-b329-495247117f43/rumoicone.png" width="40px" /> The recommendation system performance is highly dependent on your catalog’s metadata and integration, this is why it is essential to monitor it on different levels. However, our metrics are also there to assist in crafting the most effective content acquisition strategy to enhance user retention.

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