Hi Creators,
As shared at RDC, we are committed to being transparent about meaningful updates that could affect the discovery of your experiences. Today, we’d like to share an update on our recent efforts to improve the algorithms behind the “Recommended For You” sort on Home.
What are we testing
We’ve previously shared how user behaviors impact which experiences are shown in the “Recommended For You” sort on Home. For instance, we rank experiences based on engagement (e.g. qualified play through rate, D1/D7 retention and play time) and monetization (e.g. payer conversion and robux spent), as these are proven indicators of user value and long-term retention.
We’re excited to share our progress in identifying additional user behaviors that indicate long-term retention and help more creations get the opportunity to succeed on Roblox.
This will allow us to rank experiences and updates with a broader definition of success.
What this means for you
Keep building and updating experiences that users want to come back to. Our focus on long-term user retention hasn’t changed. You can also continue to track how your experience is doing in Creator Analytics.
As we test, we want to give you a heads up that some experiences may see fluctuations in their “Recommended For You” impressions. You can continue to monitor impressions from various sources including Home Recommendations in your analytics dashboards.
In early 2025, upon finalizing the results of these tests, we will incorporate these additional user behaviors into our overall recommendation algorithm and add them to your Creator Analytics dashboards so you can clearly see how your experience is doing and where it can be improved.
Please stay tuned for additional announcements in the new year and let us know if you have any questions.
Thank you,
Roblox Discovery Team
FAQs
Thank you for your questions. Below we’ve answered some of the most common ones.
What happens to good experiences that are meant to be deeply engaged vs. frequently in bursts?
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We’re testing additional user behaviors that are strong indicators of long-term retention. We are not replacing or overriding the user behaviors that are already proven indicators of long-term retention.
As a recap, we rank experiences based on engagement (e.g. qualified play through rate, D1/D7 retention and play time) and monetization (e.g. payer conversion and robux spent), as these are proven indicators of user value and long-term retention. In addition we’re now testing the addition of the frequency with which users return to play, spend, and interact with friends.
One user behavior alone is unlikely to disproportionately impact an experience’s discovery. As an example, while we value robux spent, completely free experiences that engage users in other ways can still rank well. Our intent is to rank experiences and updates with a broader definition of success.
How does Roblox account for frequent crash rates or other low-quality issues that may superficially increase the frequency of use?
- Frequent crashes mean a poor user experience, which doesn’t help the discovery of an experience; it hurts it. Our systems already account for this and will continue to do so.
Do the recommendation algorithms show monetizing experiences to paying users only?
- We do not funnel paying users to monetizing experiences only or non-paying users to non-monetizing experiences. We aim to match experiences that users enjoy playing and keep returning to.
What does “interacting with friends” mean?
- Co-playing, such as users joining an experience because their friend is playing or chatting with their friends within the experience are two examples of user behaviors in this category.