Hi Creators,
Today, we’re excited to announce the global release of an improved Recommended For You algorithm, along with a new Home Recommendations Creator Analytics tab to give you full visibility into the algorithm and to help you optimize and grow your experiences.
A Breakdown of Our Recommended For You Algorithm Signals
We’ve outlined the recommendation signals used by the new Recommended For You algorithm in the table below, including each signal’s definition and its role in influencing recommendations.
| Recommendation Signals | Definitions |
|---|---|
| Qualified play-through rate (qPTR) | The number of engaging plays divided by the number of impressions from Recommended For You. |
| 7 day playtime per user | Total playing time per user in your experience within the last 7 days (maximum of 60 minutes per user, per experience, per day). |
| 7 day play days per user | Total unique days users engage with your experience over the last 7 days. |
| 7 day spend days per user | Total unique days users spend Robux in your experience over the last 7 days. |
| 7 day Robux spent per user | Total Robux spent per user in your experience over the last 7 days. |
| 7 day intentional co-play days per user | Frequency of users intentionally playing with friends over the last 7 days (through join, invite, or private server rather than through a matchmaking). |
Optimizing Your Experiences with Recommended For You Signals
Roblox is more fun when you’re in experiences with friends, and users are often looking for new experiences to join with established connections. From our testing, we’ve seen that users with higher frequency of play, spend, and interaction with friends have a higher likelihood of long-term retention. Therefore, we’ve added an intentional co-play recommendation signal, which detects users manually joining experiences with friends via invites, sessions, or private servers and strongly indicates user interest.
To encourage co-play, focus on designing gameplay that naturally motivates users to spend time together and communicate meaningfully. For example, you can include player invite prompts and private server options, making it easier for users to invite their friends and increase co-experience gameplay.
Keep in mind — intentional co-play is not the only signal to pay attention to. When all of these signals are improving together in an experience, the recommendation algorithm will pick it up. Improving your retention, engagement, and monetization directly enhances our recommendation signals, resulting in better Home visibility.
And, to foster sustainably fun sessions, we limit recommendation benefits to the first 60 minutes of daily playtime per user, per experience.
Using Home Recommendation Analytics to Grow Your Experience
Our new Home Recommendations dashboard helps you monitor these recommendation signals. To access it, go to the Analytics > Acquisition page on Creator Dashboard, and select the Home Recommendations tab. Here’s how to use it:
1. Analyze Home Recommendation Impressions and Plays Trends
For example, if you observe a dip in Home Recommendation impressions starting March 3rd, you can analyze the corresponding recommendation signal trends.
2. Analyze Recommendation Signal Trends for Optimization
Keep in mind, changes to your recommendation signals usually show up in impression changes a few days later. So, if you noticed your qualified play-through rate dip on February 28th, that likely led to the impression drop on March 3rd.
It’s also important to identify recommendations signals that are below benchmark as areas of opportunity. Note that:
Continuing with our example, the charts below show that 7 day playtime and 7 day play days are both below benchmark. In this case, you may want to consider improving your onboarding funnel to encourage users to visit your experience more.
3. Discover Experiences Your Users Also Enjoy
We’ve added a list of similar experiences at the bottom of the page, based on relevant benchmarks, to show you other experiences your users enjoy.
Using Recommended For You to Get Discovered
Empower your creative vision and build experiences users will love discovering on Home, where over 90% of traffic begins. To maximize discovery via Recommended For You, leverage its recommendation signals to understand user preferences and adapt your experiences to drive engagement and long-term retention. Consistent updates, accurate experience details, and optimization with Creator Analytics are also key to improving discovery and building a loyal community.
We are continuously evaluating and refining the Recommended For You algorithm to improve discovery. This includes running experiments on limited segments of users. We will provide regular updates on algorithm changes, including these experiments, through announcements like this one. For updates that introduce new recommendation signals or significantly adjust existing ones for a larger audience, we will strive to give you as much advance notice as possible.
Thank you for everything you do to make Roblox great.
Roblox Discovery and Creator Success Teams
FAQs
Do I have to optimize for every recommendation signal in the Recommended For You algorithm?
-
While optimizing for all recommendation signals is beneficial, it’s most effective to focus on creating a high-quality, engaging experience. Prioritize core gameplay, user retention, and accurate metadata to improve overall user experience. To improve QPTR, focusing on your thumbnail personalization strategy is key. This includes showcasing new content or gameplay, keeping multiple variations active, avoiding overly similar thumbnails, and monitoring QPTR over time, especially after surges in Home recommendations.
It’s important to note that you may observe a temporary drop in QPTR when your impressions increase – particularly during initial discovery phases. This is a normal occurrence as new users discover your experience, and QPTR should stabilize as traffic patterns normalize.
Will these recommendation signals favor larger experiences with more users?
- No. These recommendation signals are calculated as averages per user, not total values. This ensures that smaller experiences with highly engaged users are not disadvantaged. We are focused on per user engagement, not total engagement. The Recommended For You algorithm is designed to match users with experiences they are most likely to enjoy. By prioritizing user satisfaction, you’ll create experiences that resonate with your audience and foster long-term engagement.
How quickly will changes in developer actions be updated in the analytics and the algorithm’s recommendations?
- Most of the signals get updated within 24 hours.
