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FindArticles > News > Technology

Spotify Is Testing a Smarter Shuffle With Fewer Repeats

Bill Thompson
Last updated: October 28, 2025 6:12 pm
By Bill Thompson
Technology
6 Min Read
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Spotify is testing new controls for shaping your shuffle wants and needs, enabling listeners to influence the probability of hearing a specific track or artist during a play session. Characters found in a recent Android beta build suggest there will be a selectable shuffle style—one that specifically cuts down on repeats by downweighting tracks you’ve heard recently, among others. In other words, listeners may soon be able to choose between a truly random order and a “fresher” shuffle that takes variety into consideration when playing music.

What Is Actually Changing in Spotify’s Shuffle Controls

It looks like there will be at least two options for regular shuffle on the upcoming menu. One, an all-tracks-equal, black-box approach, is still possible. The other, provisionally titled something like “Fewer repeats,” recalls the songs you’ve heard recently and is less likely to offer up the same one so soon. According to the language in the beta, this more intelligent shuffle style might need personalized recommendations to be activated in settings.

Table of Contents
  • What Is Actually Changing in Spotify’s Shuffle Controls
  • Why Listeners Want Less Repetition in Music Shuffle
    • How a “Fewer Repeats” Shuffle Likely Works
  • What This Means for Personalization and Recommendations
  • Availability and Rollout Expectations for Spotify Shuffle
Spotify logo in green and white, set against a clean white background in a 16: 9 aspect ratio.

These are distinct from Smart Shuffle, which is when a recommended song is injected into your playlist. The new controls concern how the app arranges the tracks you’ve already chosen, allowing users to have a say in just how much randomness they actually want.

Why Listeners Want Less Repetition in Music Shuffle

People rarely want “pure randomness” from a music queue. Behavioral research has long shown we perceive true randomness as suspicious when patterns appear, and we overreact to streaks. That’s why purely random shuffles can feel repetitive or unfair even when they are mathematically sound. Streaming forums have been filled for years with “shuffle keeps playing the same songs” gripes, despite huge libraries at hand. Other platforms have grappled with this too; early music apps publicly admitted they tuned their shuffles to feel more random by preventing clusters and downweighting recently played tracks, rather than relying on a strict lottery each time. Spotify itself has discussed this in public too. Making this an explicit choice is a welcome acknowledgment that one size doesn’t fit all.

How a “Fewer Repeats” Shuffle Likely Works

Under the hood, expect a mix of probability weighting and recency rules. A sliding “exclusion window” is a straightforward approach, where songs played in the last N picks are removed from the candidate pool until they age out. Weighted sampling is another method; this gives every track a chance but assigns recently played items a much lower weight that ages out over time.

Consider a 100-track playlist. With a strict random set list that allows repeats, your chances of hearing the same song very close together are not zero. Create a recency window of, say, the last 15–20 picks, and the likelihood of going back-to-back within that span is essentially zero. Throw in a mild adjacency rule (don’t play the same artist back to back) and you can smooth perceived patterns even more—without squashing surprise. These are standard tricks in recommendation systems that aim to be lively, not chaotic.

A hand holding a smartphone displaying the Spotify logo and name on a dark screen, set against a solid green background, resized to a 16: 9 aspect rat

What This Means for Personalization and Recommendations

Jumping on behavior signals, as the “Fewer repeats” mode seems to do, Spotify might connect this feature to differences in personalization settings, as it’s related to how the service powers features such as Autoplay, Smart Shuffle, and Discover modes that are based on listening history. For users concerned about data usage, the regular shuffle will stay as an option. An equal-chance shuffle appears to be a neutral side-by-side comparator.

For heavy playlisters and casual listeners alike, the result is less déjà vu. On big playlists, a recency-aware shuffle can help bubble up deeper cuts. On small playlists or mood sets, it can preserve a vibe while preventing fast repeats that counteract momentum.

Availability and Rollout Expectations for Spotify Shuffle

So far the only evidence is some language that appeared in an Android beta build, which doesn’t prove the feature has been turned on (or necessarily enabled for everyone). Spotify frequently gates new behaviors behind server-side flags and A/B tests, so some users might already be getting benefits without seeing new toggles. When it eventually does arrive, expect to see a Shuffle entry in playback or recommendation settings, from which you can pick the style that best suits your listening.

And with over half a billion monthly listeners, according to recent earnings reports, tiny changes in playback logic can have a significant impact. Explicitly presenting the user a choice of whether they want “true random” or “fewer repeats” is a sensible solution, and it respects that users have opinions about this based on our psychology of how we experience randomness. It’s a long-requested tweak and—if testing goes well—one that could soon become people’s default way to shuffle.

Bill Thompson
ByBill Thompson
Bill Thompson is a veteran technology columnist and digital culture analyst with decades of experience reporting on the intersection of media, society, and the internet. His commentary has been featured across major publications and global broadcasters. Known for exploring the social impact of digital transformation, Bill writes with a focus on ethics, innovation, and the future of information.
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