You've picked the perfect tracks for your Spotify playlist and you want to arrange those tracks. You've got something in mind, but getting started can be a daunting task. MixMoose's Flowify feature has two ways to auto arrange your playlist, so you can focus on specific creative decisions instead of tediously dragging a bunch of tracks around.

Getting Started

Curve and Sets method choices

Current editor toolbar with Flowify controls Flowify is accessed from the editor by selecting its icon from the main toolbar. Once selected a menu will open with two options, the Curve Method and the Sets Method. Selecting a method will show further options with a series of weights below.

Both methods will allow you to assign weights, or importance, to various track features. For example, if you wanted the selected method to only take into account Energy, you could assign a weight of 100% to that feature and leave the rest at 0%. If you don't know what a track feature means - hit the handy question mark next to the feature label or read more about it in Analysis Categories Explained.

Curve Method

Example of creating a curve with peak in the middle.

The curve method allows you to design curves that then will be used to fit features to. For example, if you wanted your playlist to reach the peak of Acousticness in the middle of the playlist, then you'd design a curve with a peak at the middle and weight Acousticness at 100%.

But what happens if you want different features to follow different curves? Next to each feature weight slider is a pencil icon you can click to edit an individual weights curve. One use of this would be if two features you wanted to emphasize were anti-correlated: You could draw a curve that was the opposite of the others to good fit.

Sets Method

Current Sets controls with set size and editable feature weights
Set size and feature weights in the current interface.

If you ever used the generator, then you already used this method without even knowing it. It runs after every playlist generation just to give a little extra something to your new playlist. Sets builds groups of tracks that share the features you have weighted. It keeps each group cohesive while ordering the sets to give the playlist distinct changes of character. By the way, if you have the money then hire a DJ - your party will be much better.

Set Size is a target, rather than a hard limit. Natural groups may be a little smaller or larger. When its runs, it will break the tracks up into sets of like tracks, determining likeness from the weights.

DJ Compatibility

Both methods have a DJ Transition Strength control. Increase it to favor transitions with compatible closer BPMs and smoother harmonic transitions. Small BPM differences lose little credit. Perfect harmony gets full harmonic credit, with larger energy changes receiving less. Energy up and down count equally, as do matching, half-time, and double-time tempos. BPM and harmonic fit contribute equally, so either can help the overall score. At 0%, the control is off. In Curve, higher values allow the arrangement to move farther from the curve you drew. In Sets, it changes the order within groups and the tracks at their boundaries, keeping each group together.

Add the DJ Compatibility analysis chart or table column to inspect the transition from each track's predecessor. A dash means there is no previous track or the required metadata is missing. The score is a guide for choosing an order, not a guarantee of a seamless mix. MixMoose does not beatmatch audio or change the tracks' keys.

General Tips

Limit Weight Usage

Don't use too many weights, especially for the curve method. For one thing, there are a lot of calculations going on and the more curves/tracks used, the exponentially larger the requirements are to perform the calculations. More importantly, you'll just end up with a ball of mud.

Understand Feature Relationships

For the curve method, try to understand how your track features relate to each other. If two features don't correlate, then using like curves won't have a great result. Likewise if two features have strong correlations, then having inverse curves will also produce a bad result. Some experimentation is required. Also, if people ask for it, I'll work on adding a correlation matrix to the UI.

The sets method can handle more weighted features, but some of them might not produce a precipitable result. For example weighing release date will muddy the result for a playlist of tracks with a narrow release date range, since tracks from one year to the next probably won't really be that different. However don't assume a feature won't be effective: I like using instrumental % on trance playlists because I personally like having the vocal and no-vocal tracks separated.

Have Realistic Expectations

You'll still have to do some arranging. Sometimes a good place can't be found for a track. Sometimes even if everything makes sense quantitatively, you'll still perceive a track to be out of place. Sometimes something out of place makes great sense, like dropping dub in the middle of jungle.

Conclusion

I hope you have a lot of fun using MixMoose's Flowify. If something doesn't work right, or you have any questions then please send a message via the contact page for direct email and social links.