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The genre shirt asks, “What kind of music do u listen 2?”

Microgenres exist because markets are fragmenting and marketers need names to attract emerging customer segments with increasingly specific preferences. The cost of producing and delivery music now supports a plenitude of joint pairings of recordings and customers. The coevolution of music and its audience binds together listening preferences and available alternatives.

I already know a good deal about your preferences by simply knowing that you listen to German Hip Hop or New Orleans Jazz (see the website Every Noise at Once). Those microgenres are not accidental but were named in order to broadcast the information that customers need in order to find what they want to buy and at the same time that artists require to market their goods. Matchmaking demands its own vocabulary. Over time, the language adapts and only the “fittest” categories survive.

**R Makes It Easy**

The R package NMF simplifies the analysis as I demonstrated in my post on Modeling Plenitude and Speciation. Unfortunately, the data in that post were limited to only 17 broad music categories, but the R code would have been the same had there been several hundred microgenres or several thousand songs.

The output is straightforward once you understand what nonnegative matrix factorization (NMF) is trying to accomplish. All matrix factorizations, as the name implies, attempt to identify “simpler” matrices or factors that will reproduce approximately the original data matrix when multiplied together. Simpler, in this case, means that we replace the many observed variables with a much smaller number of latent variables. The belief is that these latent variables will simultaneously account for both row cliques and column microgenres as they coevolve.

This is the matrix factorization diagram that I borrowed from Wikipedia to illustrate the process.

**Interpreting the Output**

**Why NMF Works with Marketing Data**

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