Bruce Warila: Can Computers Really Analyze Songs For Hit Potential?

(Updated) This guest post comes from consultant and entrepreneur Bruce Warila.  Bruce has studied the technologies and services that measure a song's hit potential.

In response to the ASCAP and HITLAB announcement that basically endorses the use of algorithms to analyze the hit potential of songs, I thought I would weigh in on the subject. Proceed with caution…

As someone that spent the better part of a year evaluating similar algorithms, technology, services, business models and patents connected to acoustic analysis and hit potential measurement, I can tell you that you should proceed with caution when making a purchase or career decision that involves the utilization of services that sell computer-based, hit-analysis technology.  

It’s fascinating technology, however…

Generally speaking, the technology is reasonably accurate (my experience: 80% accurate, and often close enough to my expectations) when it comes to plotting a song relative to a cluster of preexisting hits and then rolling the plots into a meaningful score.  However a high score doesn’t mean you have a hit on your hands, or that “hits” even matter anymore.  Read on…

Here are some pros and cons to consider when evaluating services that use computers and algorithms to evaluate music:

Computer-based hit analyzing technology – the pros…

Targeting.  If detailed reporting is offered, this technology should show you how close your song is to clusters of previously recorded hits.  This information is useful for targeting listeners of similar sounding hit songs.  

Selecting.  You should also be able to use the information provided to evaluate which of your songs has the most market potential.  Provided that you believe: historic success is a reasonable indicator of future potential.  

Filtering.  This technology is also useful as a filter.  Even if it only meets (average) expectations four out of every five tries (80% and then along a declining slope), in the absence of something better (“better” could be built), algorithms can definitely cut the size of the haystack down for someone looking for the needles; especially in a world that creates and uploads over 1,000,000 recordings a year.

Supplemental information.  For professionals analyzing songs, with the right reporting/presentation, computerized hit analysis is great (or at least interesting) supplemental information when paired with market /social traction data, crowd-sourced vetting data and detailed acoustic analysis/comparisons. 

Computer-based hit analyzing technology – the cons…

Songs that sound like they have been professionally produced or recorded only.  The last time I checked, hit predicting technology was not very useful for evaluating singer/songwriter demos.  

Just because it sounds like a hit… There are numerous business and social factors that make a song a hit.  (Read the Song Adoption Formula on Music Think Tank.)  Business execution and promotion weigh heavily within the hit building formula (if there is such a thing).

Lyrics matter…  The technology I previously evaluated did not analyze lyrics, although lyrics as text or as acoustic features can be compared and analyzed by machines.  Make sure any service you buy can distill out the difference between lyrics about barking dogs, tuna fish and angry girlfriends.  Your epic song about cracked concrete may sound like a hit, but…

Connected to bullshit… This bullet is not a condemnation of the technology as much as it is a denunciation of the way I have seen this technology positioned and pitched to artists in the past.  Listen up.  It doesn’t matter if you are sitting on the highest scoring song in the history of the earth, you have more of a chance of propelling yourself to the moon using the methane from your ass than you have at landing an artist-friendly deal that guarantees you repeated (more than once), genuine mass-market exposure.  When anyone sells you exposure (based upon a score or anything else), go to www.compete.com (it’s accurate enough) and verify the exposure potential of the site, label or service first; then interview three or four artists that were previously promised the same thing.

Old paradigm thinking…  Do hits really matter?  When it comes to songs, determining popularity potential (along a spectrum and within niches) and then matching songs to taste preferences, and artists to target audiences (through recommendation), are the technological advancements that should really matter to the majority of artists (IMHO).

The bottom line..  You can learn something by using/applying this technology wisely,  Just don’t use it for all the wrong reasons.

About Bruce Warila