Concert Hacking: An SEOs Insight into Playlist Prediciton

I recently stumbled upon lifehackingmovie.com and read about the making of You 2.0 – a documentary about finding shortcuts in everyday life, ultimately to get the boring stuff done quicker so there’s more time for the fun things. It ties into Web 2.0, but it’s more about the ideas behind what Web 2.0 is bringing, such as more information and distractions as well as tools to get more done.

Last night a coworker and I went to see the Bedouin Soundclash play at Maxwell’s in Hoboken during which we discussed the idea of “hacking” a concert. In the same vein as life hacking, is it possible to hack a concert using Web 2.0 technology? Can one comb through iTunes, Amazon.com, fan sites and Tweets for information to predict a band’s live concert playlist?

As an SEO specialist, my job is to analyze Google’s  ranking system and identify variables that affect search results. Ever wonder how Google works? Basically Google finds a website, runs it through an algorithm, evaluates it and figures out how it measures up to other sites. How does the algorithm work? That’s the catch – no one knows, well at least not  with 100% certainty. A search engine takes into consideration the words on the page, the antiquity of the site, the number of links pointing to it along with over 20 other metrics. Google is pretty helpful. What happens if I try and apply the same logic?

My example: The Bedouin experiment (has nice ring to it). Here is some background info – The band’s new album issued this month, “Where have all the Songs Played Gone To,” takes its title from the track 12:59 Lullaby featured on their former offering Street Gospels.  The five song EP features B-sides from Street Gospels with the addition of one new song, On My Block.  The band is most commonly know for their 2005 smash hit “When The Night Feels My Song.” They are from Canada. The show is at a small intimate venue.

A week before the show my coworker had never even heard of the band. Without hearing the band, she agreed to attend the concert. She then downloaded songs based on reviews and number of downloads via iTunes. She also listened to the latest album figuring that the tour served as a promotion platform for the new CD. The day of the show she burned me a mix of her predicted playlist. Without much effort she guessed ~ 70% of the songs played – not bad for knowing nothing about the band.

If I were to create an algorithm to predict the concert’s playlist, here are some of the criteria I would use:

• Date of latest album release – Create a filter with a threshold. Playlists would only include one song from albums less than 2 months old.
• Radio play – What songs are the radio stations beating to death?
• Size of the venue – A band is more likely to play lesser known songs to diehard fans at a small, intimate venue. Bands playing massive concerts or festivals pick songs that are more geared towards sing alongs and crowd assistance.
• Opening acts – Fan diversity influences the inclusion of hit songs versus fan favorites.
• Number of downloads on iTunes – This is an excellent indicator of song popularity.
• BPM (beats per minute). Fast songs follow slow songs and vice versa. The tempo of a concert ebbs and flows like the tides.

I’ll be trying out this idea on my next concert and will post the results. Let me know if you can think of any other criteria to consider. Happy hacking!