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SmartData Collective > Analytics > Big Data in the Music Industry: Richard Bowman
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Big Data in the Music Industry: Richard Bowman

AnniePettit
AnniePettit
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Welcome to this series of live blogs from the IJMR Research Methods Forum in London. Any errors, omissions, or silly side comments are my own.


Welcome to this series of live blogs from the IJMR Research Methods Forum in London. Any errors, omissions, or silly side comments are my own.

11.15 Big data – Making a difference with consumer insight-generated ‘big data’ in the music industry
Richard Bowman, Artist Development Insight Director, EMI Music

  • The old world – Hits paid for misses
  • Cassettes are dead, LPs are just about dead, CDs took over the world
  • People aren’t paying for music they way they once did
  • In music, it never works like this: consumer research to insight to decisions
  • They combine insight with skills and expertise of their people.  These are evidence based decisions that are owned by everyone. [THAT is how it should be done. Researchers are not specialists in your business.]
  • Insight is not a powerpoint presentation. It’s consulting with the internal experts.
    • Want relevant, valuable, and quick insights for all of their colleagues
    • It needs to be powerful, broad, global, and repeatable [there’s that annoying reliability thing again]
    • Must add to shared language and guide decision making
  • Can market research produce big data? They have spoken to 1 million people in 3 years. That comes out of 100 people surveys and 6 people focus groups. At any point, they are interviewing 12 people somewhere in the world.
  • Inferior research is not an option [Question: are British researchers more concerned with validity and reliability or is it just this single conference? I liiiiiiike it!]
  • The key skill is the people, not the technology
  • They have ONE database per function containing ALL global data they’ve every worked with  [that’s exactly how it should be!]
  • New analysis technique: contest where anyone could analyze a set of data that they provided – e.g., July 2012 hackathon

 

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