Data Analytics in the Music Industry

MB-563
The amount of data available to organizations in the music industry has reached unprecedented levels. Data is transforming business, social interactions, and how music is consumed and artists are marketed. In this course, students examine real world examples of how analytics significantly improve management decisions, firm strategies, and artist success. Students learn the following analytical methods: linear regression, logistic regression, trees, text analytics, clustering, visualization, and optimization. Students apply data analysis and statistical concepts to evaluate artists’ and labels’ marketing strategies, using logic and strategic reasoning, as well as the latest trade and scholarly writings in the field. Students focus on three areas:
 
1. Attain Data
  • Write a survey or conduct a focus group (e.g. Qualtrics, SurveyMonkey)
  • Apply online databases and search engines (e.g. Google Alerts, Next Big Sound, BuzzAngle Pro, BMAT Vericast)
  • Import metrics from social media (e.g. Facebook, Twitter) or streaming platforms (eg. Spotify Artist Insights)
2. Analyze Data
  • Sort important data and clean unuseful data by using spreadsheet software (e.g. Excel)
  • Visualize statistical hypotheses (e.g. whatif function)
  • Assess industry reports (e.g. PRS, BPI, CISAC, IFPI)
3. Apply Data
  • Present and report the result of the analysis (e.g. graphs, maps)
  • Communicate the results of the data analysis (e.g. infographics)
  • Provide recommendations for business decisions (e.g. Tableau)
Credits
3
Prerequisites
Written approval of program director
Required Of
GEMB graduate students
Electable By
GEMB graduate students
Semesters Offered
Spring only
Location
Valencia
Department
GEMB
Course Chair
Emilien Moyon
Taught By
Courses may not be offered at the listed locations or taught by the listed faculty for every semester. Consult my.berklee.edu to find course information for a specific semester.