Usage Rates, Facebook Likes, and Online Piracy: Using Big Data to Manage Entertainment Products

The rapid digitization of the entertainment industry urges managers to find new ways to improve marketing effectiveness and combat online piracy. Smart devices and innovative online services generate brand-related tracking data that reflect consumers’ brand engagement (e.g., digital usage rates, Facebook Likes), yet managers are unaware of how to use these big data to improve brand performance. We therefore propose a model to assess how digitally tracked engagement behaviors, namely consumer brand usage (CBU, measured by digital usage rates) and consumer brand endorsement (CBE, measured by Facebook Likes), drive the impact of promotion and new product releases and affect the role of piracy. We apply our framework to the U.S. music industry, and develop web scrapers and API mining scripts to collect data for 569 music artists over 66 weeks. Both CBU and CBE enhance marketing effectiveness and positively mediate the sales impact of piracy, thereby offsetting piracy’s cannibalization effect by 55%. However, CBU exerts a systematically stronger influence in these relationships than CBE. Using simulations, we show how our findings can help managers to improve the allocation of their marketing efforts across brands and reduce the detrimental sales impact of piracy.

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