Earlier this year, Google launched a new office box predicting model using big data. Basically, Google tracks the search volume for a film’s trailer, factors in other information, like franchise status and seasonality, and then it can predict opening weekend box office revenue with 94 percent accuracy. Google didn’t express what their real intentions were, though industry insiders suggested that this kind of information could be used by studios to better market their films.
More recently, IBM also worked with a major movie studio to build a box office prediction model based on online audience behaviors. The objective was to determine whether there was a predictive relationship between social data and ‘Opening Weekend Box Office’ (OWBO).
It seems that “big data” is no longer a hot topic in engineers’ world; its popularity has expanded to Hollywood. Ideally, if marketers can use correct analyzing tools, big data can be used for marketers to gain more customer insights, segmentation or targeting information, to create new product strategies, marketing mix, and to conduct better integrated advertising. However, most companies have not yet truly understand how to correctly use big data analytics in their marketing strategy.
I would suggest, let’s start from knowing what big data really means for marketing, rather than simply following this trendy word.