It seems like companies have an insatiable desire for information. In the era of big data there’s never enough, and organizations are constantly on the lookout not only for new types of information, but new sources from which to glean it. Of course, big data isn’t a crystal ball (though it’s sometimes hyped up to be), but it’s a great means of learning a number of different things, including personal preferences. The more we interact with different brands, and voice our opinions on social channels, the more we reveal who we are, our habits and overall behavior. That’s why marketers are so keen to adopt big data strategies. The more they know about us, they more they’ll know how to reach us.
Of course, this isn’t specific to any one industry. Big data analytics and understanding consumer behavior is just as important to healthcare providers as it is to steel manufacturers. However, while broad in its application, big data can certainly be more valuable to some companies than others, especially when a lot is on the line.
Media companies are constantly under pressure to deliver. Big budgets come with big risks, and if a production company or film studio invests tons of money into a movie only to have it flop, it may be their last gig. For example, it cost about $745 million to make The Hobbit trilogy. Imagine if it was a complete bust, and noone went to see it or bought any of the merchandise. Warner Brothers wouldn’t be in a very good place.
Fortunately big data makes it so executives don’t have to rely on just guesswork when it comes to crafting a blockbuster success. Here are a few companies using data to help beat the odds:
Netflix
It’s hard to talk about media companies and success without mentioning Netflix. Over the past few years, the company has seen tremendous growth. Netflix has found the perfect way to deliver customized content. When users create their profiles, it isn’t just so they can rate shows and queue movies. It’s primarily so Netflix can learn their viewing preferences. Netflix wants to know which demographics are watching what, when and for how long. When Netflix creates one of its Netflix Originals, they’ve studied extensively what people are looking for, and craft a show that fits. It also goes beyond that. People don’t decide what to watch just by the plot or the cast. We are very visual. We also make snap decisions based off the images associated with the film. Netflix uses big data to create graphics and designs for their shows that match other popular designs.
Hulu
The cousin of Netflix, Hulu, is also big data in every sense of the word. Hulu’s success is defined by how well it can offer the right material to gain and retain customers. By processing and analyzing data from its over 6 million subscribers, Hulu can decide which content to invest in, and convince partners on why they should choose Hulu as an advertising platform. Advertising on Hulu comes with a number of benefits, namely the ability to use targeted ads. In the days of cable, companies could choose which ads to run at specific times, but they were never able to fully grasp who was watching. Big data changes that. Insights into behavior can determine who is streaming which show, and advertisers can then tweak their messaging to match that individual.
Time Warner
Time Warner, the massive media company, has millions of customers. Not surprisingly, they collect information on each and every one of them, which amounts to about 0.6 terabytes of data a day. This information allows Time Warner to create personalized advertising and tailored campaigns for their customers. Time Warner combines demographic data sets and local viewing habits with other data, like real estate records. This helps it understand their customers on a more individualistic level, with insights into income and viewing environment. From there, Time Warner can create and push their ads and promotions using multiple mediums, like mobile apps and social media. This in turn provides more information on how people respond to each of these platforms, and Time Warner can make adjustments and corrections to further customize future ads.