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Big data can make a big impact in a company or agency’s approach to marketing. Patrick Negron of Cobalt and Arun Jacob of Disney Technology and Shared Services discussed how to get the most out of a stream of never ending information.
Big data means you have such high volumes that it “swamps” traditional tools, it won’t really fit into your traditional tabular format, and it is most likely accumulating at a very high velocity. The right set up allows you to “throw machines” at your big data to find insights and patterns.
But just having big data and the proper system is not enough. The pair emphasize that you must define and understand the problem you are trying to solve before you dive in looking for answers. If you aren’t sure what this problem might be, they believe it is best to “collect, store, and analyze” until you begin to sift out patterns. Then you can begin to create specialized offers or customized promotions. It is also important not to assume you know what data you need. Data has a way of revealing insights that are completely unexpected, so you don’t want to start with too narrow of a search. Staying focused on the value and purpose will prevent you from being caught up in the hype of a new technology. For example, just because you can monitor data in real time doesn’t mean you need to. Start by understanding your information as a whole before you move on to instant measurements.
In addition to its impact on tracking and monitoring, big data is rapidly increasing the speed at which marketers can test and measure new ideas. With big data, the cost of failure is significantly reduced, allowing marketers to “fail fast.” This experimental approach to campaign development is transforming marketers into scientists. Big data decreases our dependence on intuition. Marketers can stop a new campaign as soon as they know it isn’t working, or they can turn up the volume on techniques that preform strongly.
If your company is ready to implement big data practices, Arun and Patrick emphasize that building an inquisitive team is an important first step. You need people who want to understand why and how your data is connected. It’s about attitude. If you can hire smart people who are passionate about analysis the techniques can come later.