Investors put more than $3.6 billion into Big Data startups in 2013, but now Big Data is reaching the peak of its buzz. One reason may be that, though the promise of Big Data is huge, data sets are often unwieldy and unnecessary.
Big Data is all about volume. It requires powerful machines and seasoned data scientists to turn raw information into insights. Even at large companies, allocating the right resources and translating information between departments and disciplines can be tricky. And when insights are squeezed from the Big Data stone, how to put them to use is often unclear.
For example, in a recent study, 45% of organizations surveyed said they aren't even able to pinpoint the right audience for their messages most of the time. And only one-third of ad agencies are using big data to drive more than half of their marketing initiatives. Working with Big Data is challenging.
The antidote? Small data.
What Small Data Means for Marketers
Small data, in essence, recognizes the value of fewer, more relevant data points. The value of data shouldn't depend on its volume but on its quality and how it is analyzed, interpreted, and put to use. Small data is about focusing on real-use cases, collecting only the right type and amount of data, and applying it with maximum efficiency and contextual relevance.
For marketers, small data means specific, bounded data sets. It may mean working with a smaller sample size (perhaps a small slice of your customer base) or focusing only on the details that drive your business. Small data can help brands personalize, curate, and deliver more of what customers want in a timely fashion. Best of all, that kind of data is all around us, encompassing everything from weather to foot traffic to search and beyond.
Using small data as described above, brands can become more human. They can determine exactly what people want at a specific point in time and deliver it in a personalized and relevant manner.