The only way any of us can understand online audiences is through data. Companies like Nielsen and comScore have traditionally gathered that data by tracking a sample over time. But increasingly, what we know about audiences comes to us through servers.
Servers collect vast amounts of information on what consumers are doing online every second of every day. To some businesses, this Big Data speaks for itself and offers a crystal-clear lens with which to see and manage audiences. But much of the buzz surrounding Big Data is hype.
To make effective use of Big Data, marketers should be clear about its strengths and weaknesses. Here are five questions to keep in mind when you're seeing the marketplace through Big Data.
Census or Sample?
Big Data is often thought of as a census. If that were true, it would be great. You wouldn't have to draw a sample and carefully "weight" individual responses to reflect the population. But frequently, Big Data really means a big sample.
For instance, some companies claim that gathering data from digital set-top boxes (STBs) can create a census of the TV audience. In practice, however, STB ratings are based on samples that are cobbled together and extensively weighted to resemble the total TV audience. Those samples are large enough to offer a lot more granularity than traditional methods, but they're not close to a census.
Moreover, most big databases are adjusted in some way. You may think that the topics trending on Twitter reflect a simple headcount, but trending metrics are tweaked in ways that aren't widely reported. Providers of "currency" measures are often audited, so it's easier to know the recipe behind the numbers. But how many of the newer metrics are cooked up is a mystery. If you use them, you should assume you're not getting an unadulterated look at the audience; you're probably wearing corrective lenses.
Preference or Behavior?
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