big data analytics
Yet having access to the data is only one part of the equation. Making sense of the data is the harder part.
Marketers sometimes forget the Statistics 101 maxim that correlation doesn’t imply causation. I’m also sensing a movement in business to follow data blindly without common sense questioning.
As New Yorker’s Gary Marcus put it, “Big Data is a powerful tool for inferring correlations, not a magic wand for inferring causality.”
There’s an art to data science. Big Data does not necessarily lead to Big Insights. As marketers, we need to ask the right questions to collect the right data, and probe deeply on the implications that we find.
I liked reading this insight from the Guardian that advocates Lean Data over Big Data:
“The dirty secret of big data is that no algorithm can tell you what’s significant, or what it means. Data then becomes another problem for you to solve. A lean data approach suggests starting with questions relevant to your business and finding ways to answer them through data, rather than sifting through countless data sets.
“Furthermore, purely algorithmic extraction of rules from data is prone to creating spurious connections, such as false correlations. Today’s big data hype seems more concerned with indiscriminate hoarding than helping businesses make the right decisions.”
I’d love to hear your thoughts and experiences marketing with Big Data.
(Marketoonist Monday: I’m giving away a signed print of this week’s cartoon. Just share an insightful comment to this week’s post by 5:00 PST on Monday. Thanks!)