The latest buzz concept is ‘Big Data.’ Like most buzz concepts/ words, its definition leaves much up to the mouth of the speaker. Big Data, whatever the specifics, refers to the large amount of information that can be collected from online activity and exchange of information (on social networks, for example). The ability to aggregate such information from posts, streams, and online purchases creates some truly ‘big’ numbers. And they are only further extended with the collection of information from rewards programs and loyalty cards.
But Big Data can also trick us with impressive numbers like our Twitter followers or Facebook friends − but who within that number are encouraging each other to support our causes? Though ‘numbers don’t lie,’ statistics do, so an organization must know how it’s going to parse the data is collecting and what it hopes to achieve with the effort.
Commercial marketers see in big data as a gold mine to seek out rich veins of customer habits. John Caron of Catalina Mobile is excited about our ability to present the precise information to the right customers at the right time:
With the amount of shopper data available today, we have an unprecedented opportunity to get the right ads in front of the right people… based on their purchase-behavior. Not based on their age, sex, income or marital status, but based on what they bought last week, last month or last year. Purchase-behavior, gathered by every retailer or brand with a loyalty program, is more abundant than ever before, and it provides marketers with new, relevant data points with which to target shoppers.
Nonprofits, though, are not looking for such metrics, even as they are collecting ‘Big Data.’ So the question is, what sorts of metrics might you want?
The answer depends on what you hope to improve. The data can be parsed in numerous ways, but what are you looking for? Before you crunch numbers, that should be your first question.for what you want to accomplish in the real world? If, for example, you want people to buy organic cleaning products at their stores, tracing the retweets of your message won’t give you much information about your project − though you might get a psychological boost if the message is spreading quickly.
But if you offer people a coupon that rewards them for one purchase by encouraging another, then you can count the numbers of coupons distributed versus the number of coupons used. That data is smaller in numbers, but bigger in value!
Similarly, if you want to see if your flock of followers is really as big as the number suggests, tap into the online app ‘Status People’, which will check whether your followers are real people or not. You might not be entirely happy with the result, but again: bigger value talking to those who are left.
Big Data could simply be a set of numbers you hope to impress a potential donor with, but don’t be afraid to understand ‘big’ in terms of worth as well. Set goals first of all, then see if meaningful analysis of the data shows if/how those goals are being met. If not, spend a moment reconsidering the analysis − but the biggest portion of your time should be spent analyzing why you are not meeting those goals.