So, what exactly is big data? How is it unlike ordinary data? The answer is all in the name – it’s really, really big. In the Mad Men days, an advertiser could send out nationwide surveys, scrutinize TV ratings, or cram a focus group full of 35-45 year-old moms with a preference for chocolate ice cream into a room. Nowadays, the world is your focus group.
That’s because technology has snuck its way into nearly every moment of our lives. And everywhere that there’s technology, there’s data. From websites to tablets to smartphone apps, consumers are generating mind-boggling amounts of information about themselves and their habits to marketers and advertisers.
You spent 3.2 minutes on haagandazs.com this morning?
You tweeted about how you can’t wait to scarf some ice cream tonight?
So did 1,672 women this week.
As marketers, this means we’re sailing through oceans of data that Mr. Draper could never have dreamed of. We can literally eavesdrop on our customers’ social media conversations. We know where they’re spending their time, which types of ads they’re clicking on, and which ice cream brand they Google the most. That being said, many strategists and analysts find the sheer quantity of readily available data overwhelming. That’s why big data is typically broken down into four V’s for measurement:
Volume is the amount of data being produced – in other words, how much information we have about ice cream. Processing and mining that volume is the first step to getting meaningful data that can be analyzed. And with the constant hum of social media, big data is always getting, well, bigger.
Velocity is a consequence of two factors: how quickly new data is being created, and how quickly the new data is integrated into existing models. That’s how often people talk about ice cream, and how quickly we will learn when chocolate unseats vanilla as the most popular flavor. “Stale” data can hurt your marketing – sometimes no information is better than bad information – so you’ll need to know how quickly data in your category is evolving.
Variety is what makes big data so immense. It’s asking “how many different ways can we learn about ice cream?” There are clickthrough rates, Facebook likes, Google searches, Foursquare check-ins at ice cream parlors, and countless other potential metrics. The more you’ve got the better – as long as it’s relevant.
Variability is usually considered the most important pillar in big data. If there was just one variable, volume would take precedence. Because there are so many characteristics that come together in social media, this can make for some exciting strategies once analysis is completed. For example, in retail, when a client’s information is combined with social graph data, it may identify key influencers within the retailer’s community. These people can then be contacted to participate in promotions and launches.
Even despite knowing the four Vs inside and out, you might be tempted to leap into the huge pool of data at your disposal before you really look at it. Take time to digest, strategize, and analyze. Remember that big data is constantly evolving with new analytics, new conversations, and new destinations emerging daily. The world is talking – now you’ve got to learn how to listen.