When I first heard the phrase “big data,” I thought about the early computers, those Frankensteinian behemoths that helped change the world. The picture below (circa 1945) is the Electronic Numerical Integrator And Computer (ENIAC), the first general-purpose electronic digital computer. It was 150 feet wide, with 20 banks of flashing lights, and about 300 times faster than its predecessor, the Mark 1. This US Army photo from the archives of the ARL Technical Library shows programmers Gloria Ruth Gordon [Bolotsky] and Ester Gerston at work on the ENIAC.
Big Data Today
Today’s Big Data is a completely different beastie: immense, ubiquitous, and intangible. IBM says:
“…Every day, we create 2.5 quintillion bytes of data — so much that 90% of the data in the world today has been created in the last two years alone. (Businessweek puts this in context: By comparison, all of the earth’s oceans contain 352 quintillion gallons of water; if bytes were buckets, it would only take about 20 weeks of information gathering to fill the seas.) Big data comes from everywhere: sensors used to gather climate information, posts to social media sites, digital pictures and videos, purchase transaction records, and cell phone GPS signals to name a few. This data is big data. Big data is any type of data – structured, and unstructured such as text, sensor data, audio, video, click streams, log files and more.” Big data spans four dimensions: Volume, Velocity, Variety, and Veracity.
- An example of volume: Could we turn 12 terabytes of tweets created each day into improved product sentiment analysis?
- An example of velocity:Could we analyze 500 million daily call detail records in real-time to predict customer churn faster?
- An example of variety: Could we exploit the 80% data growth in images, video and documents to improve customer satisfaction?
- An example of veracity (or the lack thereof): 1 in 3 business leaders don’t trust the information they use to make decisions. Establishing trust in big data presents a huge challenge as the variety and number of sources grows.
The same things that characterize Big Data in the aggregate also apply to the data marketers are concerned with for their specific purposes. According to Steve McKee, writing on Bloomberg Businessweek on small business and marketing, big data is not just for big businesses. “Data analytics is just another tool to increase revenue and maximize profitability. For any size business to stay competitive, it’s imperative to get a handle on its data because its counterparts are. IBM’s vice president of enterprise marketing management, Yuchun Lee, suggests a very simple starting point: a company’s website. ‘Where there’s traffic online,’ Lee says, ‘there’s opportunity for Big Data.’”
For marketers, this means that the data that flows from website visitor tracking reports, email marketing, social media reporting, real-time reporting and analytics and more can be integrated and parsed to reveal what prospects and customers actually respond to. McKee addresses the role social media plays: “For marketers, social media’s initial promise was brands’ ability to interact with their fans in real time. Now its bigger value may lie in analyzing those conversations to determine customer sentiment, identify product improvements, head off nascent public relations crises, and understand evolving needs and perceptions.”
As marketing has transitioned from How We Sell to How They Buy, learning what “they” think and feel and want helps you orient your marketing to what works. Getting your slice of Big Data will help you get there.
Start the conversation: Aside from revenue, what are the most telling numbers you work with?