Next year will see the Internet moving more than one zettabyte, or one billion terabytes, of information per year, according to digital accessories manufacturer Cisco. This number will double by 2019. This much data has led to a new form of business analysis, using big data for marketing.
Making meaningful interpretation of data, large or small, is the province of the mathematical field of statistics. Data mining, at its simplest, involves finding the central tendencies of the data and interpreting their meaning. The two most common of the mathematical analytic tools is the average, called a mean, and the standard deviation. The mean gives a center from which to compare and the standard deviation tells an analyst how tightly the data clusters around the mean. For a marketer, this can tell the average marketing reach and the variance in impact of that advertisement.
Dashboard and Scorecards
Big data has given businesses the ability to create internal scorecards and compare effectiveness of marketing. Small data pools tend to be inaccurate as a dashboard analytic. Finding the average of two pieces of data is generally meaningless and making business decisions based on the inclusion of a third piece of data would be unrealistic. Big data, with thousands and tens of thousands of data points, give telling scorecard analytics from which to make solid business decisions.
Social Media Analytics
Social media networks and interactive blogs have placed content delivery in the hands of the masses. Advertising is no longer unidirectional, starting with the business as a point of origin. Now it is an interactive conversation, generating thousands of data results in one thread. The key challenge of social media analytics is identifying the emotional content, called a valence, of the thread. Since a Facebook feed is not a survey, it can be difficult to define whether the overall opinion of a business is positive or negative. Big data has opened up a world of granularity research that is focused on creating algorithms that tease apart the meaning of a statement within its context.
Big data now captures information that is geographic as well as written. In 2014, Walgreens used data acquisition techniques to identify geographic clusters of people with health care needs. They used this information to increase pharmaceutical offerings in these areas. Most smartphones have GPS functions that can be accessed, with permission, by businesses and marketers.
One of the benefits of big data analysis is that it offers increased accuracy for predictions. More data points allow greater predictive force for creating regression lines that offer insight into consumer behavior. Since the amount in the data set is directly linked to the predictive power of the set, being able to capture and store the information is important. Computer science researchers are finding that cloud-based storage and computing opens opportunities for small- and medium-sized businesses to gain the benefits of big data analysis.
With all of the analytic tools that big data offers, one of its practical upshots is that it opens a new world of interactive communication that can be algorithm based. If we take the analytical information that big data offers and make it recursive, creating a constant cycle of input and analysis, then the new frontier of marketing is to create a form of artificial business intelligence that will learn from and respond to consumer input.