Most companies and marketers are just now learning “data literacy.”
A survey by Kentico Software found that Big Data was the third highest priority for US digital marketers in 2015. Moreover, a recent Teradata study stated that just two in five companies report generating revenues from using their data aggressively, and an Economist Intelligence Unit survey of 530 executives found that 89% didn’t believe they were significantly better than their peers at using data.
In other words, most marketers are feeling pretty data illiterate at this point.
So, you have time to put a plan in place.
Becoming data literate takes understanding where the data is coming from and how it’s used to sell products.
Big Data has been around for decades, but it’s getting attention now because of the advent of the data collected by social and search channels.
The volume of what data aggregators can now collect astounds us. Every day, people around the world post 230 million tweets on Twitter and “like” 2.7 billion posts on Facebook. Those actions, along with user profiles, reveal each individual’s interests, shopping plans, actions, and more.
Social data, however, is just one kind of data that provides insights into customer behavior and trends. “Machine data” also comes from the sensors and even Web logs that monitor machine user behavior.
Used in industrial settings until recently, this “Internet of Things” is coming to a refrigerator near you! Our everyday household devices will increasingly be embedded with sensors and network connectivity, alerting manufacturers to when parts are wearing out or supplies running low. (Imagine Hewlett Packard giving you a call to say your printer ink is low and asking whether it can ship a new cartridge to you today.)
Machines aren’t the only data-collection devices. Large companies and many B2B entities collect product IDs, prices, payment information, distributor data, and more. Called “transactional data,” that information is used by companies to understand their customers and better run their supply chain.
Collected data is worthless without the analytics applied to it that help businesses determine trends, personas, and pricing. Raw data must be analyzed to gain insights into customers and trends.
With “data” as the new buzzword, however, new companies like InsightSquared, Cloudera, and Sumo Logic have joined the ranks. There will be plenty of business for math geniuses who can apply formulas to data points to determine your ideal customer’s email marketing preferences, the products they need currently, the likelihood of recommending a company, and so much more.
Recently companies have used Big Data and Big Math to:
Big Data and Big Math can provide the most specific recommendations based, not on guesswork or even best-practices (which may have nothing to do with your industry) but on concrete, data-driven insights based on your very own operations and audiences.
Here’s a story of a CMO who took a nationwide company from zero data to Big Data.
In 2014, Pep Boys Chief Marketing Officer Ron Stoupa moved to Sports Authority to take over the same role there.;