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.

What Is Data Literacy?

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.

Big Math

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:

  • Speed up operational processes
  • Finely tune ad targeting
  • Determine which ad resonates more with which audience
  • Speed up customer service responses
  • Raise the predictive quality of business analysis reports
  • Deliver relevant communications to narrowly targeted audiences
  • Discover new services the customer base wants

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.

A Data-Driven Marketing Strategy

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. In a recent interview with a Forbes writer, Stoupa explains why he championed a data literacy movement:

"The marketing profession from 20 years ago, which was about big ideas, pretty pictures and fluff, is pretty much dead. About a third of CMOs use data and the [remaining two-thirds] aren't as data-focused... Data competency is the source of power for CMOs sitting in the C-suite."

Data literacy gives marketers the power to prove their campaigns were successful. It also gives them the power to move on from unsuccessful campaigns more quickly, saving the company money. Data will be as concrete in the marketing department as profits and expenses are in finance.

Stoupa delivers the good news:

"The reality is that the consumer is willing to hand over a lot of data. They will give marketers information that you can't find any other place. However, the consumer has high expectations that marketers/firms will use the information effectively. Data puts marketing on an equal or better footing versus their peers and in a much better position than in the past. It used to be that marketers lived in the 'grey' while data enables marketers to make fact-based decisions."

Marketers know that "the grey" can be an uncomfortable place. Data will bring them out of the fog and into the light, where campaign success and ROI can be proven more definitively in hard numbers. No more back seat to the finance people!

Step 1: Hire Data Talent or Partner With a Data and Analytics Company

Data and analysis companies have been finding and scrutinizing data for decades. Sports Authority settled on Axciom, but competitors include IBM, Accenture, Cognizant, and InfoSys. They've developed systems for onboarding new clients, and it's in their best interests to lead new clients through the entire process. You'll work with this company to capture from data your own systems and even purchase data.

Other data companies, like Luth Research, collect your consumers' online behavioral data and provide you with the insights necessary to make well-informed marketing decisions.

If your company is on board with creating a data-driven marketing team, hiring new experienced talent provides an alternative to bringing in outside help. Job market experts are warning, however, that the universities can't create data professionals fast enough, and demand will exceed supply for the foreseeable future.

With experienced team members either from a consulting company or inside, the company can begin to collect and organize data. Understanding customers, the sales process, operations, and more requires high-level algorithms that take additional months to hammer down. This is not an overnight change, but considering how much more relevant marketing campaigns can become with data, team members should agree to the pain of growth.

Step 2: Cultivate a Data-Focused Culture

Marketers who have spent entire careers more on the creative side of customer outreach may have a tough time transitioning out of the imaginative world. Even Sports Authority's Stoupa says that making the switch can take years. Not only do employees need to change attitudes, they will have to pick up new skills, work habits, and processes.

Step 3: Use the Data to Create More Differentiated Personas

Discover the commonalities between certain types of customers and consider widening your personas from five to 10. Better-defined audiences mean more effective messaging and better informed sales teams.

Step 4: Measure and Optimize

Don't stop with the tools and the talent. The best data you'll have access to is the results of your campaign. Build new campaigns from these results, and watch your ROI rise.

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image of Roseanne Luth

Roseanne Luth is the founder and president of Luth Research, a privately held market research company founded in 1977 and located in San Diego, California.

LinkedIn: Roseanne Luth