Data, data everywhere. There's no escaping it. "A carefully considered data strategy must be a CMO's top priority," according to a recent Ad Age column. Data is the "new oil" that fuels marketing today. Okay, understood. We all need to be familiar with customer and prospect data, and add it to our to-do lists. We will hire data scientists and chief data officers. Got it.
But are we marketers really comfortable with data? Don't we really wish it would just go away? Maybe the "Data Fairy" will come along and wave her wand, and we won't have to think about it.
This kind of magical thinking is a problem in marketing today. Some marketers are simply intimidated by data. Maybe they are math phobes. Chances are, they went into marketing partly because it seemed like a field where they could avoid too many numbers.
But no more. All of us need to get comfortable with data. We don't need to be ready to build statistical models. We don't even need to do math. But we have to understand the concepts. Here's how to get a grip on marketing data without getting your stomach tied up in knots.
1. Get some inspiration. Start with "Competing on Analytics," by Thomas H. Davenport. This ground-breaking HBR article puts data-driven decision-making in a strategic context that will help make the buzzwords tangible, familiar and downright interesting.
2. Don't panic. Many of the concepts around data, like segmentation and targeting, are already familiar to marketers. After that, perhaps the most complicated concept is predictive modeling, now more often termed predictive analytics.
Here's a simple definition: Modeling uses past behavior to predict future behavior. So, if you're in b-to-b, you might analyze a sample of your top customers, or prospect accounts that have converted to buyers, and build a model to identify their defining characteristics. With these characteristics, called variables, in hand, you can then go find others with similar characteristics, and expect that they will behave similarly, in response to similar stimuli, like a marketing message.
3. Start small. The whole idea of "big data" feels pretty overwhelming. But most data-driven marketing, especially in b-to-b, involves more manageable data sets. Consider a campaign to 10,000 machine-tool buyers. You might be calculating the cost-per-lead with a numerator of fewer than 500. It's pretty simple arithmetic.
4. Make friends with an analyst. To be sure, some statisticians get tied up in jargon and can be hard to understand. But there are plenty of them who understand business and can help bridge the gap between a math phobe and the data itself. Often, these translators hold job titles like "business analyst." Go find some, and take them out for coffee.
5. Dip your toe into the big stuff. In b-to-b marketing, one example of big data is online behavioral data that provides insight to help select audiences for targeted messages. This includes programmatic online media buying, where ads are served up across multiple digital channels according to specified firmographic variables, such as company size, industry and job role, all tied together with the individual target's cookie data. There is a lot of data underneath, to be sure, but conceptually it's pretty straightforward. And to reduce your anxiety even further, most of the analytical work is done for you by automated platforms like Choozle.
Being able to take advantage of the world of marketing data is just a wand's wave away.