Better Beats Bigger Data, Every Time.
"Better Data" vs. "Bigger Data" ― hopefully, this doesn’t even sound like much of a debate. Yet in many cases, the distinction isn’t so subtle. These two broad descriptions are often easily, and innocently, confused. Let’s try and clear that up a bit.
Oftentimes, marketers we help with marketing database development find themselves in a rush to “build their database.” Virtually all retail organizations today are tasked with “building the database.” CMOs know intuitively that amassing data about customers and prospects has value. One CMO recently gushed, “that data is gold.”
Not surprisingly, given the data was valued like gold ― a precious commodity ― then more must be better. And what came next was somewhat predictable after working with dozens of brands on leveraging their data to achieve scale and performance.
Customer, marketing, operations and finance all rolled into a singular database being constructed by a modest and already overwhelmed IT staff. Years went by before the project was killed ― and creating value with the data was postponed indefinitely.
Here are just a few of the key issues that develop when the focus meanders to “bigger” rather than “better”:
1. The Goal Isn’t Entirely Clear. If you begin with the goal of capturing and storing data, that’s what you're going to do. Conversely, if you begin with the goal of growing customer value, a discrete set of data points come into focus. How they are captured and organized is clearly informed, and how they will be utilized gets clearer from the start.
Similarly, marketing data can fail to meet the expectation when those expectations were only loosely formed shortly after the result was delivered!
2. The Culture Doesn’t Embrace Making Decisions With Data. Let’s face it. Historically, many organizations embrace decisions from the gut. Intuition and opinions rule, even as talk of using data to inform decisions is the norm. These organizations can only shift from valuing data by the terabyte to valuing data by its financial performance after the top-level decision-makers in the organization embrace data-driven decision-making.