Escaping the Data Paralysis Trap
An infinite loop (also known as an endless or unproductive loop) is a sequence of instructions in a computer program, which loops endlessly with no beginning and no end. The term has taken on other meanings in popular culture and also refers to a street on the Apple campus. For my purposes, an infinite loop is useful to help us understand data paralysis. The idea that we can use data to direct the tone and strategies for marketing plans is becoming complex. Mountains of data come in; we enter it into our repositories and executive dashboards, and then hope we can pull out useful morsels that prove the strategy we are using is the right one.
We know we need to manage risk by aligning the tactical day-to-day to do lists with the strategic corporate goals and objectives. These goals and objectives are valid. They should stimulate appropriate action to solve real problems. How do we measure the effectiveness of a marketing initiative? By tracking and analyzing metrics that have been defined and key performance indicators (KPI’s). The data being collected can be sorted through and evaluated via the SMART data analysis theory I touched on earlier. This is your salvation from being caught in the trap. Keep your eye on your objectives; know what qualifies as a success and what’s white noise.
As I’ve said from the beginning, I am a data mechanic. I work with data every day and learn while doing. All the tools in the world will prove useless if you’re collecting the wrong data, segmenting it the wrong way and analyzing it against a set of false or vague objectives. As a mechanic, the only real way to fix anything is to know what’s wrong. Otherwise, you’re just fishing in the big pond without a rod. Have you ever tried to catch a fish with your hands? Yeah, it’s not easy, and even if you do it, it’s usually pure luck. We can’t afford that in digital marketing. We need to set smart goals that are aligned with corporate needs. You need to get your hands dirty.
During the planning stage, collecting and harvesting good data will lay a solid foundation and greatly reduce the risk of paralysis. Being a data mechanic means learning to tell what is actionable data and what is extraneous or should be left behind.
In the next several posts, we will cover each element of setting smarter goals. This is all based on knowing the corporate business goals and objectives and aligning with them from the start.
We’ll use old and new data to make all our marketing goals meet five key characteristics:
These characteristics must be in a controlled infinite loop in the feedback process:
- Plan refinement based on data evaluation
- Focus on goals
- Reevaluate data
Then the data evaluation stage will produce successful results. We can turn the endless loop into a productive tool for marketing success instead of being paralyzed by the data we employ to define it.