Those are three simple words—insights into data—and simplicity is a desired goal to reach when you’re trying to educate people about things like how to make data give you the insights you need to market effectively. I am a data mechanic. I’d like to say I’m a data planner, but it seems in the haste to keep up with the velocity, volume, and variety of data available today, we just charge off and do it most times. Thus, I become a mechanic to fix broken data rather than a designer to create sleek and robust data machines. Just like an automobile mechanic, people with broken data don’t care about how you fix it. They just sign the authorization to repair order and tell me to call them if it’s going to cost more than a gazillion dollars to fix it.

My purpose for being here is to right that wrong. Any good mechanic—data or automotive—will tell you that the best way to get good results from your investment is to plan responsibly, perform wellness checks on your investment at periodic intervals (KPIs), identify problems early (before the data machine breaks down), and do small course corrections. This will be a lengthy series of articles to teach and amaze you with effective techniques for implementing data plans for your marketing campaign that deliver the insights you need to engage your customer personally and directly.

If the message hasn’t hit home yet, pay attention. It’s all about insight into what the data means. It is not about integrating the data feeds of a thousand sources. The digital marketing teams, the product sales teams only care about the insights that data provides in giving them a competitive advantage to increase the profit margin and gain more sales. They do not care about how or why the tools used to gain that insight are working correctly. We also see new tools that are proliferating the market more quickly than new social media sites with an API to gain access to their data streams. When we talk about tools, and we will talk about tools, it will be in the context of what insight we can gain from the data as a result if using that tool.

Adobe approaches data as a means to gain insight. When I, as a data mechanic, am asked to fix a broken data machine, it is because a client and team lost sight of the objective, insight. In doing that, we work on harder and more complex problems than just integrating data. You have to embrace complexity if you ever hope to achieve simplicity for the benefit of our customers. The customer needs insight, not integration.