In my last post, I discussed marketing data as the most dangerous thing in your office and outlined how to tame it. Now, let's talk about how to draw insights from your data.
First, ask yourself a question: are you Nate Silver? If you are...um, hi, Nate. Thanks for reading. But more importantly, if you're Nate Silver or an honest-to-God data wizard, then you already know what you can and can't do with data. You can run all kinds of exotic analyses and make wild predictions that come to fruition. In short, you have nothing to learn from me. Godspeed.
If you're still reading, then you need to understand one thing: data don't tell you anything other than how to guess well. However, good guesses can help you more than you might think.
Let's go back to the previous discussion in which I suggested running banners in your data to see what you knew about your customers in the aggregate. Initially, this exercise helps you avoid the infamous GIGO or "garbage in, garbage out" problem. However, it also allows you to start making good guesses.
Start asking yourself what you can infer from the data.
For instance, if you know that you have a sizable population of customers who live in Florida, you guess that they have a need for warm-weather clothing and outdoor sporting goods year-round. If your prospect list includes a lot of electrical engineers, you can guess that they have an interest in hard-core technical data. You generally don't have to be an expert to make these kinds of guesses, but you do have to take the time to make them.
In other cases, you may want to borrow subject matter experts to help you make guesses. Maybe you not only have electrical engineers in your prospect list, but also chemical engineers. I don't know much about what differentiates the two, but if I had to make guesses, I'd enlist someone who does know. Similarly, I have no idea what consumers in another country might want.
Your subject matter expert could help you make guesses. Maybe he knows that chemical engineers always want to see an MSDS instead of the specs that the electrical engineers want. Maybe she knows that German consumers would never buy kitchen implements in green or that Argentinians really like video reviews.
As above, make a record of these guesses.
Next, we'll talk about what to do with these guesses.