This article is the problem with Big Data. Everyone wants to jump so many steps on their way to true 1-to-1 marketing using data as the cornerstone. Great marketing is always an evolution. One step forward using data brings results and different behavior is gleaned from that data. Then that data is taken and different questions are asked of the data based on the results using the previous data set. This is how marketing problems are solved using data.

Marketers can't take a dataset that is fairly large, one they are already struggling to make the most of anyway, and then be given a much larger dataset and told to "go make magic". Marketing with data is a disciplined venture. As a marketer, make sure you are making the most out of the data you already have before worrying about what keystrokes the customer is making or the "Internet of Things".

Always make sure the next step in the data is one that will bring you value today. Have a long term understanding of where the data can take you, but be disciplined in getting there or you just might miss a lot of insight on the way.

Not my favorite article, but some good points to live by as a database marketer. My main pet peeve is sending too many emails. This has slowly been getting better through the years, I don't find myself getting so many daily emails, which is a testament to analytics I would imagine.

There are a number of reasons, but there are several common ones. And there are a lot of reasons at different companies. But the main one that we've found is that customers receive too many emails. So, it's always important for an email marketer to understand [customers'] preferences—especially the mailing frequency that your customers prefer. It's always important not to overwhelm them with emails. When you send too many emails, you're causing them to tune out.... They'll look at them, and just ignore them.

Getting back a customer that has become inactive is very difficult, so have different strategies for customers that are trending toward inactivity. In my history I call these customers decliners and it is easier to save them before they become inactive.