The Memorial Day weekend gave me a little time to get caught up on some reading. Some of what I was reading were analytics reports (I know – get a life) and while I very much appreciate the cycle of continual improvement Google fosters within their analytics product, that cycle yields a continuously growing amount of data. The problem that I have isn’t so much understanding what I’m reading but trying to figure out why any of it matters to my clients. I also spend time figuring out which of the numbers are lying to me.
It’s no secret that there are an awful lot of bad actors in the digital world. Once it becomes clear how fraud is detected those bad actors move on to another form. If viewability is important, they create sites where there is 100% viewability but no content of any value. I had a client get all excited about an increase in referral traffic until I pointed out that most of that traffic was coming as a result of referrer spam. When we filtered it out, traffic was flat. Another prospect got excited by the large “stickiness” – time on site and pages viewed – that her site has. They were impressive until you filtered out the IP addresses of her employees, who spent hours a day on the site.
Silly things, I know, but it points to a common problem. An IDG study of a couple of years ago pointed out that nearly half of marketers said they struggle to make sense of the vast amount of data they get. The other half thinks they know what the numbers mean, yet many of their plans are built to achieve unrealistic metrics. The problem is compounded by what the paper identifies as the accuracy problem I mentioned above:
Why is data accuracy still such a big issue? One possible reason is a lack of investment in a defined data management process that includes ongoing, consistent data migration, data maintenance, quality control and governance. Too often data is held and managed in multiple organizational silos. This results in inconsistency, duplication, gaps and errors.
So while “garbage in, garbage out” isn’t a particular revelation, it does serve as an excellent reminder to take out the trash as best you can while compiling all of that data. You with me?